Amazon Web Services (AWS) has announced a series of changes to Amazon OpenSearch aimed at streamlining data log analysis.

A new purpose-built log analytics engine for the service will provide users with marked performance gains and up to 70% lower storage costs, according to the firm.

OpenSearch allows users to search, analyze, and visualize data in real-time, and is typically used for application monitoring, observability, and AI/ML search applications.

The hyperscaler said the update comes in direct response to surging volumes of log data handled by enterprises in 2026, largely due to AI.

Research from AWS shows that log volumes have grown between 30-40% year over year, which is stretching budgets and creating bottlenecks.

Amazon OpenSearch overhaul

As part of the update, Amazon revealed OpenSearch will now store data in the Apache Parquet format. This is a column-oriented data file format designed specifically for more efficient data storage and retrieval purposes.

The service previously relied on inverted indexing. Amazon noted the shift will deliver significant efficiency gains and faster search and retrieval capabilities.

“Apache Calcite parses and optimizes each query, then routes operations to the engine best suited to execute them: Apache DataFusion for analytical operations on columnar data, or Lucene for search predicates,” the company explained in a blog post.

“The two hand off mid-query, so a single query can search log content and aggregate the results without additional roundtrips.”

Amazon noted that OpenSearch now also supports the Piped Processing Language (PPL) and SQL query languages, both of which “execute natively” through the platform.

Amazon eyes optimized log analytics

From a performance perspective, Amazon noted users can expect significant improvements alongside lower costs.

OpenSearch now boasts up to four-times price improvements compared to the existing engine, based on internal benchmarks.

Users can also capitalize on two-times faster analytics queries due to the fact the engine processes data in columnar batches, even across larger data sets. A two-fold improvement on ingestion rates also aims to reduce bottlenecks.

“The optimized engine sustained 1.78 million documents per second at matched concurrency, approximately 2x the throughput of the Lucene baseline, while consuming less CPU,” the hyperscaler explained.

“Both domains ran with zero write rejections. For teams ingesting terabytes per day, the throughput advantage translates to fewer nodes for the same volume, or longer retention on the same infrastructure.”

How to access Amazon OpenSearch

The new log analytics engine is available now for enterprises in AWS regions where OpenSearch Optimized instances are supported, the company noted. Similarly, there will be no additional premium for the optimized engine.

It’s worth noting that the new engine is a setting selected at creation time, meaning users can’t add this to an existing domain or enable it within individual indices or fields within a general-purpose domain.

“To adopt the optimized engine, create a new domain and migrate your ingestion pipelines into it,” the company explained.

“Create a new domain in the Amazon OpenSearch Service console and select Observability as your use case. The optimized engine is enabled by default.”

The in-built console will provide users with a side-by-side comparison of capabilities based on individual needs.

“After your domain is ready, ingest JSON documents through the same Bulk API and client libraries you use today. No changes to your ingestion pipelines or application code are required.”

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SAS has announced new synthetic data capabilities and support for digital twins in a push to equip enterprises with concrete platforms for data-driven decision making.

Synthetic data is artificial data generated to resemble real datasets in every way that’s meaningful. These datasets are typically used to train AI and machine learning models without exposing sensitive data.

While generating synthetic data has benefits, obtaining it can be difficult, research shows. Organizations need access to the right algorithms to generate quality data, particularly if they’re looking to train a domain-specific AI model for very targeted use cases.

This is where SAS Data Maker is intended to come in. The service is a low-code/no-code platform that can quickly generate synthetic data in the quantities needed and to a high standard that’s auditable.

SAS first announced Data Maker in 2024 as an in-preview product with an unspecified release date, and has since acquired the UK synthetic data startup Hazy to improve its data generation software. It has now announced a targeted general release of Q3 2025.

The announcement was made at SAS Innovate 2025, the company’s annual conference held in Orlando, Florida. At the same event, SAS elaborated on work it’s doing at the other end of the data pipeline to make better use of existing business data for advanced data simulations, such as digital twins.

It gave the example of a recent project it has undertaken with the paper and wood-based product manufacturer Georgia-Pacific (GP), in collaboration with Epic Games.

The trio have leveraged Epic Games’ 3D Unreal Engine, originally developed for video games, combined with GP's enterprise information and SAS data technology, to simulate an entire factory at Savannah River Mill in Georgia.

Using the factory’s digital twin, GP could analyze the efficiency of its on-site automated guided vehicles (AGVs), as well as lower the barrier to entry for workers seeking analytics data on the factory.

SAS said its cloud-native Viya platform was integral in getting the project up and running, with GP having used tit to translate unstructured factory data into informations systems that formed the backbone of the digital twin.

“With the help of SAS and Unreal Engine, we can create realistic simulations of factory operations,” said Roshan Shah, GP’s vice president of AI & Products.

“Imagine watching AGVs navigate through a bustling factory floor, reacting to proximity alerts, obstacles and rare adverse events in real time," Shah added.

"The powerful analysis and photorealistic simulations delivered by SAS’ enhanced digital twins can enable decision making and boost output at Savannah River Mill. And they hold great promise for improving productivity, safety and efficiency at other GP facilities.”

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Enterprise analytics specialist Alteryx has announced the appointments of Jon Pexton as chief financial officer and Steven Birdsall as chief revenue officer.

The pair will lead the company's next phase of growth as it looks to drive further value through its AI Platform for Enterprise Analytics – a solution currently leveraged by more than 8,000 customers worldwide.

A seasoned financial leader, Pexton brings more than two decades’ experience that includes equity and debt offerings, mergers and acquisitions, international expansion, as well as strategic planning at high growth technology companies.

He has previously served as CFO of five different companies, most recently at healthcare practice automation software provider, Tebra. Prior to that, he held the same title at UserTesting.

In his new role as CFO of Alteryx, Pexton will spearhead the firm’s global financial operations, including strategic planning, budgeting, and investor relations.

Meanwhile, new CRO Steven Birdsall will lead Alteryx’s revenue strategy, covering sales and customer success, retention C acquisition, alongside partnerships and market expansion.

Like Pexton, Birdsall also arrives with a wealth of experience, having spent more than 25 years scaling revenue operations at both public and private companies. Most recently, he held the title of CRO at Qlik, where he led revenue growth and the implementation of data driven-strategies.

He has also previously served as Oracle’s senior vice president of HCM Cloud Application, as well as CRO at Anaplan, where he led the firm’s sales organization through its IPO. Other leadership roles include stints as CRO at Radial and COO at SAP.

In an announcement, Alteryx said its latest leadership hires underscore its commitment to helping customers scale their AI and analytics automation journeys.

“I am thrilled to welcome Jon and Steven to the Alteryx team,” commented Andy MacMillan, Alteryx CEO. “Their expertise and leadership will help our customers scale efficiently and unlock new opportunities for long-term success.

“Most importantly, they are both passionate about driving growth, building high-performing teams and championing innovation. Together, we’ll create even greater value globally to our customers, partners and community worldwide.”

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Data analysts around the world remain dependent on spreadsheets for preparation tasks that take up a significant portion of their day, according to new research.

A survey commissioned by Alteryx, spoke to global data, IT, and operations analysts across five industries to determine how the role is changing in the face of new technologies and rising automation.

Three-quarters (76%) of respondents said they still used spreadsheets to clean and prepare data for analysis, with just over half (56%) stating they used dedicated data preparation tools.

The largest proportion of analysts (42%) said they typically spend between one-to-five hours per week preparing and cleaning data, whereas with 40% this takes roughly up to 10 hours a week.

One-in-twenty analysts revealed they spend more than 10 hours every week on data preparation and cleaning, however.

When combined with data collection, the global average time spent on preparation was 10.57 hours, this was the second most time-consuming activity in the analysts’ day just behind the actual analysis of the data, which came in at 11.23 hours.

Half of the respondents said the complexity of data was the greatest challenge bogging them down, whereas data quality, security, and privacy were also cited as hurdles they frequently face when preparing it for analysis.

AI and automation will drastically change the data analyst role

AI tools have seen widespread uptake in the analyst profession, with 97% of respondents stating that they have integrated AI tools into some aspects of their workflow.

Tools for analytics automation are not far behind, with 87% of analysts adding they have also integrated these solutions into their daily activities.

More than half (59%) said AI tools increased their efficiency and productivity while 46% said it had reduced their workload and stress, citing an improved job satisfaction as a result.

On a weekly basis, the analysts said that utilizing AI tools saved them 8.6 hours on average.

The time saved using these tools looks to be shaping the analyst in new ways, with strategy becoming more heavily emphasized as AI removes some of the more repetitive tasks from the analysts’ daily workflow.

The vast majority (94%) of analysts agreed that their role impacts strategic decision-making, with 87% stating that their influence on business decisions has increased in the last year.

When asked how their role has changed in the last year, 85% of respondents agreed that their ability to respond to changes in the scope or direction of a project has improved.

Nearly four-fifths (79%) also said their ability to combine multiple sources of data compared to a year ago had improved since the previous year.

Overall, 86% agreed that AI had changed their role at least to some degree, with half of these going further to say it has reshaped their role “to a great extent” over the last 12 months.

This has improved slightly over recent years, with just 34% of respondents saying the same about the last 3 – 5 years, and 16% adding that they didn’t think AI had changed their role and had been affected by AI at all during this period.

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We all know data is the new currency, and the applications for data analytics are seemingly endless. Industries across the economy have been keen to adopt big data and analytics, but have done so to varying degrees of success. 

Football is an area in which data is everywhere. Indeed, the use of data analytics is rife – whether it’s quantifying different phases of play throughout a match or measuring player performance, or even identifying transfer targets.

There are countless data points available to coaches, presenters, commentators, pundits, and executives throughout the industry, who comb through the numbers and translate them into insights. 

But there are metrics off the pitch the football industry has less success in translating to real insights. Seeking to capitalize on the opportunities of on-pitch and off-pitch data is LaLiga, the premier division in Spain.

Tapping into rivers of data

To make the most of the untapped rivers of data flowing through football, the league created LaLiga Tech as a subsidiary that strives to capture and process the data generated throughout each facet of the annual competition, with the organization providing detailed analytics to the groups that make up the league.

“We know now that data is power – but if data is isolated, and you have silos of data that are unconnected, then you are not able to provide value for the clubs, or the fans,” says Fermin Martinez, senior data engineer for business intelligence and analytics at La Liga Tech. 

“But it's not only about having the data, you have to be able to join all the data together. In order to get real insights, you need to put a lot of different sources together and mix them.

“The real motivation is to be able to give value to clubs and fans. In order to do something with this data, we need a platform. We need the data lake we are using from Databricks, but we also need to apply data processing techniques.”

Collaborating with data off the pitch

Before the inception of LaLiga Tech five years ago, clubs were processing their own data and creating analysis in isolation. While this was useful for each club in isolation, it couldn’t provide insights that a larger data model would be capable of, Martinez says.

With 20 clubs all providing up to 25 data points a second throughout matches, this volume of data needed a place to be stored and processed. In the case of LaLiga Tech, this came in the form of Databrick’s data lake where, as Martinez puts it, the data originating from different sources can be “mixed” and insights can be generated.

“Before we started with Databricks, most departments inside LaLiga worked with different providers; these providers were the only ones able to access the data. As a result, the data was there but there was no connection between one source and the other because there was no connection between teams.

“We talk about data and how data is important. It's obvious that we need to get all this data together somewhere. The data lake is the place where all the data goes. Using Databricks, we are able to separate the data we receive into several states. We have a staging area inside this data lake, a prepared area where we start to prepare the data, and we have a final consumer area where the data is presented.”

Powering the sporting world with data

With these analytics, LaLiga Tech is able to provide insights to players and management around the probability of a player getting injured, the style of play when a goal was scored and, during the pandemic, how likely it was for players to transmit COVID-19 to each other during a match.

For the clubs and TV broadcasters, the data that’s generated provides the best time to start promoting season tickets for the next year. The insights will also reveal which events during a match – like yellow cards and goals – might cause people to tune into a game.

According to Martinez, these insights are not just reserved for football and can be applied to any sport from rugby, to tennis, to basketball. “We’ll need to use some different data sources,” says Martinez, “but the process is going to be more or less the same. We are now able to use what we have built to apply it to different leagues around the world.

"We want to package what we have built and to be able to apply it to a tennis competition, or the Olympic Games. If we talk about tracking the position of a player 25 times a second, this is something that a lot of sports could use. The conclusions we get may be different but the treatment of the information stays the same.”

Less than half of data and analytics (D&A) leaders believe their team is effectively delivering value to their organisation.

A survey of more than 500 D&A leaders globally found that just 44% reported their teams are unlocking tangible long-term benefits for their firms despite rising budgets and growing expertise.

D&A budgets have risen steadily as organisations seek to deliver greater value from data, streamline operations, and enhance operational agility. The mean D&A budget now stands at $5.41 million (£4.4 million), the research from Gartner found, while 44% of D&A teams also increased in size over the last year.

However, while rising budgets reflect increasing confidence in the data function, this is placing additional pressure to deliver impactful results, resulting in a negative impact on both teams and leaders, said Donna Medeiros, senior director analyst at Gartner.

“The demands being placed upon D&A, as well as increased investment, reflect a growing confidence in CDAO’s abilities and recognition of the data office as an indispensable business function,” she said.

“However, this leads to more work as pressure grows for D&A to achieve tangible business results.”

Gartner’s study found that D&A functions are receiving increased investment across a range of areas. Nearly two-thirds (65%) of leaders reported increased investment in data management while 63% and 60% reported investment in data governance and advanced analytics capabilities respectively.

Growing responsibilities present challenges

Chief data and analytics officers (CDAOs) now find themselves tasked with an expanding range of responsibilities within their organisation, Gartner found.

60% said they are now responsible for defining and implementing data strategies, with 59% also taking responsibility for oversight of said strategies.

Management of data-driven culture change was also a key responsibility highlighted by 54% of respondents.

This widening array of responsibilities means that some CDAOs are struggling to meet increasingly complex leadership demands, however.

Leaders that committed time to their own professional development were found to be far more effective than those who did not, highlighting the critical need for continual learning and evolution to accommodate the changing demands of the role.

Nearly half (43%) of “top-performing” D&A leaders reported increased effectiveness in both their own ability and the broader team by committing time to professional development, compared with just 19% of “low performers”.

“Successful CDAOs must be elite leaders,” said Alan Duncan, distinguished VP analyst at Gartner. “Top-performing CDAOs invest in their success by developing skills to thrive in ambiguous circumstances, articulate compelling value stories and identify D&A products, and services that can drive business impact.”

Human-related challenges to success

Difficulty meeting the complexity of demands placed on D&A teams is being exacerbated by an acute shortage of talent, Gartner noted.

More than one-third (39%) said that a lack of available talent had become a major impediment to success in the data function.

In fact, the top six key roadblocks for D&A leaders were all human-related challenges, including poor data literacy across the broader organisation and culture change acceptance.

APM and observability tools have become powerful analytics platforms that ingest multiple telemetry feeds, providing critical insight into application performance. The significant differences amongst the vendors mean infrastructure and operations leaders need to consider strategic monitoring choices.

This Gartner report looks at the capabilities of APM and observability tools, including security functionality, application monitoring on mobile, support for VDIs, and integrations with service management tools, amongst others.

Read now to gain insights into the current vendor landscape and how IBM Instana has been recognised as a leader in this field.

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As organisations seek to become more competitive, they are often moving to cloud data warehouses (CDWs) and cloud data lakes (CDLs) to help manage large volumes of diverse data and perform advanced analytics. In many cases they are using multiple cloud providers to fit their needs.

Organisations like the idea of a multi-cloud environment, which avoids vendor lock-in and helps them stay portable. They also want to take advantage of the best features and services of each cloud provider.

Download this study to see why the respondents agree that cloud is the future of data management and realise the five must-haves to modernise data and analytics.

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Today, organisations are investing heavily in new cloud-based processes, platforms and environments in order to achieve benefits like scalability, elasticity, agility and cost efficiencies. At the same time, organisations also understand that data is foundational to successful digital transformation, and cannot be an afterthought.

As these trends converge, IT departments are tasked with helping the business become cloud ready or cloud first, specifically as they modernise analytics. However, when it comes to managing the data in cloud data warehouses, data lakes and lakehouses, the typical approach by IT departments can result in increased cost and maintenance complexity–wiping out any benefits of modernising analytics in the cloud.

Download this whitepaper now to learn how to overcome drawbacks and realise four key elements of intelligent, automated cloud data management.

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CMS Distribution has teamed up with Irish cyber security firm GuardYoo to provide a new Attack Surface Management Cloud Service offering.

The hosted service, dubbed CMS Cloud Service Powered by GuardYoo, aims to help partners maintain high level attack surface management, leveraging functionality such as artefact analysis and forensic reporting.

CMS says its new offering’s primary purpose is to strengthen organisations’ resilience against vulnerabilities and cyber threats - whilst also enabling their growth and “reaching their full business potential”.

“CMS is delighted to have penned an agreement to provide GuardYoo’s pen testing and security services under our ‘CMS Powered by’ brand,” commented Nick Bailey, Alliance Director at CMS Distribution.

“Our partners look to us to provide innovative new products and services, and adding GuardYoo strengthens that considerably.”

Regularly used by first responders tackling advanced cyber attacks, GuardYoo enables organisations to reduce their attack surface to a minimum with its self-service style assessment platform.

It allows partners to create, execute, and analyse cyber security assessments on clients’ infrastructure and can be augmented with additional services - such as penetration and security testing, as well as digital forensics and threat intelligence.

CMS says GuardYoo’s level of research and frontline experience in cyber warfare, combined with its own value-added offerings, will provide partners with a sophisticated attack surface management platform to help their clients identify and remediate previously undetected vulnerabilities.

“It’s a real pleasure for us at GuardYoo to partner with CMS Distribution who have a strong history of delivering value-added services to their channel,” said Darren Sexton, GuardYoo CEO.

“Through our partnership with CMS, we are able to provide cybersecurity partners with a sophisticated Attack Surface Management platform to help their clients accurately identify and remediate previously undetected vulnerabilities."

TikTok has announced new initiatives aimed at improving transparency around the company’s data use, measurement of trends and moderation systems.

In a blog post, chief operating officer Vanessa Pappas laid out a series of plans in detail to involve researchers, industry experts and academics to test and advise on TikTok’s platform.

Researchers will be given access to an application programming interface (API) through which they will be able to study public and anonymised data about content on the platform. This will be made available later this year.

The short-form video hosting service and editing app is extremely popular, with an active base of over one billion users. If research led by the data is made publicly available, insight into the trends and data analysis of TikTok’s vast dataset could prove highly valuable to the tech sector.

Businesses could benefit from knowledge of the factors that drive content to do well on the platform, as well as an understanding of how trends grow in popularity to release videos before or during them. Often, by the time businesses engage with a viral trend, much of the user interest in it has waned.

This month, Ofcom published a report stating that TikTok is the second most popular news source for teenagers with 28% using it to inform themselves, just one percent behind Instagram’s 29% of teens.

This marks it as a vital frontier in the battle against disinformation, and the moves announced today will allow greater oversight into this ongoing issue. In the same announcement, the company pledged to publish information on covert influence operations in all further quarterly Community Guidelines Enforcement Reports.

Select researchers will be given a similar API focused on TikTok's moderation system, to probe existing content moderation systems and the current state of content on the platform. The API will also have the functionality to let researchers upload their own content, to see what is permitted, rejected, or passed on to moderators.

In addition, select independent experts will be given access to TikTok’s list of filter keywords, which it uses to identify content as harmful and asked to offer advice based on this.

Those chosen will include members of TikTok’s US Content Advisory Council, which was set up in 2020 to give industry experts a say in the company’s safety strategies and content policies. The expert members of TikTok’s regional Safety Advisory Councils, namely Europe, the Middle East and North Africa, Asia Pacific, Brazil and Latin America will also be included.

“We've been listening to feedback from different communities of researchers, academics, and experts, and are today sharing new initiatives to strengthen transparency and accountability of our platform,” wrote Pappas in the post.

TikTok and its parent company ByteDance have faced harsh criticism in recent months, with FCC commissioner Brendan Carr last month urging Apple and Google to remove TikTok from their respective app stores. This was prompted by growing concerns over the security risk posed by the app's data harvesting.

IT Pro has approached TikTok for comment.

Oracle has launched a new solution to help builders streamline data across construction applications.

Dubbed Construction Intelligence Cloud Analytics, the new solution builds on Oracle’s Smart Construction Platform. The unified platform blends construction applications and data to help owners and contractors continuously improve performance, according to Oracle.

"You can't manage what you can't measure," said Roz Buick, senior vice president of product, strategy, and marketing for Oracle Construction and Engineering.

"The new Oracle Construction Intelligence Cloud Analytics offering combined with the Smart Construction Platform's predictive intelligence engine and common data environment gives our customers a deeper, holistic understanding of their performance,” added Buick.

Furthermore, the Smart Construction Platform by Oracle combines capabilities from the firm’s engineering and construction applications, including third-party solutions in a common data environment, making collaboration a breeze.

Oracle announced the availability of its new analytics solution as well as enhancements to the construction platform at its Industry Lab in Deerfield, Illinois.

"We are increasingly focused on finding new and better ways to leverage our data to gain further insights into project performance and risk," said Brian Neal, project manager at Rudolph Libbe.

"Connecting and blending data for analysis will provide the broadest and deepest view into our operations, helping us to understand trends across our business and identify ways to keep improving how we deliver projects for our customers."

Social, mobile, analytics and cloud (SMAC) is a powerful way of thinking about how you do business, but it’s focused more on processes and platforms than solutions. You still need to identify your needs and goals within a SMAC framework.

This feeds into the larger topic of digital transformation – another buzz phrase that basically means updating your business model for the digital age. You might think you crossed that bridge many years ago, but SMAC reflects a sea-change that many haven’t yet caught up with. It’s even been described as the successor to the web, because it represents the new ways that customers interact with online services – ones that are multidimensional and reciprocal, in a way that the original web experience never was.

In other words, SMAC might not lead you directly to your goals, but it can light the way. Think of its elements not as merely a checklist, but as the pillars of your next digital transformation. We explore what SMAC is, how it’s applied, and why it might be worth exploring in today’s age.

SMAC is another of those marketing buzzwords, right?

Yes – but it’s more than that. Standing for social, mobile, analytics and cloud, it certainly does tick the boxes for a LinkedIn search term. Before consigning the phrase to the buzzword bin, though, it’s worth taking a moment to consider what it encapsulates. The combination of these terms constitutes a broad manifesto for interacting with your users and collecting data that can drive smarter business decisions.

How will this faddish ideology keep my business going?

Let’s be clear: SMAC is not a detailed game plan. It’s a helpful mnemonic for a multi-pronged approach that can help you reach your customers effectively. At a minimum, the social aspect means having a presence on social media, so your customers can talk to you, and you can, in turn, learn about their interests and activities.

Mobile means recognising that they might want to interact with you via a smartphone or even a wearable, which again gives you an opportunity to collect valuable insights.

Do we really need to be reminded that people use social media and smartphones?

It’s true, the fact that “social” and “mobile” are mentioned explicitly (and separately) does rather date the acronym. People first started talking about SMAC back in the days when social engagement was an exciting new currency, and a custom app was a necessity – not merely for the sake of brand cachet, but because the mobile browser wasn’t able to reproduce the desktop PC experience.

Now the situation is almost reversed, and social and mobile activity is so ubiquitous it’s easy to overlook. But it’s crucial to keep abreast of how these spaces are expanding and evolving, as they continue to throw up huge new opportunities to sell, communicate and learn more about your customer.

Do we really need new technologies for analytics?

Big data analytics doesn’t have to mean multi-sheet Excel workbooks or expensive online dashboards. My late cousin used to make parts for submarines, and his analytical process fitted on a beer mat.

The important thing is to learn from the data you collect. That often means letting the information speak for itself – start by looking for the peaks and troughs on the graph, as it were, rather than diving in with filters and queries. This can require a “big data” mindset, which calls for modern tools and methods.

Why does the cloud always need to be involved in everything?

The cloud part of SMAC may seem a bit bolted on, as it doesn’t directly shape your relationship with customers. But building your business on a public cloud platform such as Amazon Web Services (AWS) or Microsoft Azure allows you to quickly scale, iterate, segment and customise your offering to suit the demands and opportunities that are revealed by your social, media and analytics activity.

In fact, for most businesses, that sort of flexibility is worth having even if you largely ignore the other three ingredients – which answers your initial question.

Is SMAC too vague to be actionable?

The looseness of SMAC as a concept is part of what makes it useful – its principles can apply to almost any business. And thinking about its four parts together can help point you towards joined-up solutions, such as launching a social media campaign to encourage a certain demographic to install your app. Since the four initials are handily encompassed in one PowerPoint slide, it’s also an easy way to break down activities and costs into silos, and decide where next to focus your attention.

Boeing has struck a deal with space-based automatic dependent surveillance-broadcast (ADS-B) service provider Aireon to better predict and prevent aviation hazards.

Per the accord, Aireon will offer its flight data stream to Boeing, expanding the aerospace firm’s data analytics capabilities. Select Boeing airplane programs will have access to historical aircraft data, including near real-time aircraft event data, via AireonINSIGHTS.

“The global space-based ADS-B data from AireonINSIGHTS can help customers gain insights to key performance indicators on flight safety,” stated Aireon.

Boeing will notably integrate Aireon-provided ADS-B data into enterprise Safety Management System (SMS), in a bid to proactively monitor risks and ‌changing‌ ‌safety trends.

Oceanic, polar, and outlying areas can be monitored by space-based ADS-B, which adds to conventional ground-based surveillance limited to terrestrial airspace.

"We are investing in a data stream that can be transformed into safety intelligence," commented Vishwa Uddanwadiker, vice president of aerospace safety analytics at Boeing.

"We are adding this to our data analytics ecosystem to help predict and prevent safety risks, while identifying other opportunities to strengthen our Safety Management System."

Aireon CEO Don Thoma said, "The power of the Aireon data unlocks a cache of information for Boeing regarding the operations of its aircraft in the global airspace. With this integration, Boeing will have data to provide a full operational view of its fleet, and we are excited to partner with them.”

Datadog has launched a new service to help organizations aggregate, filter, and route ‌large volumes‌ ‌of observability data.

Dubbed Observability Pipelines, the vendor-agnostic tool offers customers with a unified view of infrastructure and application metrics, logs, and traces.

The granular outlook helps with lowering costs, reducing technology lock-in, standardizing data quality, improving compliance, and scaling observability practices, according to Datadog.

Most notably, businesses can gather, enrich, transform, sanitize, and route observability data from any source to any destination at petabyte scale. Rule-based throttles and reactive routing strategies ‌can also be deployed to protect against data spikes.

If need be, organizations can also choose to redact sensitive data from a data stream ‌before‌ ‌it‌ ‌leaves‌ ‌the company‌ ‌network.

"As the amount of telemetry continues to grow at an organization, teams are often completely overwhelmed—if they're not blind to—the runaway costs, reliability and compliance risks that come from a lack of visibility into infrastructure and application data," said Zach Sherman, senior product manager at Datadog.

“We built Datadog Observability Pipelines to give organizations a powerful way to take back control of their data, without compromising visibility for engineering, security and SRE teams," added Sherman.

Datadog’s Observability Pipelines also comes with an extensive list of integrations or built-in connectors that give organizations the ability to collect and route data quickly and easily to any existing tools.

This IDG eBook examines how data can be overwhelming to organisations large and small and demonstrates how a modern analytics and machine learning (ML) approach will help make data accessible to your entire organisation, opening up new ways to put your data to work and reinvent your business.

Download now to read how organisations are applying modern analytics with tips on how you can get your data to work for you.

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Telefónica Tech has announced the acquisition of UK-based Microsoft partner Incremental for up to £175 million, including potential contingent payments linked to future performance.

The move strengthens Telefónica Tech’s presence in the UK and Ireland, as well as its scale and competencies in Microsoft technologies, the firm said.

Launched in 2016, Incremental Group has become one of the leading Microsoft Dynamics Partners in the UK and is also a major player in the data and analytics market.

The company has been a Microsoft Business Applications Inner Circle member for the past three years and is one of just two partners in EMEA on the Redmond giant’s Global Advisory Board for data analytics.

The acquisition means Telefónica Tech now becomes one of Microsoft’s largest partners in the UK, with 16 Gold Competencies and 5 Advanced Specialisations.

Telefónica said the addition of Incremental’s business applications, power apps, data analytics and management capabilities to its cloud services portfolio will enable it to enhance its end-to-end cloud offering for mid-market, large enterprise, and government customers.

“We warmly welcome Incremental Group, and are delighted that this acquisition enables us to strengthen our position as a leader in the UK market for IT services,” commented José Cerdán, CEO of Telefónica Tech.

“We are now able to provide end-to-end Microsoft services, including digital transformation, managed services and data analytics, and achieve attractive cross-selling synergies with Telefónica Tech UK&I, complementing and positioning us as a leading Microsoft-focused company in the UK.”

Glasgow-headquartered Incremental has experienced significant organic and inorganic growth in recent years. Early last year, the firm acquired Redspire in a bid to expand its capabilities in the financial services market and become one of the UK’s largest Microsoft Dynamics partners.

It then snapped up data analytics company Adatis, which enabled the business to offer end-to-end digital transformation to customers.

Today, Incremental has more than 350 employees on its books, which will take Telefónica Tech UK&I’s headcount to around 1,000 staff post-transaction.

Neil Logan, CEO at Incremental Group, said the focus was on securing the “right support for the long term” as the business looked to the next stage of its development.

“Becoming part of Telefonica Tech propels us into the next phase of our journey and enables us to further scale the business, creating exciting opportunities for our people and our customers,” he said.

The data as a service (DaaS) market is slated to reach $61.42 billion by 2030, with a compound annual growth rate of 36.9%, according to Market Research Future (MRFR).

DaaS enables enterprises to better manage their data workloads, boost reliability and integrity of data, and decrease time-to-insight. Owning to the benefits, the service is an increasingly popular choice for data integration, management, storage, and analytics.

As more organizations turn to the cloud to streamline their infrastructure and workloads, MRFR forecasts significant gains for the DaaS market in the coming years. Microsoft, Facebook, IBM are among the market's dominant players.

Additionally, North America holds the largest share of the global DaaS market. The rapid market growth in the region can be attributed to unstructured data gathering in the commercial and industrial sectors.

DaaS is in the Asia Pacific region also poised to generate considerable revenue over the forecast period.

“Increasing uptake of cloud-based services and enormous opportunities across businesses provide better scope for the APAC countries to advance in the data as a service (DaaS) market,” MRFR stated in its report.

Mergers, acquisitions, and collaboration are a few strategies enterprises use to remain competitive.

As an example, Intermap Technologies, a geospatial information and content services firm, recently announced a new contract with a European airline, providing elevation data as a service for route planning operations.

In another instance, PhaseZero, a provider of B2B and B2C digital commerce software solutions, unveiled CxAnalytics, a tool capable of proactively managing sales and market share growth, in addition to mitigating critical risks. The service is another strategic move by PhaseZero as it continues to build out its multi-cloud enterprise SaaS application platform.

SolarWinds has acquired federal services provider Monalytic for an undisclosed sum.

SolarWinds has long entrusted Monalytic with the services and training necessary to help its public sector clients achieve optimal performance in their mission-critical systems.

The monitoring and analytics firm boasts extensive experience in integrating SolarWinds with legacy systems, in addition to installing SolarWinds software in complex environments.

The acquisition will strengthen the existing IT management and security services currently supplied to federal clients, the companies explained, and will combine SolarWinds' IT management solutions with Monalytic's expertise in highly secure environments.

SolarWinds CEO Sudhakar Ramakrishna said: “We are thrilled to welcome the Monalytic team to SolarWinds. This acquisition will enhance our ability to serve our federal customers and Partners.”

“In supporting our federal customers for over a decade, Monalytic has proven its ability to operate in the most secure environments and deliver fantastic value.”

In their role as SolarWinds certified professionals, Monalytic consultants will continue to work closely with SolarWinds' partner ecosystem and reseller network. SolarWinds is also hiring a total of 16 employees from Monalytic and plans to uphold the firm's autonomous status.

Joint services and offerings are generally available through SolarWinds' preferred public sector partners and procurement services.

“For existing Monalytic customers, nothing will change – it will only get better,” said Greg Fetterhoff, president at Monalytic.

“We will continue to help organizations perform at their peak and reap the benefits of their SolarWinds investment, and it will be even easier for SolarWinds users to access our services. We will continue to team with the SolarWinds channel partners to meet program goals. And we will continue all operations, but with more resources to do it even better.”

The end of the year should be a period for reflection, looking back over what we’ve accomplished during the last 12 months and thinking about the lessons we can apply to the forthcoming year. The best way to do this is through data, and when it comes to packaging data-driven insights in a fun and accessible format, there’s one clear winner.

If your social media feeds are anything like mine, you’ll have seen a slew of people sharing their ‘Spotify Wrapped’ results over the last few weeks. For those unfamiliar with this annual ritual, around this time of year, Spotify crunches through the vast reams of data it collects on its users’ listening habits and collates them into a fun little report for each individual user, showing what bands and genres they listened to most that year.

Spotify has essentially cracked the code to making mass data collection not only acceptable but fun, and each year, the flurry of activity as people share their results gives the company a healthy dose of free organic marketing. This isn’t, of course, a new observation, and neither is the idea that more services should copy it; Netflix, Twitter, YouTube, and basically every other online content platform have the capacity to offer users the same kind of insights into their habits. It remains surprising that to date, no other platform has made much of an effort to duplicate this obviously winning formula.

What’s even more interesting, however, is that no business software vendors have tried it either. SaaS tools of varying stripes have an all but unassailable foothold within modern IT, and as part of their continued operation, they have to monitor a huge number of data points covering a wide range of areas. The resulting data gives vendors everything they need to build reports highlighting a number of interesting trends and stats across every business.

Collaboration services like Slack, for example, could offer both individual stats (such as how many messages you send compared to coworkers, who you message the most, and how many new channels you joined that year) as well as organisation-wide figures like how many messages your company sends per day, the average number of GIFs shared per week, and so on.

Google – the reigning champion of data-driven business – could go even further for Workspace customers, collating data from across products like Google Calendar, Google Docs and Google Meet to show how many documents you shared with colleagues, the number of emails you opened without responding to, and how much time you spent that year in meetings compared to other staff.

This extends to technical staff as well, who are already highly metric-driven through tools like Trello and Jira. It’s not that much of a stretch to picture a ‘Jira Wrapped’ report showing a team’s average ticket completion time, or how many new tickets were opened that year compared to last year. GitHub already has an unofficial version of this – courtesy of developers Himanshu and Ishan Sharma – showing each GitHub user’s commits and pull requests for the last 12 months.

Admittedly, this concept isn’t without its perils. Without due consideration, this process could veer into the territory of overly invasive employee surveillance and behaviour monitoring, depending on what data points are being tracked. With that having been said, however, much of this information is already used by companies for KPI measurement and staff performance reviews. Presenting it in a more engaging, interactive style could, therefore, alleviate some of the apprehension and dread that can often accompany this process, as well as giving staff an opportunity to gain some perspective on their own methods, behaviours and processes that they may not otherwise recognise.

As well as being a fun way for employers to give staff insight into their activity, these reports could also provide useful indicators for organisations to base decisions on. Data-driven transformation continues to be a goal for many companies, and organisation-wide stats based on their staff’s tool usage could tell them whether they need to invest in more automation to speed up manual processes, where certain teams or departments may be under-resourced, and if de-emphasising meetings in favour of shorter email or IM updates might free up workers’ time for more productive tasks.

The fact is that all of this data already exists, and is surfaced in various ways throughout the tools in question, but it’s too sporadic and hard to find at present. Distilling it into an annual bite-sized roundup not only makes it more useful for both employees and businesses, it also provides a tangible benefit to the data-harvesting that most SaaS platforms carry out by default. If cloud vendors really want to embed data-driven thinking into their customers’ organisations, then their new years’ resolution should be to follow Spotify’s lead, and give us a reason to care about it.

Data drives almost every business decision today. So, the more data your business collects, the more critical the need to analyse and interpret it—this is vital for making the right decisions, fast.

Read this guide to learn how augmented analytics—which includes embedded AI and the ability to present data in easy-to-understand visuals—can improve every area of your business. Whether it’s enabling proactive sales and marketing campaigns, improving financial reporting effectiveness, or increasing supply chain efficiency, this eBook will show you how to extract maximum value from your data.

Analyse and interpret your data with augmented analytics.

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Google Analytics is a key tool in any digital marketer’s arsenal, and so naturally, there are a huge number of training courses available. Our list of some of the best Google Analytics courses and certificates offers just a snapshot of what's available.

On a basic level, website owners use Google Analytics to monitor page views and determine how well their sites are performing. However, Google Analytics is an incredibly sophisticated tool, and can be used for far more than simple graphs and charts. As long as website owners only use the platform as a tool to discover real-time metrics, they’ll be missing out on Google Analytics' full capabilities.

Although deploying it might be a walk in the park, users who aren’t familiar with technology might encounter a steep learning curve when it comes to understanding how some of the wider tools work. If you can get past this curve, you might just find you can transform your marketing strategy.

To give you an idea of what's out there, we've pulled together what we feel are some of the best Google Analytics courses and certificate programs available.

Our list of the best Google Analytics courses and certificates has been populated based on a combination of factors, including community reviews, the convenience of each course, and whether they cater for absolute beginners or a current professional looking to up-skill or retrain. Our goal is to provide a broad range of options to give you a good sense the market today.

The best Google Analytics courses and certificates

Take a look at the below programs and you’ll be an expert in Google Analytics in no time.

Get started using Google Analytics

Best Google Analytics short course for beginners

Provider: Skillshop (via Google)

Price: Free

Course link: Get started using Google Analytics

Course length: 1 hour

This course is a great option for those looking for a very quick overview of Google Analytics and its basic functions.

It designed to give you an understanding of how Google Analytics works and the skills to fully leverage its capabilities to accelerate your business goals. You'll grasp how Analytics collects, processes, and structures data in order to generate actionable insights.

This course is a solid choice for complete beginners, with short videos and step-by-step guidance condensed into an hour session. Also, as it's directly from Google, it provides an authoritative introduction to using its platform.

Google Universal Analytics Essential Training

Best advanced Google Analytics short course

Provider: Corey Koberg (via LinkedIn Learning)

Price: $20 per month (LinkedIn Learning subscription)

Course link: Google Universal Analytics Essential Training

Course length: 2 hours 40 mins

This course teaches users how to deploy Google Analytics to gain a better understanding of digital customers, including how they discovered your website and how they interact with it once they arrive.

The course covers the platform’s basic functionality, from setting up an account to generating reports, but the course's true value is in the advanced features deep dive. Instructor Corey Koberg shows you how to extract valuable insights from the vast amount of data available, including averages, segments, trends, and context.

LinkedIn Learning is known for high-quality business and tech courses. The instructor gets top reviews for explaining complex data clearly. This is ideal for going beyond basics to advanced data analysis.

Google Analytics Certification - One-Day Certification Guide

Best intensive Google Analytics certification program

Provider: Daragh Walsh (via Udemy)

Price: $129 (£49.99)

Course link: Google Analytics Certification - One-Day Certification Guide

Course length: Two hours

This course offers a step-by-step guide to passing the Google Analytics certification exam in just one day, with no prior experience required. The course includes complete certification training, a detailed exam overview, and over 200 practice questions.

The Google Analytics Certification is an industry-recognized IT certification that can boost your resume and increase your chances of getting a job in digital marketing. The course also includes tips on how to promote your certification and get hired.

For those short on study time, this highly-rated preparation course offers key tips and practice to pass the exam quickly. Students say it provides comprehensive training efficiently, saving them weeks of preparation.

Foundations: Data, Data, Everywhere

Best Google Analytics certificate program for switching careers

Provider: Google Career Certificates (via Coursera)

Price: $49 (£38) per month

Course link: Foundations: Data, Data, Everywhere

Course length: 22 hours

This course is the first in the Google Data Analytics Certificate program, which prepares you for an entry-level data analyst job – and therefore a much larger commitment than many others on this list.

You will learn about the role and skills of a data analyst, the data life cycle and analysis process, and the tools and terms used in the field – including Google Analytics. You will also explore career opportunities and best practices for job search. The course is taught by Google data analysts and includes hands-on exercises and quizzes.

This course is praised for its hands-on learning. It's a great option if you want training in Google's analytics tools, with a view of potentially changing careers.

Although it's part of a broader data analysis certificate, you can opt to purchase individual modules, and there is no requirement to complete the wider program.

Google Analytics 4 (GA4) Essential Training

Best Google Analytics 4 (GA4) course

Provider: Corey Koberg (via LinkedIn Learning)

Price: $20 per month (LinkedIn Learning subscription)

Course link: Google Analytics 4 (GA4) Essential Training

Course length: 2 hours

This course teaches you how to use Google Analytics to track, analyse, and report on-site visits, marketing goals, and ad revenue. Google product expert Corey Koberg covers the platform’s functionality and explains how to glean insights from the data available. 

You will learn how to measure traffic, conversions, ad performance, and ROI, and identify how people use your website. The course is designed to help you get, convert, and retain customers, manage user accounts, and more.

LinkedIn Learning offers another top-notch course focusing specifically on the newest GA4 platform. The instructor gets rave reviews for clear explanations tailored to beginners.

Google Analytics for Marketing - Boost Sales & Lower Costs

Best Google Analytics course for marketing

Provider: Joe Parys et al (via Udemy)

Price: $40 (£25)

Course link: Google Analytics for Marketing - Boost Sales & Lower Costs

Course length: 2 hours

The course aims to help marketers who are struggling to measure their progress and are confused about how to use analytics to boost sales and lower costs. The course is suitable for those who are keen to build new skills and improve their marketing strategy and results.

This course cuts through the jargon, offering focused training to those struggling to connect analytics to marketing strategy.

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A change in a system, like a customer updating their information or placing an order, produces a notification called an event.

To best manage the increasing volume of event producers and consumers in your TT ecosystem and make use of the information in event streams, your organisation needs an event-driven architecture (EDA).

Download this whitepaper to learn about the key capabilities of an EDA, like:

• Pub-sub and message-oriented middleware to reliably move event messages
• Streaming analytics, which applies machine learning to make decisions
• Event mesh, a dynamic infrastructure that allows message to be delivered across a distributed enterprise

The US Army has selected Palantir to implement its intelligence data fabric and analytics solution for the Capability Drop 2 (CD-2) program.

CD-2 is one of several initiatives Palantir and program executive officer (PEO) for Intelligence, Electronic Warfare and Sensors (IEW&S) are undertaking to modernize the Army's intelligence systems, alongside Capability Drop 1 (CD-1) and Tactical Intelligence Targeting Access Node (TITAN).

According to reports, Palantir will deploy its Gotham Platform for rapid defense decision-makingto support Army Intelligence users worldwide. Connecting disparate data sources, Gotham offers a federated intelligence data fabric and analytics solution that spans multiple levels of security.

Leveraging Gotham’s capabilities, the Army Intelligence community will migrate legacy programs to CD-2, strengthening its data foundation. CD-2 will also assist the Army with future modernization efforts supporting Joint All Domain Operations.

Additionally, Palantir’s data integration, correlation, fusion, and analytic capabilities will aid the Army’s strategies to combat near-peer threat actors.

“We look forward to the continued partnership with PEO IEW&S and the Army’s Intelligence Community in providing new and exciting technology that help them in their modernization efforts,” said Doug Philippone, global defense lead at Palantir.

Palantir has advanced to the next step in the Army’s competitive $823 million indefinite-delivery, indefinite-quantity (IDIQ) contract. In a "Test, Fix, Test" process, the firm will oversee the final testing and fielding of the Army's intelligence system.

Earlier this year, Palantir signed a pact with the United States Space Force (USSF) and United States Air Force (USAF) to support the country's armed forces.

Mavenir has announced its next-generation Operations Support System (ngOSS), expanding the MAVscale platform.

The new solution integrates artificial intelligence (AI), analytics, automation, and orchestration to enable intelligent network operations. With a microservices-based architecture, Mavenir's ngOSS deconstructs monolithic systems into smaller, autonomous components that provide insights, intelligence, and network control.

“By enhancing network performance, Mavenir’s ngOSS enables CSPs to improve the overall customer experience, lower operating expenses (OPEX), and reduce the risk of manual errors more prevalent in legacy OSS systems,” explained Mavenir.

Outlining key capabilities of ngOSS, Mavenir said the platform offers provisioning as a service across any cloud, regardless of vendor. Additionally, Mavenir’s Active Inventory offers a real-time view of the available resources and services across cloud and vendor applications and environments.

The Service Order Management feature, integrated with Mavenir’s business support system (BSS) solution, automates all parts of network operations, including service design, 5G slice management, and network service orchestration.

Lastly, Observability Framework collects and analyzes domain-specific metrics on infrastructure systems, including PaaS and CaaS.

“As CSPs advance toward automation, next-generation OSS will be a critical component to enable the network of the future,” said Kuntal Chowdhury, SVP and GM of AI and analytics at Mavenir.

Chowdhury added: “Using advanced AI and ML models to enhance network performance will help CSPs deliver superior customer experience, while scalable automation reduces manual tasks to lower maintenance costs and reduces the risk of human error.

"Mavenir’s ngOSS solution allows CSPs to break open the network and take advantage of Open APIs to increase agility and innovation, introduce new services, and monetize 5G with rapid service velocity.”

Northern Sky Research (NSR) has released version 2.0 of its proprietary Non-GEO Constellations Analysis Toolkit (NCAT).

The update adds to NSR's comprehensive analytical tools for benchmarking low Earth orbit (LEO) and medium Earth orbit (MEO) satellite constellations.

A multi-faceted toolkit, NCAT includes analytical models, input and output data tables, comparison charts, maps with satellites, orbital routes, footprints per constellation, and more.

According to the company, the latest version doubles input and output data tables to 56 sub-constellations and increases tool options to 15. NCAT2 also supports granular evaluation of mobile and fixed data applications.

“Two systems, Starlink and SES O3B, are now operational but many others, such as OneWeb, Telesat, and Amazon are in the pipeline,” said Christopher Baugh, NSR president.

Baugh added, “The rapidly increasing numbers in the Non-GEO sector drives need for tools to assess capabilities factually and in-depth. Driven by client feedback, NCAT2 incorporates new tools, including the ability to conduct assessment for fixed and mobility applications at global, regional or country-levels.”

NCAT2 comes preloaded with data, configurable filters, inputs, and visualizations. Specifically, the toolkit can be used alongside market data and insights drawn from relevant NSR research studies.

NCAT2’s other notable features include gateway housing and visibility assessment, exclusion angles, mobility heatmaps for 56 LEO/MEO constellations shells, and breakeven analysis of Non-GEO capital cost per Mbps

Commenting on outreach, NSR said its NCAT2 toolkit is intended for both business and technical professionals looking to understand Non-GEO high-throughput SATCOM in-depth.

“As thousands of LEO and MEO satellites beam tens of Terabits per second, they transform not only the space sector, but the adjacent telecommunications industry, making it vital for strategic decision makers of both value chains to evaluate potential developments. NCAT2’s configurable filters and visualizations allow that insight,” added NSR.

Allurion Technologies has extended its Virtual Care Suite to include a remote patient monitoring service.

Designed exclusively for weight loss practitioners, Allurion Insights includes automated weight-loss monitoring, analytics, and instant text/video communications to simplify remote care.

The tool is available to Allurion partner clinics for follow-up with patients after an Allurion Balloon (swallowable gastric pill) placement procedure.

“High-quality follow-up care is critical to achieving lifelong weight loss, and Allurion is committed to offering our providers the digital services they need to efficiently deliver care,” said Jeff Feldgoise, head of digital product at Allurion Technologies.

Feldgoise added, “Allurion Insights is an easy-to-use and powerful digital solution that is tightly integrated with all of the other components in the Allurion Virtual Care Suite. We have designed Allurion Insights specifically for weight-loss providers, tailoring it for their needs.”

Furthermore, Allurion Insights allows health care providers to access patient information collected via the Allurion App, Connected Scale, and Health Tracker. Using real-time messaging, dieticians can instantly communicate and share files with their patients.

A private yet secure video consult feature helps medical professionals communicate with geographically distant patients. Allurion Insights also includes notes, a lightweight digital medical record that allows clinicians to streamline patient care.

Allurion App, Connected Scale, Health Tracker, and Allurion Insights provide a comprehensive set of software and hardware for weight loss.

“With the launch of Allurion Insights, we have taken the Allurion Program to the next level,” said Shantanu Gaur, co-founder and CEO of Allurion Technologies.

“Between the best-in-class results of the Allurion Balloon and our expanding digital health capabilities, the Allurion Program has become the most complete weight loss solution on the market.”

BlackSky and Palantir have announced the results of their geospatial pilot project.

As part of their strategic partnership, BlackSky integrated commercial satellite imagery and analytics with Palantir's enterprise platform Palantir Foundry.

This combination creates an intelligent monitoring system capable of predicting Earth events from space. The solution pairs high-resolution imagery with deep analytics to encourage proactive decision-making.

In a series of exercises, the pilot program's capabilities were successfully demonstrated to experts in geointelligence. Most notably, the BlackSky-Palantir solution will help government and defense intelligence squads execute time-sensitive operations.

“Our joint pilot program with Palantir highlights the vital impact of real-time insights,” said Brian O’Toole, BlackSky CEO.

O’Toole continued, “The use of our data and analytics in these types of exercises drives demand for our geospatial intelligence as customers experience the rapid delivery of first-to-know insights that can inform proactive strategic decision making.”

Commenting on its analytics platform, BlackSky said Spectra AI spots potential threats in high-risk locations such as airports and construction sites. Through computer vision, the platform detects movement, damage, and anomalies in critical areas.

With Spectra AI incorporated into Palantir Foundry, geospatial analysts can access real-time insights on ground events without human intervention.

“Our collaboration with BlackSky radically compresses the decision-chain for warfighters,” said Shyam Sankar, Palantir Technologies COO.

“It gives users unprecedented control over orbital sensors and operationalizes AI insights from space to support better, faster decisions on earth. Palantir’s software continues to provide the operating system for operational decision-making at the edge across domains, from space to mud.”

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IBM Security™ QRadar® was again named a leader in the Forrester Wave for Security Analytics (SA), with the highest-rated security analytics offering of the 11 vendors evaluated.

IBM believes its continued leadership in the report is reinforced by its continued innovation in key areas, such as AI, threat intelligence, and world-class managed services.

Security and risk professionals should download this report to find out more about the benefits of IBM Security™ QRadar® and how it compares to the ten other top providers, and choose the best option for their business needs.

Data is taking on an increasingly important role within organisations around the world, but IT leaders have traditionally struggled to make staff truly understand or engage with analytics and business intelligence. There are many options for how to approach this particular challenge, but for Nationwide’s business intelligence team, the answer lies in building a culture of self-service data consumption.

This week, we’re talking to the leader of Nationwide’s business intelligence solutions Centre of Excellence, Richard Speigal, to find out how data literacy programmes and a federated model are helping the organisation’s staff to adopt data specialisations within their own teams - as well as how BI divisions can embed some of these practices into their own workflows.

Footnotes

• IT Pro Panel: Building a data-first culture
• What is Business Intelligence (BI)?
• What is a business intelligence analyst?
• Addressing the data literacy problem in the financial services sector
• Best data visualisation tips and tools
• How to measure data quality
• How to become a data scientist
• Home Office seeks AWS and Windows experts for criminal data lake
• Poor data is killing the smart city dream
• Infrastructure is everywhere — and so is your data
• Cloud can help you understand data – but only if you plan first
• The Locus Charter – a sign of the times
• The new generation of technologists
• Yes, you can use Excel as an enterprise database tool
• Need Excel training? Try these 10 cheap or free options
• NHS Test and Trace IT blunder blamed on Microsoft Excel glitch
• Why COVID-19 could spur a learning revolution
• The IT Pro Podcast: Data-driven doggos
• What can companies learn from object storage pioneers?

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Siemens has acquired Nextflow Software, an independent provider of particle-based computational fluid dynamics (CFD) solutions, for an undisclosed sum.

As part of the acquisition, Siemens will incorporate Nextflow's smooth-particle hydrodynamics (SPH) technology into its Xcelerator software. The integration will allow for rapid and automated analysis of fluid flow and transient motion applications in the automotive, aerospace, and marine industries. Use cases include gearbox lubrication, tank sloshing, spray cooling of motors, and more.

"Our customers need to leverage sophisticated simulations earlier and more often in their design process, and this is creating a strong demand for rapid and automated CFD of dynamic gas-liquid flows," said Jean-Claude Ercolanelli, senior vice president of simulation and test solutions at Siemens Digital Industries Software.

Ercolanelli continued, "Meshless technology has emerged as a leading solution to greatly reduce the setup and solving times for this class of problems, accelerating time to results and prove the behavior of products at a reduced time and cost."

The Siemens Digital Industries Software suite caters to a broad range of mechanical and electrical design scenarios with computer-aided design and high-fidelity tools.

With Nextflow Software's SPH technology now included in the Siemens' Simcenter Xcelerator portfolio, engineers can capitalize on the complementary benefits of meshless and mesh-based solvers to address design challenges, added Siemens.

For instance, in applications where it would be best suited, SPH-flow Explorer can be 5 to 100 times faster than conventional finite volume (FV) solvers, simplifying a week's worth of simulations into a few hours, with superior results over FV.

"We are very excited to join Siemens and expand the scope of CFD simulation for our customers," said Vincent Perrier, Nextflow Software CEO.

"Today, there is no single validation approach that fits all industrial applications. As engineering problems become more complex and design cycles are shortened, analysts must find the optimal trade-off between accuracy and computation time. Nextflow Software's SPH solutions nicely complement the existing CFD offering in the Simcenter Portfolio to overcome challenges of complexity and long run-times."

The following article originally appeared in Issue 12 of IT Pro 20/20 as part of a new series that invites industry experts to give their take on some of the most pressing issues facing businesses today. To sign up to receive the latest issue of IT Pro 20/20 in your inbox every month, click here. For a list of previous issues, click here.

Historically, the financial services sector has struggled to realise the benefits data can offer. Despite awareness from business leaders that access to the right data at the right time can accelerate business value, the sector often falls behind, in part due to a persistent digital and data skills gap.

Even when businesses have equipped people with the tools to effectively integrate data, financial services organisations haven’t always trained people with the requisite skills to understand it.

Our industry faces two significant challenges to data literacy. The first is to break a perception that we implicitly understand data because we deal with financial matters. The reality is that while we can use structured reports or dashboards to accurately measure what has happened, we generally do less exploration to understand why things happen. The second challenge is overcoming the embarrassment from colleagues throughout the business of asking for or accepting help when it comes to interpreting and acting on data.

If we want our industry to keep up with consumer demand and remain competitive, a cultural shift in attitudes toward data needs to take place – and we have to put people at the heart of it.

That’s why at Nationwide, we’ve embarked on a programme that is helping us make a shift towards a data-driven culture, where every employee is empowered to embrace data in decision-making. Our Business Intelligence (BI) team has implemented an approach, with our partner Qlik, that aims to help all employees become ‘Fit to Fly’ when working with data, helping them make decisions through self-service analysis and reporting.

Expanding data access

The first pillar of activity we embarked upon as part of the ‘Fit to Fly’ approach was raising awareness of the importance of data and how it can be a productive tool to help employees improve their decision-making. From creating drop-in days where we showcase our analytics tools, to setting up ‘data speed dating’ sessions to explore new ways of working and troubleshoot any challenges, the process not only helped us improve the perception of data in our organisation, it critically also helped us better understand the challenges employees were facing. This process validated our belief that a huge portion of our team’s time was being spent on preparing data rather than providing insights from it, but we also learnt that some people just weren’t especially confident using the data they did have.

This learning then informed our next objective, to make analytics-ready data accessible to those that need it. By democratising access to our analytics applications, we were able to put the power to self-serve data insights into the hands of all our employees – not just the BI team.

With the appetite for data use growing, we also needed to find a consistent way of visualising data sets. If the same data is presented differently in every meeting, it can easily feel like you’re starting at zero every time.

To overcome this challenge, we established a Visual Vocabulary application based on the Financial Times model that breaks down visualisations into logical categories, essentially acting as a ‘menu’ of what our analytics teams can produce. For business stakeholders, it helps us identify the most appropriate way to visualise data and derive insight, and for developers, it’s a technical timesaver that aids design consistency.

Home-grown experts

Our data team also includes a smaller group that is dedicated to driving and maintaining adoption of our solutions. Where the team see a reduction in usage, they will make an intervention, which could be a call, arranging a solution review, or just inviting colleagues to one of our weekly drop-in sessions. The team develop and deploy learning aids that are short, punchy and easy to consume and use existing engaged business users to record video learning clips, with the benefit of the explanation and learning being in a language their colleagues understand, not “data speak”.

To encourage teams to be more collaborative with data, we also have an accreditation programme that nurtures highly skilled employees as ‘platinum level Qlik-experts’, who understand both the technology and our data strategy. This gives them more freedom, helping them become ambassadors of change and fostering knowledge-sharing throughout the organisation.

In the 80s and 90s, tobacco sponsorships were as synonymous with Formula 1 as Fleetwood Mac’s ‘The Chain’ – and, it’s a testament to the power of advertising that many of the sports most famous cars and drivers can still conjure the memory of a certain brand of cigarette.

The Williams Renault driven by Damon Hill in 1996 won the Championship, and a mental image of the winning car will show a giant ‘Rothman’s’ logo. Four years earlier, Nigel Mansell did the same but his Williams car is as famous for its great big yellow advert for ‘Camel’.

In 2006, when motorsport’s governing body, the Fédération Internationale de l'Automobile (FIA), brought in a sport-wide ban on tobacco advertising, nine of the ten Formula 1 (F1) teams had some form of cigarette logo on their cars. However, over the last 15-years, this advertising space has been largely taken over by technology firms.

For the 2021 season, there are logos for at least two technology companies on each car; Oracle is the proud sponsor of the RedBull team, the UK’s Darktrace has a prominent spot on the McLaren’s spoiler, Kaspersky is right at the front of the Ferrari and chipmaker AMD can be seen on closeups of Lewis Hamilton in the Mercedes.

NetApp has also partnered with the UK’s Aston Martin team, which is back in F1 after an almost 60-year absence. The firm is providing cloud services to help collect, store and process data from the car, but it’s also a chance to promote NetApp in Britain. The company’s UK director, Chris Greenwood, tells IT Pro that the deal was a great opportunity for the firm to be linked with a British company, pointing out that the NetApp logo appears next to a Union Jack at the front of the car. A space that would not so long ago have been dominated by tobacco brands.

Up in smoke

The influence of tobacco in Formula 1 can be traced back to 1974 with Marlboro’s first partnership with McLaren. The famous brand of cigarette, which is owned by Philip Morris International, is perhaps more well known for its lucrative collaboration with Ferrari, which has arguably produced the sport’s most iconic cars. However, the tobacco industry as a whole was heavily invested in F1 from the mid-80s and lingered well beyond the millennium. But its involvement in sport, in general, goes back hundreds of years, according to sports advertising expert Tim Crow.

“When sport got organised and got big back in the 20s and 30s of the 20th century, you'll find a lot of tobacco advertising and sponsorship happening then,” Crow points out. “But obviously TV cameras moved in in the 50s and 60s, and at the same time, the legislators were starting to outlaw cigarette advertising on television. So they needed to find another way to do advertising and get onto TV and sport represented a very good way.

“Professional sport was still growing, still learning the ropes. And big tobacco came along and offered big checks, and sport took them. So it was that combination of sport getting big and getting the TV cameras in, and tobacco companies having to find a new way of getting onto TV without being able to use TV advertising.”

In the case of Formula 1, cigarette branding almost covered every available space, from cars to drivers’ suits to massive billboards above the race tracks. Its impact was so great that it was still being felt decades later with the 2013 movie Rush, which tells the story of James Hunt’s rivalry with Niki Lauda. Hunt’s 1976 McLaren carries the Marlboro logo and its repeated use in the film forced the British Board of Film Classification to rate it ‘12A’.

Value in Kind

Modern Formula 1 cars are virtually IoT ecosystems with nearly all components connected and fitted with sensors. Swaths of IT professionals are at the roadside and even further afield, monitoring and analysing continuous streams of data about every facet of performance. Everything from the tread of the tyres to the health of the driver is translated back to the team with various forms of cloud software used to inform race strategy and even predict car failure.

They're by no means the most lucrative sports sponsorship deals, but unlike the tobacco companies, tech firms are providing more than just hefty fees. They offer ‘value in kind’ deals ,where F1’s sprawling mass of engineers and analysts can access some of the most advanced hardware and software in the world.

For example, Darktrace isn’t improving the McLaren car, as such, but it is protecting its data and the IT teams that analyse and share it. Likewise, Oracle has supplied cloud infrastructure to the RedBull team and Mercedes uses HPE’s edge computing services. Simply put, the modern version of F1 couldn’t function without the cloud and analytics, and it has been that way for a number of years. It’s this context that makes F1 a great place for technology sponsorships, Crow suggests.

“So they give the team's stuff that the teams need to go racing,” Crow explains. “And instead of having to pay cash to do that, they give the teams their people and their knowledge and their expertise and their time and their services to do what is called ‘value in kind’ deals.”

“These are a big feature of sport, particularly, for example, in the Olympics where 60% of the value of total Olympic sponsorship is value in kind deals by B2B companies, who provide the Olympics with a whole range of products and services that the Olympics could not do without in order to put the show on.”

Similarly, the organisers of F1 also have deals with large tech companies. AWS has been a collaborator for the last few years, providing cloud and data analytics services as well as statistical platforms for use in TV broadcasting. A lot of the information that the drivers and teams have is also fed through to the live stream of the race. So you at home know more about the state of the car than which cigarette brand formerly paid for it.

Data has been described as everything from the new gold, to the new oil - but really, it’s much more than that. Data has become more than just a valuable commodity, for many businesses, it’s essential for their very survival. However, immersing yourself in data carries its own risks.

For Or Lenchner, CEO of data collection platform Bright Data, many organisations make the mistake of trying to run before they can walk, gathering as much data as they can with little thought to what their actual needs are, and how they’re served by the data they’re gathering.

“Data isn’t the new gold,” says Lenchner, speaking on The IT Pro Podcast; “it's the new water. But you know, you can drown with too much water – so just take what you need. No more. You can always scale up in the future.”

The most valuable tip for businesses who want to experiment with data collection and analysis, he says, is to eschew fancy AI-powered tools altogether, and start with manual processes.

“There’s no replacement for just doing it yourself for the first time. You can throw terms like AI and ML into the air, and yeah, they'll handle it. But what the hell; I mean, you know what data you need. So just grab the data that you need, and later on scale up.”

Implementing mass-scale data collection, he said, is a waste of time and money if you don’t know what you’re looking for. When Lenchner started as a product manager, he said that his most valuable data came from simply calling customers and asking them a few basic questions.

“As a data company, it took us, like, four years to implement our first data warehouse,” he says, “not because we couldn't, but because we didn't want to; we had so much to do with the basic data that we collected internally.”

“If you're doing a good job, you'll need to scale up to more places, gathering more data, which is great. Just, you know, start reasonably.”

Combining artificial intelligence (AI) with remote asset monitoring helps organisations identify the right alerts among the hundreds generated daily from critical assets. This allows you to optimise your processes and minimise condition-based inspections by your staff, allowing you to deploy maintenance only when necessary.

Here are six reasons why you should consider remote asset monitoring with AI.

Data is a vital commodity in modern business, but there’s a growing movement based on openly sharing it for mutual benefit. This trend has neatly intersected with the ongoing coronavirus crisis, in the form of the track and trace efforts which are being used to measure and limit the spread of the virus - but how exactly is open data being used to fight the pandemic, and what lessons can we learn about the use of open data in a business setting?

In this week’s episode, we’re joined by Amanda Brock, CEO of industry body Open UK, to find out more about how open data is contributing to relief efforts, the pitfalls of poorly-planned strategies, and how organisations can collaborate on data initiatives.

Footnotes

• European Commission's new president pledges action on AI
• What is big data analytics?
• What is big data?
• The IT Pro Podcast: Data-driven doggos
• Why transparency is key to promoting trust in artificial intelligence
• What is open source?
• UK gov faces legal action over Test and Trace data retention
• NHS Test and Trace IT blunder blamed on Microsoft Excel glitch
• UK gov abandons contact-tracing app in favour of Apple-Google API
• The IT Pro Podcast: Tech's coronavirus triumphs and tribulations
• The GSMA’s impractical ideas for contact-tracing reveal the scale of the challenge
• IT Pro Live: It's open under the cloud
• IT Pro Live: How Pro Football Focus became the NFL's secret weapon
• OpenUK
• Data: A resource much too valuable to leave unprotected

Subscribe

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• Subscribe to The IT Pro Podcast on Google Podcasts
• Subscribe to The IT Pro Podcast on Spotify
• Subscribe to the IT Pro newsletter
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Microsoft always uses its annual Ignite conference to show off all the latest tools and features it has planned for its Microsoft Teams platform, and this year the company hasn't disappointed.

The company has taken steps to address a few of the more inconvenient aspects of Teams, whether that's through UI changes, better admin controls, or with wider integration options. Although the update list is pretty comprehensive, we've picked out some of the more important updates that are either available now, or coming soon.

UI improvements

New Together mode scenes - before end of 2020

Teams’ Together mode, first announced in July, is that somewhat unsettling feature that pulls each user together into a virtual space, such as an empty auditorium, which is said to make participants feel less like they’re on a video call and more part of a cohesive group. Microsoft plans to expand on the number of scenes available to users by the end of the year, although it’s not clear what precisely these will be.

Custom layouts – before the end of 2020

Also due to arrive over the coming months is the ability to customise the layouts of video meetings and how information is shared with other participants. An example given is the option to have a presenter’s video feed transposed on top of their PowerPoint slides.

Teams Panels – early 2021

Provided we have all returned to the office by early 2021, Microsoft will be rolling out its own range of door tablets that sit outside of a meeting room and give information on its availability. These new devices will provide another way for users to reserve space, view upcoming meetings, and identify free slots. These will be largely supplied by electronics firms Creston and Yealink.

Channel information pane – available now

A channel info pane has been added to give a quick activity summary of things like users, posts, and pinned files, which can be used by new users to get a sense of what the channel is about, or by existing members to catch up on recent activity.

Better search results – before end of 2020

Search is also getting an overhaul, so that finding messages, people, or files should soon be far more intuitive. The results page has been redesigned to surface more appropriate results that are based on content or individuals that you interact with most.

Alternate meeting types

Breakout rooms – October 2020

Microsoft is also adding what it calls ‘breakout rooms’, a feature that meeting organisers can use to split up participants into smaller groups – something which could prove especially useful for training sessions. Presenters will also be able to jump between rooms, make announcements to the team as a whole, and end the individual sessions on the fly.

Meeting recap – before end of 2020

One of the more sorely needed updates will arrive in October in the form of Meeting Recaps. This new tool will collate a meeting’s recording, associated transcripts, its chat history, and any shared files into a single window that is then automatically shared in the meeting chat tab. It can also be configured to automatically add this info to the meeting event entry in an Outlook calendar, as well as the meeting details tab inside Teams.

Better support for webinars – before end of 2020.

Microsoft is also adding more sophisticated tools for supporting webinar sessions. These include the option to use event registration with automated emails and make use of a post-session dashboard that details viewer engagement – although it’s not clear how comprehensive this data will be.

Better calling tools

Improved calling features – before end of 2020

Over the next few months Teams will be getting a handful of new calling features, including an alternate view that shows contacts, voicemail, and a user’s calling history in a single window.

Users will also soon be able to connect a call queue with a channel in Teams, the idea being that users can then collaborate inside the channel while taking calls in the queue. This should be particularly useful for those handling, for example, an IT help desk, where they can transfer the queues to relevant channels on the fly.

New calling plans – available October

Microsoft Calling Plan countries are set to expand, bringing calling services to Austria, Denmark, Italy, Portugal, Sweden, and Switzerland.

Team management tools

Teams templates – available now

New templates are generally available today that let Teams admins quickly deploy Teams environments with predefined channels and suggested apps, each tailored to specific industries, such as banks or hospitals. Admins are also able to construct their own templates if they want to standardise how Teams is deployed across an organisation.

Member limit increase – before end of 2020

Microsoft is increasing the number of allowed members on any given Team from 5,000 to 25,000.

Better app integrations

Wellbeing and productivity – available October

Better analytics tools for monitoring wellbeing and productivity will soon be added that offer managers a more informed way of making changes to how they and their staff access Teams.

Microsoft has also partnered with meditation app Headspace to create built-in tools that help to improve employee wellbeing and reduce stress. Teams will also be getting a ‘virtual commute’ feature that allows employees to decompress after a long day and gives them time to disconnect from work. Both of these will be coming in the first half of 2021.

SharePoint Home – before end of 2020

Users will soon be able to download the new SharePoint home site app that allows admins to build a portal to a company’s intranet from within Teams. This comes with all the customisable options you might expect, including the option to change naming schemes, branding, and navigation to specific resources.

Approvals – available in October

Microsoft is overhauling the process for completing approvals in Teams, allowing users to create, manage, share, and act on approvals within the Teams environment. An approval process can trigger from a single chat window, or from a dedicated Approvals App.

Microsoft is also adding new integrations with Adobe Sign and DocuSign before the end of 2020.

Security improvements

Customer Keys – before end of 2020

Microsoft is adding a tool that lets customers add an additional layer of encryption to their data using their own keys, on top of existing Teams encryption. The same function already exists in SharePoint Online and OneDrive.

Microsoft Graph API for Teams Data Loss Prevention – available now

Leaving public preview is the Microsoft Graph Change Notification API for Teams messages, which allows developers to build apps that are able to monitor messages in near-real-time and trigger actions that prevent potential data loss.

Teams Export – available in preview

A new API is available in preview for developers that allows the exporting of either 1:1 or group chat messages, along with any associated files, images, or user mentions.

More powerful admin tools

More options for company branding – before end of 2020

Teams admins will soon be able to customise their custom line-of-business application catalog using their organisation’s branding – which should make it much easier for end-users to discover these apps organically.

Bulk policies – available now

Admins can now assign policies in batches of up to 50,000 users, allowing for better control over how Teams features are utilised.

Delegate device management – available now

Allows global admins to set controls that only allow lower-level admins to view and manage the devices section in the Teams Admin Center – effectively allows global admins to control the permissions of other admin functions.

Smarter analytics and automation

Improved power BI app – before end of 2020

Changes to the way Power BI interacts with Teams should make it easier to discover data from across the organisation, as well as speed up the process of creating visualisation from Excel. Power BI is now designed to be a centralised place for users to analyse data, as well as enhancing how users engage with Excel inside chat windows and channels.

New Power Automate app – before end of 2020

The new Power Automate app will bring with it a new set of templates that make it easier to automate processes within Teams, as well as a much friendlier UI. New options for automation will also be added, such as automated meeting creation and automated message actions.

Resource-specific consent (RSC) – available now

Teams now supports the option to install RSC-enabled apps that let admins control how much data is accessed by individual teams, without having to change global permissions. Other app functions can include creating, renaming, or deleting channels, reading messages, creating tabs, and reading settings.

Single sign-on – available now

Thanks to an integration with Azure Active Directory, Teams now supports single sign on (SSO), allowing developers to build apps that allow users to sign in using the same account used for Microsoft Teams.

Streamlined support for Android

Earlier this year, Microsoft launched a new product called 'Collaboration Bars', essentially video conferencing hardware that's powered by Android and plugged into Teams. Unlike its Microsoft Teams Rooms hardware, this Android range is meant for smaller teams, focus groups, or instances where a budget version would do just fine.

This week the company announced two things in relation to this hardware. Firstly, the company is simplifying things somewhat by bringing this Android version under the same branding as the main Teams Rooms. However, what's more interesting is that Microsoft is working with partners to develop new form factors beyond the simple integrated media bar, so we could soon see a new range of Android devices built for Teams.

Microsoft has announced the launch of a fully managed service that allows developers to add an array of communication tools to existing applications in a bid to help improve how businesses connect with their employees and customers.

Described by Microsoft as a first of its kind from a major cloud provider, the fully managed service, dubbed Azure Communications Service, lets businesses add voice and video calling, SMS text messaging, and instant chat support to mobile, desktop, and web apps, regardless of platform or device.

It's currently possible for developers to add chat capabilities to existing applications, for example, by using Azure Functions. However, this is a fairly lengthy and laborious process involving sourcing code from GitHub and manually testing the application.

Microsoft claims the new set of APIs cuts much of the complexity out of the process, allowing for new integrations to be created "in a matter of minutes" using "just a few lines of code".

Perhaps its biggest selling point is that these functions can then be integrated alongside other Microsoft services, including Azure Cognitive Services. This means businesses will be able to deploy tools like sentiment analysis and translation on top of any chat functions they add to their apps.

New chat functions will also benefit from any tools the base application has access to, which could be particularly powerful if those apps already have access to wider business operations, such as the company's website.

Azure Communications Service will run off the same global network that underpins Microsoft Teams, the company added, allowing for much of the backend work and ongoing maintenance to be handled entirely by Microsoft.

Microsoft also confirmed that all communications, regardless of how they are delivered, will be encrypted and adhere to GDPR and similar frameworks.

The Azure Communications Service is the latest move from Microsoft to try and expand its footprint across business communications, having already opened up Microsoft Teams to third-party applications – apps that customers may have been reluctant to abandon in favour of Teams.

According to Nick McQuire, senior vice president of Enterprise Research at CCS Insight, Microsoft has managed to position itself as a major player in what is traditionally a telecommunications role.

"Azure Communications Services takes all the experience Microsoft has gained from its remote development and communications solutions during the pandemic and turns them into key developer services," said McQuire.

"The shift to remote everything during the pandemic has meant that developers are now more attracted by communications-based features in their applications. It's an area of opportunity that telcos worldwide have failed to grasp over the past few years and above all, shows that Microsoft has ascended to become one of the world's most important communications companies as well."

Voice and video calling and live chat functionality are available today, and support for both SMS text messaging and dedicated phone numbers will arrive in October.

Microsoft has announced a host of new security updates to coincide with a strategic shift that pulls all of its detection and event management services under the new Microsoft Defender brand.

Microsoft Defender represents the "broadest resource coverage" of any security portfolio in the industry, the company claims, spanning identity protection, endpoints, cloud applications, and infrastructure, to name a few.

This means all of Microsoft's extended detection and response (XDR) tools will now sit alongside its suite of security information and event management (SIEM) software, offered as a single umbrella brand in a bid to reduce complexity.

For customers, this new direction will take the form of two separate packages, namely Microsoft 365 Defender, tailored for end-user environments, and Azure Defender, built for cloud and hybrid infrastructure. Both of these packages bring their own product name changes, with Microsoft effectively abandoning the 'advanced threat protection (ATP)' theme for most products.

Microsoft 365 Defender will replace all instances of Microsoft Threat Protection, the name given to the suite of products covering identity, endpoint, email, and app security, launched just two years ago.

Included in that Microsoft 365 Defender suite is an updated version of Microsoft Defender ATP, now known as Microsoft Defender for Endpoint, bringing with it expanded support for Android and iOS devices.

Microsoft Defender for Office 365, previously known as Office 365 ATP, and Microsoft Defender for Identity, previously known as Azure ATP, will also feature as part of the Microsoft 365 Defender suite.

The second package, Azure Defender, is described as an evolution of the Azure Security Center (ASC) and repurposes a number of its tools, although the original version ASC still exists. Firstly, Azure Defender for Servers will replace the standard version of ASC, while both Azure Defender for SQL and Azure Defender for IoT will both replace their respective ASC versions. All of these will be packaged inside Azure Defender.

Aside from the name changes, Azure Defender will bring a new look with a unified dashboard inside ASC, as well as expanded protection coverage for SQL on-premises, Kubernetes, and Azure Key Vault. It will also cover industrial IoT, operational technology (OT), and building management systems, largely thanks to the acquisition of CyberX in June.

"Today we're delivering a new set of security, compliance, and identity innovations to help all customers simplify and modernize their environments by embracing the reality that the past seven months have likely reshaped the next 10 years of security and digital transformation," said Vasu Jakkal, corporate vice president of Microsoft Security, Compliance, and Identity, announcing the rebrand.

"We hold a differentiated view among our peers that security should not only encompass all critical aspects of security -- including cybersecurity, identity and compliance -- but that these components should be tightly integrated, and built right into the products and platforms that businesses are already using."

Also updated, but still separate from the Microsoft Defender branding, is Azure Sentinel, a tool that collates all of an organisation's security logs and threat data into one window. This has been given an updated search functionality and the option to create watchlists for specific threats. It's also now possible to create user and entity behaviour profiles that can be paired with Microsoft's own security research to monitor for unseen threats.

Beginning in November, Microsoft will also be cutting the cost of Azure Sentinel for a limited time, which it estimates will help a typical organisation of 3,500 users save around $1,500 per month.

Once-in-a-lifetime events are, as the name would suggest, very few and far between. Those that are completely unforeseen are even fewer. Unlike the 2008 economic crisis or the dot-com bubble before it, the COVID-19 pandemic is one of those occasions when everyone was taken by surprise and the economic and social implications have already been significant, with more aftershocks predicted.

For businesses, this is an extremely tough time and it’s hard to see a light at the end of the tunnel, particularly as things as fundamental as how and where we live and work are being disrupted on a seemingly permanent basis.

Data analytics, however, may hold the answer not only to how businesses can survive these turbulent times, but even reinvent themselves and thrive. This week, Adam and Jane are joined by Libby Duane, co-founder and CCO of Alteryx, to discuss this and how organisations can make better use of data analytics in the longer term.

In the news this week, some of the biggest names in Silicon Valley have been getting a grilling from the House Judiciary Committee’s antitrust panel, Intel has said goodbye to its chief engineering officer following further delays to its next generation of 7nm chips, while 11 UK Councils are being awarded £800,000 to build on digital services created during the pandemic.

Footnotes

News

• 4 Big Tech CEOs grilled by House Judiciary Committee's antitrust panel
• Intel ousts hardware chief following 7nm woes
• UK councils awarded £800,000 to develop innovative services
• Bridging the data gap to digitise Britain's railway system
• How coronavirus has accelerated the digital transformation of Britain's public sector

In-depth

• Why humans and machines work better together
• Businesses warned coronavirus disruption 'could last a decade'
• Four business benefits of AI-powered analytics
• Why the coronavirus pandemic could prove fertile ground for startups
• Riding the business rollercoaster safely
• How Bank of America uses AI to improve customer service and take on competitors
• The IT Pro Podcast: Do you need a CDO?
• The IT Pro Podcast: Digitising dinosaurs

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A newly-formed UN-backed global alliance of think tanks is working on delivering a platform which will use artificial intelligence (AI) to help policymakers mitigate the effects of the coronavirus on public health and the economy.

The Collective and Augmented Intelligence Against Covid-19 (CAIAC) is formed by Stanford University’s Institute for Human-Centered Artificial Intelligence (HAI) and non-profit think tank the Future Society.

CAIAC aims to establish an advisory group consisting of UN entities, such as UNESCO and the UN Global Pulse, and use the “rapidly expanding collection” of global health, social, and economical data on the coronavirus pandemic in order to “enable the world’s decision-makers to confidently take action”.

The idea behind CAIAC’s platform is rooted in a UN initiative called the Global Data Access Framework (GDAF), which uses big data and AI to achieve the UN's 17 Sustainable Development Goals.

CAIAC is planning to initially focus its platform on using mobility data and AI to monitor contagion chains, identify and address inaccurate information on COVID-19, and recognise areas which are most vulnerable to the pandemic in order to deploy the appropriate interventions required.

In order to provide CAIAC with the AI technology that will power the decision-making platform, the alliance’s founding members are partnering closely with private sector companies including C3.ai, stability.ai, Element AI, Axis, GLG, and Planet.

Michael Sellitto, deputy director of the Stanford Institute for Human-Centered Artificial Intelligence, said that COVID-19 “represents a shared and urgent global challenge”.

“AI can play an important role in helping us emerge from the pandemic by organizing the vast quantities of data and emerging research, and combined with human intelligence, surfacing critical insights to support evidence-based decision making. Through this alliance, Stanford HAI and CAIAC will help connect the breadth of research across Stanford with public health leaders, policy makers, and others worldwide on the front lines of this crisis,” he said.

According to Cyrus Hodes, co-founder & chair of the AI Initiative at The Future Society, the pandemic has “accelerated innovation and global cooperation with the blossoming of thousands of bottom-up initiatives to find solutions”.

“Creating a coherent, truly holistic, knowledge platform for policy makers to navigate the flow of information has become a necessity. Fortunately, modern technologies such as AI can be used to harness vast amounts of disparate data and produce meaningful insights,” he said. “CAIAC will build this ground-breaking decision-making tool for global leaders to help solve the pandemic and accelerate the economic and social recovery.”

Artificial intelligence is about more than adding a chatbot to tick a marketing box. AI, within the context of analytics, is about automating what was previously manual, and using the computing power of the machine that was not possible before.

This whitepaper looks at how AI can be leveraged to power analytics in your software platform. AI-powered analytics offer an opportunity to add real value to your customers, and a point of differentiation for your application.

Download it now to discover how embedding AI-powered analytics into your applications can give you a competitive advantage, and what questions to ask before selecting a platform.

Stringent funding cuts are threatening the safety of prosecutions based on digital evidence, experts have claimed. Police officers failing to understand complex digital evidence, a huge backlog in evidence processing and a lack of legal aid for expert defence witnesses are all contributing to miscarriages of justice.

Digital devices, particularly mobile phones and PCs, are routinely used in criminal cases and can provide detailed, time-stamped evidence that’s useful to prosecutors and defence teams, but what happens when the system fails?

“Simultaneous budget cuts and reorganisation, together with exponential growth in the need for new services such as digital evidence, have put forensic science providers under extreme pressure,” a House of Lords select committee said in its Forensic science and the criminal justice system: a blueprint for change report last year. “The result is a forensic science market which is becoming dysfunctional.”

With swingeing cuts to the Ministry of Justice, experts fear the situation is unlikely to improve.

Bulk collection

Police forces have habitually been criticised for a lack of digital crime expertise. Most police forces now have digital units of their own, with official data showing that 80% of digital forensics is performed in-house. However, the police units are largely set up to process routine actions, such as capturing hard drive data or phone images, and often lack the expertise to delve deeper or perform reconstructions of actions logged on a device.

“The issue is cost,” Peter Sommer, who works on criminal cases and lectures on digital forensics at Birmingham City University, said. “Most units are operating at more than 100% capacity and they are still trying to deal with backlogs. They have expanded dramatically, but they are still doing a lot of volume processing and are heavily reliant on particular tools.

“What they don’t have is the luxury of people who can spend a day thinking about implementing tests or the latest standards,” Sommer said.

Mark Stokes, chief of the Metropolitan Police’s Digital, Cyber and Communications Forensics Unit, has admitted his unit is working with a seven-month backlog and, despite renewed efforts, told a House of Lords committee last year that the service “cannot meet the demand currently with what we have”.

Amid this backdrop, experts believe the police are becoming over-reliant on the output of automated systems, which streamline evidence gathering, but issue reports that untrained officers don’t understand.

“The volume side of things has got to a level where it’s becoming dangerous,” says Angus Marshall, a lecturer in digital evidence, forensic investigations and quality standards at the University of York and another independent forensic expert witness.

“Most police forces have adopted an automated digital device examination workstation that is deployed in police stations. Regular police officers are trained to use the kiosk, which spits out a report and it’s left to the officer to interpret it. The officers often don’t understand what they are seeing.”

Marshall cited a case where police were ready to charge a suspect they believed had been using his mobile phone in the moments before a serious accident – something that could lead to a lengthy prison term.

“The officer was convinced that was what had happened because the report showed a lot of files being changed in the time of the collision,” he explains. “On closer inspection, what it actually showed was that the mobile phone had disconnected from the Bluetooth system of the car when it lost power and had shut down some applications – that’s a major difference and could have gone forward as a prosecution and resulted in a wrongful conviction.”

The officer had noted files labelled “plists” and assumed that they were playlists, which would suggest user interaction with the handset before the crash, while the files actually referred to Properties, which changed when the handset disconnected.

“That motorist was particularly lucky,” says Marshall. “It could have ended with all manner of problems.”

Data black hole

Collection of data is only the first step in the prosecution process, and according to experts the way that data is handled and shared is equally problematic – especially when it comes to clarity over what evidence from handsets might be used by the prosecution, as well as data that’s been collected but isn’t part of the prosecution’s case.

“It should be automatic that any evidence that’s been found that’s not being presented by the prosecution should be disclosed, at least in list form, so the defence can ask for it,” says Marshall. “This is again symptomatic of cost-cutting within organisations like the CPS [Crown Prosecution Service], that they don’t have the time and resources to make sure the job is done properly.”

The disclosure situation came to a head when a series of rape cases collapsed after it became clear prosecutors had not provided the defence with all the evidence they had collected.

In one example, the defendant pleaded not guilty in a rape case claiming the act had been consensual and part of an ongoing sex game. At the last moment, the defence was given access to 57,000 messages that showed the pair had a relationship, evidence that saw the accused acquitted after a fraught two-year investigation.

“There have been a number of cases where the disclosure of evidence has been highly problematic and led to the collapse of cases,” says Ruth Morgan, director of University College London’s Centre for the Forensic Sciences.

“There were a number of cases that collapsed in 2017 due to issues with the disclosure of data that led to a review by the CPS of all rape cases in 2018, and this is an ongoing challenge. It’s a particular challenge as the amount of data available is increasing so rapidly and finding what is relevant can be difficult when time frames are limited.”

Unaffordable expertise

In addition, not all defendants will have access to an expert witness to delve into the investigation’s reports, as the legal aid budget has been cut by £350 million since 2013.

“If the defence hasn’t engaged an expert and taken advice, they might not know that a dataset is worth looking at,” says Marshall. “Whether you get the funding depends on the strength of your argument, but it can be a bit hit and miss.”

The Legal Aid Agency requires three quotes from forensic experts and for the defence to justify reasons why forensic testing is necessary. It will usually offer the work to the cheapest company regardless of quality, leaving defendants at risk.

“The only way you can challenge a [digital forensic] reconstruction that’s been done for the prosecution is to say, ‘Haven’t you been making assumptions?’ or ‘Maybe we could rearrange the evidence and present another story’,” says Sommer. “It works on an adversarial system – prosecution and defence – and for this reconstruction work you need to actually have an expert hired by the defence to test the assumptions made by the prosecution.

“The great weakness is that the funding available for defence experts is pretty miserable – the legal aid authority will have arguments about how much is necessary and their grant may not be sufficient for everything that a defendant would like.”

AI to the rescue?

The solution often proposed by senior officials is artificial intelligence: that an ever more automated service will reduce backlogs and streamline the system. But there are fears amongst practitioners that more automation could lead to more mistakes.

“AI in the criminal justice system terrifies me,” says Marshall. “At least with a human being, you can challenge them and ask how they reached their conclusions – with AI systems, good luck. For triage it’s fine, for suggesting devices to look at it’s fine, but producing primary evidence, please no.”

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Commvault has rebuilt its data analytics platform "from the ground-up" with a host of fresh features that aim to tackle customers' data protection requirements.

The firm's data analytics and governance service, Commvault Activate, has been issued with three additional tools that are geared towards addressing concerns around data protection compliance.

The update was announced at Commavult GO 2019 in light of the EU's General Data Protection Regulation (GDPR), as well as moves in the US to replicate these laws, for instance, in the form of the California Consumer Privacy Act.

"Enterprises today need to be ready to take on complex data governance, compliance and storage optimisation challenges if they want to avoid heavy government data privacy fines, reduce unnecessary IT costs, and build customer trust," said the firm's vice president for product management, Ranga Rajagopalan.

File storage optimisation allows for the visualisation of data and file access controls, while the sensitive data governance tool can give customers a way to profile particular types of data and give it additional layers of security through encryption. The final dimension, dubbed search and ediscovery, allows for processing legal hold requests.

Together, the additional functionality aims to give customers the tools to ensure the data they manage is compliant with these tough regulations.

The platform itself, meanwhile, can now be used as a standalone product without adopting Commvault's other product and services centres on backup and recovery.

"We built this product, we reimagined it from the ground-up, we rebuilt it," the company's newly-appointed CEO Sanjay Mirchandani told delegates. "This product has incredible potential. We've recalibrated pricing to make it easier for you to consume.

"All of this without requiring our backup product to drive it. You can use it just as it is, as a standalone product. We're giving you this so you can truly protect, manage, control and use the data."

One example of the new functionality in practice, outlined by Rajagopalan during a press event at the conference, centres on identifying sensitive data such as social security numbers. Users could, hypothetically, identify data patterns like social security numbers, and purge them from primary storage, as well as from backups.

As part of the file storage optimisation module, customers can also customise how long data is retained, and set policies that automatically archive or remove data after a period of time has elapsed.

The government's new data strategy is at risk fo collapse before it has been launched due to several challenges including legacy IT and leadership problems, and a lack of progress towards overcoming them.

The leadership on various projects is fragmented, and it's not clear which government agency is responsible for driving changes needed to improve the government's use of data, according to parliament's Public Accounts Committee (PAC).

To highlight the level of fragmentation, the Department for Digital, Culture, Media and Sport (DCMS) is responsible for data policy and Government Digital Service (GDS) is responsible for standards. The former prime minister Theresa May stripped elements of government data function from GDS last year.

Meanwhile, the Data Advisory Board is the senior oversight board, but it is not well attended by senior officials. The government, moreover, has not yet appointed a Chief Digital Officer (CDO) after pledging to do so.

Both DCMS and the Cabinet Office, under which GDS falls, have made little progress in developing the data strategy since they announced it in 2018, meanwhile, opening a preliminary 'call for evidence' as late as June this year.

"Poor quality data in government leads to failings in services provided, poor decision-making and an inability to understand how best to improve. Issues with data come up in many of this Committee's reports," the committee's MPs said.

"Over many years government has increased its use of technology and data. However, departments have been left to develop their own processes for managing data, leading to inconsistency across government.

"Data has not been treated as a valuable asset, so it has become normal to 'work around' poor-quality, disorganised data. A step-change in the government's approach to data is long overdue."

The MPs found that ageing IT systems across the government make it difficult to use data effectively and efficiently, meanwhile, with data expensive or even impossible to extract.

This has had an effect in measuring the progress on various government projects, such as Universal Credit, where data would have been used to assess whether programmes or systems were functioning as intended.

The report has been published days after GDS held its annual Spring conference, where it fleshed out its plans to gather data from visitors to its gov.uk website. The data would then be used to improve and personally tailor government services through the online platform.

The report added that rising concerns about data protection could lead to overcompensation that might then potentially hinder innovation. This could mostly arise in the form of civil servants being reluctant to share data across departmental boundaries.

Analytics, the process of deriving information from raw data, is an important practice that businesses have tried to master for as long as such data has been available. In a short space of time, it's evolved from a fairly basic concept to an advanced practice incorporating technologies like machine learning and artificial intelligence (AI).

Text mining is one such evolution, which takes the basic idea of deriving information from data and applying this to vast volumes of documents, letters, emails and written material. As with other conventional analytics, the aim of text mining is to convert raw data into meaningful information which can then be used to support other processes.

Text mining has only really been possible thanks to the advent of AI and more specialist technology like natural language processing (NLP), given that to produce effective results you need to trawl through vast quantities of data at pace. If deployed correctly, text mining has the potential to open new insights for your organisation.

How does text mining work?

Before your organisation can take advantage of text mining, any text-based data needs to be structured – in other words, text mining is a secondary process. For example, data contained in streams of uncategorised documents is considered unstructured.

To give this kind of data structure, businesses often deploy relational databases, where the data is organised based on connections between stored items. This would need to involve a variety of processes, such as parsing of text or pattern analysis, before it is considered structured. Once in this form, the data can be translated to something more visually appealing, such as charts, maps and tables.

Unleashing the power of natural language processing is one key method used to structure raw text-based big data. This technology uses data in combination with algorithms to add context to the way machines try to understand spoken language. It essentially tries to replicate the process by which a human might read text, and often serves to understand and define potentially vague words, like 'bow' for example. It's also embedded in most AI-powered virtual assistants, like Apple's Siri or Microsoft's Alexa.

NLP is deployed as part of this process to churn through reams of documentation in a way that would otherwise be too costly and time-consuming for any human, identifying the most relevant and important nuggets of information, based on any particular request.

One important branch of text mining is sentiment analysis, which involves combing through vast quantities of documentation to summarise how certain groups of people, either customers or employees, feel towards a certain issue. This could be used to learn how customers feel toward a brand, such as using text mining on web forums, or can be used to assess worker morale by subjecting internal emails to analysis.

Relationships, patterns and key facts are isolated and then turned into structured data so that AI can conduct further analysis on the data and identify insights based on what was demanded in the first place.

Benefits of sentiment analysis

Once assorted into a more structured format, the data can then be exposed to algorithms designed to give businesses high-quality insights that were impossible to glean through human-led analysis.

Sentiment analysis is one key application of text mining that can give businesses the exact thoughts and feelings about a company, or a particular aspect of a company. The insights could range from customer attitudes towards a brand to the morale of employees within the organisation.

In the former example, the text absorbed into the text mining process might come from online reviews, social media, customer interactions via email, as well as call centre interactions. These can be turned into data points to identify patterns that point to common threads in the way people perceive a certain brand. The information can then be presented in such a way as to devise strategies to solve negative branding and improve standards and practices.

This form of data analytics can also be applied within an organisation to monitor the way that workers interact with each other through workspace applications like Slack or Microsoft Teams, as well as email. This is so that an organisation can determine how employees are feeling towards the leadership, for instance, and use this information to find ways to boost morale or build trust in areas where it may be lacking.

The Enron effect

A now infamous scandal of the early noughties provides a useful case study for demonstrating the power of text mining. Almost a decade after the bankruptcy of energy firm Enron, a text-mining firm, KeenCorp, has managed to sift through troves of emails dating back to the days of the scandal.

The emails in question held correspondence between 150 of the company’s executives, essentially chronicling the downfall of the company. KeepCorp was able to make sense of the vast trove by passing it through an algorithm tailored to track company morale.

By tracking changes in the tone of the messages, KeepCorp’s algorithm was able to pinpoint the exact date when communications started to turn sour; 28 June 1999. This also turned out to be the date that the company’s board had discussed ‘LJM’, a proposal to hide the company’s struggling finances. This is considered to be one of the key moments of Enron’s downfall.

This is just one example of how text mining is able to make sense of enormous volumes of data that may otherwise obfuscate important information.