Enterprises across the UK are contending with “critical blind spots” over what workers are sharing with AI applications, according to new research.

A survey from SailPoint found more than two-thirds (67%) of organizations can’t account for the information staff are sharing with AI platforms and large language models (LLMs).

Worse still, the study noted that 35% of respondents admitted to sharing data through external tools, rather than approved internal applications, which is creating an array of risks for enterprises.

The rise of ‘shadow AI’ has become a recurring pain point for organizations over the last two years. Workers using unauthorized applications risk exposing sensitive company data, research shows – and there’s no sign of the trend slowing down.

Research from Gartner in November 2025 predicts that 40% of enterprises will suffer a data breach due to shadow AI by 2030.

SailPoint noted that the growing shadow AI trend comes in spite of the fact many enterprises are investing heavily in data management and AI capabilities for staff.

More than four-in-five respondents (82%) said they have invested in additional staff and skills training to help workers better manage AI applications, while 41% have brought on dedicated AI and analytics personnel.

Notably, nearly half (45%) of IT leaders said they still lack visibility on where information is being shared, and how.

Agentic AI poses new governance challenges

Mark McClain, CEO and Founder at SailPoint, said the findings show AI can often represent a catch-22 for organizations. While these tools are helping staff, they’re now creating additional risk surfaces for security teams.

“AI tools can enhance productivity, but they also create serious risk when they operate outside an organization’s visibility and governance,” he said.

“When sensitive information is entered into unapproved models, it can be exposed, mishandled, or even amplified through errors and hallucinations.”

McClain warned that with the rise of agentic AI, poor data management practices could be further amplified and put businesses at greater risk.

SailPoint noted that the need for greater visibility and oversight is now a priority for many enterprises on account of growing risks. In a previous study from SailPoint, four-in-five organizations (80%) revealed that AI agents had performed “unintended actions” such as accessing or sharing inappropriate data.

UK businesses are adding as many as 10,000 agents and machine identities each month, the company noted, meaning security teams could quickly become overwhelmed.

"As use of AI systems becomes more widespread, the situation is only going to get more out of control if organizations fail to put the right guardrails in place – compounded by other tools flying under the radar,” McClain commented.

“Organizations need to stop workarounds and regain control. That takes a combination of skills and awareness, but it also fundamentally boils down to a challenge around identity”

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Relational database management provider MariaDB has struck a definitive agreement to acquire in-memory computing specialist GridGain.

Founded in 2007, GridGain provides an in-memory computing platform designed to help organizations process large volumes of data in real-time. The company is also the creator of the Apache Ignite open source software.

The acquisition will see the firm’s capabilities integrated with MariaDB’s AI-ready relational database platform to deliver high-performance data infrastructure capable of supporting emerging AI workloads.

The aim is to address increasing performance demands and close the AI latency gap as businesses adopt more advanced systems that require quick access to large datasets.

In an announcement, MariaDB said the combined platform will deliver sub-millisecond data infrastructure in response to the “unprecedented demands” that agentic workloads have placed on dated enterprise architecture.

“By uniting our platform with GridGain’s in-memory data grid, we are entering a new weight class,” said MariaDB CEO Rohit de Souza. “This enables us to provide a high-performance, scalable, open alternative to the rigid lock-in of Oracle and the fragmented complexity of hyperscalers.”

Addressing the AI latency gap

GridGain’s in-memory computing technology is used to accelerate data processing for organizations running large-scale, data-intensive applications.

The platform provides security controls, high availability, distributed capability, and management features designed to drive performance and scalability.

Post-acquisition, the planned integration will combine the ACID-compliant transactional integrity of MariaDB’s own database platform with GridGain’s extreme-scale and in-memory processing capabilities to help eliminate the disk-drive tax on performance.

According to MariaDB, the integrated offering will support organizations operating across sectors such as financial services, telecommunications, logistics, and technology. Notable customers include American Express, Barclays, BNP Paribas, HPE, Red Hat, Verizon, and Virgin Media O2.

A unified approach to AI data

The MariaDB-GridGain integration aims to replace fragmented services with a unified, hybrid-cloud platform capable of tackling transactional, analytical, and AI use cases through a single, high-velocity system.

Commenting on the acquisition, Lalit Ahuja, CTO of GridGain, said enterprises can no longer afford the latency that arises from siloed data architectures.

“With MariaDB and GridGain, enterprise customers will get a unified platform that provides them the best of both worlds, performance and scale without having to give up on durability,” he explained.

“The combined technology stack will unlock one of the key enablers for agentic enterprises: high-performance and reliable data processing that powers the next generation of AI applications.”

The transaction is subject to customary closing conditions. Financial terms of the deal were not disclosed.

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Pure Storage has announced a new acquisition – and a new image – as the company pivots away from its traditional hardware focus and towards data management.

The acquisition of data intelligence and orchestration firm 1Touch will bolster the company’s data intelligence and orchestration features, which will be incorporated into its Enterprise Data Cloud (EDC) platforms.

“We are going beyond just pure data storage and adding context to the information and pulling it together into an enterprise data cloud,” CEO Charlie Giancarlo said in an announcement video.

“The announcement we made today to acquire 1Touch is a major advance toward that goal.”

As part of the move, Pure Storage will also rebrand to ‘Everpure’ in a move Giancarlo said better “reflects the company we have become”.

“The name Everpure represents the next step as we continue to not only redefine storage, but now redefine data management at scale,” he said.

The rebrand marks the culmination of a sharp pivot by the company over the last two years away from “pure” storage offerings toward data management capabilities for customers.

As ITPro reported at Pure Accelerate 2025, the launch of the firm’s Enterprise Data Cloud (EDC) signaled a heavier focus in this domain.

With EDC, the company now offers enterprises an all-encompassing environment which incorporates both hardware and software.

In the video announcement detailing the rebrand, CTO and founder John Colgrove echoed Giancarlo’s comments on the company’s new focus, noting that the “brand expansion” will better serve customers.

“We started the company and we built a fantastic data storage platform, but now as we expand beyond data storage into data management, understanding the data, helping people use their data better, it just makes sense to expand the brand,” he said.

Everpure targets deeper data insights

A key factor behind the EDC launch last year was the problem of data silos, the company said – an issue that has only been exacerbated by the arrival of generative AI.

“The key thing for AI is being able to make better use of one’s data,” he said. “But actually, the data that companies have is highly fragmented in their operational silos, and that data doesn’t really have the context necessary to be used for AI.”

Shawn Hansen, VP and GM at what is now Everpure’s Core Platform Business Unit, told ITPro last year that the company’s motivation for launching EDC came as a result of surging customer demands for flexible storage solutions and more intuitive management features.

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Magnetic tape storage might seem like a relic of a bygone era, but it’s still going strong in 2025 – and new upgrades mean it’s set to get even better.

The LTO Program, a joint initiative between IBM, Quantum Corp, and HPE, has unveiled a new generation of LTO Ultrium data cartridges offering enterprises up to 40 TB of native capacity - marking a significant improvement on previous generations.

The launch of the new range comes in direct response to surging AI-related data storage demands, with the capacity boost underpinned by “Aramid”, a new base film material which offers longer tape lengths.

“Aramid permits the manufacture of significantly thinner and smoother media, enabling longer tape lengths in a standard LTO Ultrium cartridge form factor,” the organization noted in a statement.

“This material innovation provides an extra 10 TB of native capacity than the currently available 30 TB LTO-10 cartridge, which is manufactured using different materials.”

Stephen Bacon, VP for data protection solutions product management at HPE, said the new cartridges are aimed at enterprises spanning an array of industries dealing with high data volumes, from manufacturing to financial services.

“AI has turned archives into strategic assets,” Bacon commented.

“The new 40 TB LTO-10 cartridge will help enterprise-class organizations – across healthcare, financial services, media, research, manufacturing, the public sector and beyond – consolidate petabytes efficiently, strengthen cyber resiliency with true offline air-gapping, and keep long-term retention affordable and sustainable.”

The magnetic tape renaissance

Magnetic tape storage has been going through something of a renaissance in recent years, and the advent of generative AI in late 2022 has played a key factor in this revival.

Indeed, figures published by the LTO Program in early 2024 showed a whopping 152.9 exabytes of total (compressed) tape capacity was shipped in 2023. That record was broken in July this year, with 176.5 exabytes shipped.

This marked the fourth consecutive year of growth for tape storage, underlining its continued popularity.

Tape storage has a number of distinct advantages, including low cost, durability, and easy portability. According to previous analysis from the LTO Program, companies using tape recorded an 86% lower total cost of ownership (TCO) compared to disk storage.

TCO compared to cloud storage was also 66% lower across a 10 year period, figures showed.

Notably, the use of tape for unstructured data storage also adds to the appeal, with this now vital in the training process for large language models (LLMs).

Tape is only going to get better

Long-term, tape storage is only going to improve, at least if the LTO Program’s roadmap is to be believed.

Through generations 11 through to 14, enterprises can expect to see significant capacity gains, eventually peaking with a 913 TB cartridge.

“The new capacity points will prioritize reliability and compelling value in terms of cost per terabyte, and ensure everyday LTO Ultrium tape solutions will remain a practical and affordable storage choice for every type of business or workload,” the LTO Program noted.

“Meanwhile, the new maximum capacity of 913 TB for LTO-14 will reduce the time needed to store and recover data, while preserving exabyte-scale growth paths for tape libraries.”

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Many firms have no formal data strategy despite increasing AI usage, according to a new study from Carruthers and Jackson.

More than a quarter (26%) lack a data strategy, the study found, while 39% reported little to no data governance throughout their business.

These same firms are still pushing on AI and ramping up their adoption efforts, though. Just 7% of businesses now go without AI, falling from 26% of businesses a year ago, while 53% reported an increase in the use of AI tools.

There’s also a lack of data literacy among staff, with 57% reporting a deficiency in this understanding among employees.

Similarly, while 44% have seen an increase in conversations around ethical AI, only 13% have turned these conversations into structured policies around AI ethics.

The report revealed some positives, however, with 37% claiming their business adopts multiple governance frameworks around AI. This figure is up from 31% in 2023.

“An AI Paradox has been created, as the use of AI tools in organizations has surged in the last year, yet employees lack the data literacy to use them effectively, as their fundamental understanding of data remains largely unchanged from last year,” Caroline Carruthers, CEO of Carruthers and Jackson, said.

Richard Bovey, data chief at AND Digital, said that there is a worrying knowledge gap around the risks of rushed implementation and that businesses need solid data governance structures to cover technology development.

“That’s especially true when it comes to AI, not only facilitating greater accuracy and reliability within AI outputs but helping to mitigate potential privacy and security concerns,” Bovey said.

“Weaving data governance principles across the development and integration process, supported by data skills, will greatly increase the likelihood of success for AI systems, providing a platform for them to be a business enabler rather than a costly mistake,” he added.

Good AI needs good data

It’s becoming increasingly clear to firms that data is of central importance to AI adoption projects, with studies pointing to the importance of data quality.

In a recent report from Ataccama, 68% of chief data officers claimed that data quality was their top challenge, while 40% said they struggle to maintain consistent data quality. This directly hinders outcomes, the report found.

“At the heart of every successful AI deployment is a foundation of high-quality, well-managed, and readily accessible data, so it’s concerning to see businesses ramping up AI usage without the basics in place,” Stuart Harvey, CEO of Datactics, told ITPro.

“The outputs of AI models are only as good as the data they are trained on and input, so disregarding a robust data strategy is only setting up for failure,” Harvey added.

Data storage may start to cause problems, as well. Research from Hitachi Vantara at the start of last year found that data storage capacity requirements were set to surge by 150% over the next few years.

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Only a third of businesses are making meaningful progress in AI adoption, and chief data officers (CDOs) are pinning the blame on poor data quality.

More than two-thirds (68%) of CDOs said data quality was their top challenge, according to the Ataccama Data Trust Report 2025. Meanwhile, four-in-ten struggle to maintain consistent data quality, directly hindering AI outcomes.

The report noted that trust is a critical factor when leveraging data in daily operations. Without it, organizations face inefficiencies, poor decision-making, and the risk of compliance failures, ultimately limiting their ability to achieve business objectives.

However, the report found most organizations still struggle with siloed systems.

"Untrusted data erodes every decision it informs. Without real insights into data quality, businesses risk cascading failures, from unreliable AI outputs to stalled growth," said Krishna Cheriath, chief digital Officer at Thermo Fisher Scientific.

"Trust must permeate every layer — data, models, and decisions."

Bad data leads to bad insights, the report noted, affecting decision-making, slowing down operations, and wasting valuable resources. Similarly, it jeopardizes compliance, leaving organizations vulnerable to regulatory and financial risks, and diminishes ROI.

Knowledge gaps are hampering digital progress

Knowledge gaps around data trust and governance are slowing progress, the report found, with a lack of unified standards leading to inconsistency. Without guidelines for data formats, definition, and validation, CDOs find it hard to establish a centralized system of control.

A third of organizations experience processing delays because there are too many barriers that stand in the way of integration.

"Fragmented systems bleed efficiency and inflate costs," said Andrew Foster, chief data officer at M&T Bank.

The report also found legacy systems are still a major barrier to innovation, with CDOs finding that outdated systems are ill-equipped to handle increasing data volumes.

Many systems are designed to provide period data updates, for example, rather than continuous, real-time streams. It’s this area in particular that’s causing serious trouble for CDOs ramping up AI adoption, with only a third of enterprises reporting meaningful progress on this front.

The report called for new national standards for data quality in the UK, and suggested that the proposed National Data Library - a core goal within the UK’s AI Action Plan - could play a key role in bolstering national data governance benchmarks and best practices.

These standards would ensure clear compliance guidelines while supporting the UK’s pro-innovation regulatory goals.

"The report makes one thing clear: enterprise AI initiatives rely on a foundation of trusted data," said Jay Limburn, chief product officer at Ataccama.

"Without addressing systemic data quality challenges, organisations risk stalling progress. The UK’s approach to AI regulation shows how aligning data trust principles with national standards and infrastructure modernization can deliver tangible results."

Amazon Web Services (AWS) customers will soon be able to book time slots at physical locations to connect their storage devices and upload data to the cloud.

Data can be uploaded to any AWS endpoint, including Amazon S3, Amazon Elastic File System (Amazon EFS), or others, using a high throughput connection of up to up to 400Gbps.

Each AWS Data Transfer Terminal will house a patch panel, fiber optic cable and a PC for monitoring data transfer jobs, the hyperscaler revealed. Terminals will be charged by the hour, with no per GB charge for the data transfer if the data remains in the same continent.

The first two Data Transfer Terminals are already up and running in Los Angeles and New York, with plans to launch more globally.

So far, the company is only listing charges for US-to-US transfers - $300 per hour - and US-to-EU at $500.

"On your reserved date and time, visit the location and confirm access with the building reception. You’re escorted by building staff to the floor and your reserved room of the Data Transfer Terminal location," said Channy Yun, principal developer advocate for AWS Cloud.

"Don’t be surprised if there are no AWS signs in the building or room. This is for security reasons to keep your work location as secret as possible."

The company said the terminals will significantly cut the time it takes to upload large amounts of data, meaning ingested data can be processed within minutes.

Customers can then analyze large datasets using Amazon Athena, train and run machine learning models with ingested data using SageMaker, or build scalable applications using Amazon EC2.

"After the data is uploaded to AWS, you can use the extensive suite of AWS services to generate value from your data and accelerate innovation," Yun commented.

"You can also bring your AWS Snowball devices to the location for upload and retain the device for continued use and not rely on traditional shipping methods."

Suggested use cases include video production data for processing in the media and entertainment industry, training data for Advanced Driver Assistance Systems (ADAS) in the automotive industry, or migrating legacy data in the financial services industry.

The hyperscaler also noted the service could help support uploads of equipment sensor data in the industrial and agricultural sectors.

"You can upload large datasets from fleets of vehicles operating and collecting data in metro areas for training machine learning models, digital audio and video files from content creators for media processing workloads, and mapping or imagery data from local government organizations for geographic analysis," said Yun.

It’s been more than a decade since the UK government abandoned plans to create a new NHS IT system, costing taxpayers billions of pounds. The scheme had been designed to deliver electronic records, digital scanning, and integrated IT systems across hospitals and community care.

For many in both the public and private sectors, that contracting saga lives long in the memory and its failure has now returned front of mind with government plans to create the new NHS Federated Data Platform (FDP).

What is the Federated Data Platform (FDP)?

The government hopes the FDP will allow NHS organizations to gather operational data from across the huge organization’s disparate systems and consolidate it in one place.

Writing on gov.uk last year, National Data Guardian Dr Nicola Byrne explained how the “value of our data will only be realized if it can be organized in such a way that the NHS is able to use it well to improve treatments, services and ultimately our health and care”.

“The programme’s work to support better health and care for all through the better use of our data is too important an ambition to fail,” she added.

However, with the platform value set at £480 million and multiple bidders expected, this new scheme doesn’t come without controversy. Fears over privacy, and concerns about data security, are all driving debate. 

Iain O’Neil, a former NHS director, and now managing partner of health and social care at TPXimpact, believes we will only “truly unlock the potential of NHS data” once the fundamentals are right; this includes data standards, interoperability, and getting data where and when it’s needed most.

He suggests funnelling all NHS patient data into one private firm could be a risk, explaining: “The FDP will work best if it supports an ecosystem of suppliers tackling the difficult challenges the health and care system faces.” 

And looking ahead five to ten years, he adds: “Clinical decisions based on data gathered from the 67 million people plugged into the NHS Service should be ubiquitous, enabling learning and better decision making.”

A revolution for managing and storing data

A major challenge for the FDP will be to gain frontline buy-in from receptionists, clinicians, nurses, and all working with data within the NHS. Unless the culture inside the organization fully adopts it, it won’t achieve its aims, experts argue.

But Alex Case, who previously worked in Downing Street overseeing cross-Whitehall Brexit delivery, believes the platform could “revolutionize the way we store, manage, and utilize healthcare data in the UK” – although he agrees this is only one part of the story. 

“There needs to be a recognition of the need to coordinate and orchestrate a 'patient journey' across the different components of an integrated care system, because that’s the point of taking a consolidated view of the data,” Case, who is now public sector industry principal at Pegasystems, explains.

Many argue implementing cutting-edge technology and infrastructure in partnership with the private sector could allow for a more coordinated healthcare system. Case, however, adds: “It’s crucial the NHS ensures data is collected and shared in a responsible and transparent manner, with robust safeguards in place to protect patient confidentiality. Additionally, there is a need for clear guidelines around data ownership and access to prevent any potential misuse or abuse.”

He argues the platform should be feature-rich, rather than simply focused on data integration, if patients are to be placed on “the right pathway to get the right treatment, at the right time”, while also accounting for NHS workloads, backlogs, and prioritization.

“The government and their technology partners have the responsibility to work together to ensure we deliver the highest standards of ethics and governance so that we can address the healthcare needs across the nation better and more reliably than before,” Case warns.

Experts agree the FDP should lead to better decision-making, given it will break down silos, including CEO of Apheris, Robin Röhm. “By providing access to distributed data sources, stored in different sources and locations, the data analytics platform can then be utilized for a multitude of operational purposes from care coordination to improving medicine supply chains.

“Data is most valuable when it is extensive and detailed. As the current handling of data within the NHS involves sensitive data being stored on many separate systems, this often leads to poor access and visibility of data by stakeholders.

“Federated data ecosystems are the most pressing response to the problem of working across organizational and geographical boundaries as personal data never leaves its secure environment.”

Avoiding the threat of vendor lock-in

The need to keep information in the FDP from being personally identifiable is a major issue for campaigners and patient-led organisations. The security risks are real; for example, according to Palo Alto Networks’ Unit 42 team, healthcare was the third most-targeted sector in the UK, with 9% of all attacks targeting healthcare organisations.

Amanda Brock, CEO at not-for-profit OpenUK, suggests some form of NHS systems standardisation could help manage every aspect of the user journey from appointment booking to service delivery, while updating patient records along the way to be more efficient. But she warns its success depends on its implementation; the NHS must own the platform and it’s built on open source software in a “collaborative and transparent way”. 

She adds public sector platforms frequently “pay lip service to the legal definition of open source using an OSI-approved licence and sharing the source”, but this is “not enough to avoid lock-in”, she states.

“The scale of this project means there are few people that have the skills to lead it successfully,” Brock further explains, “but the risk with appointing a single vendor is of course lock-in. The NHS has spent years fighting against this. 

“We need to find a balance between the current status quo of myriad disjointed platforms and apps, and one single vendor that owns everything in perpetuity and profits off that patient data at our expense.” 

Risking privacy is a price worth paying

The FDP will lead to better patient care, as it makes a person’s complete medical history far more accessible, adds Waseem Ali, formerly CDO at Lloyd’s of London and current CEO of data and analytics consultants Rockborne. 

This is because of its “treatment-first, paperwork-later” approach. Ali’s years of experience with healthcare data, however, shows the use of integrated records has always been an issue, especially amid privacy concerns.

“It’s understandable for people to be hesitant about their data being shared,” he concedes. “However, most people are already sharing more information with Amazon or Facebook, sometimes without even realizing it. 

“So, if you are happy for Amazon to know your consumer preferences and shopping habits, then why aren’t you happy to share your healthcare information with the NHS so that you can receive the optimum level of care?”

Ali talks of the potential benefits that would exist if “healthcare professionals knew everything about a patient”. “This information could be harnessed to pre-empt the types of services they may need, which would be a gold mine for preventative care,” he adds. 

“Yes, there will always be the argument about data privacy, but the number of lives that could be improved, or even saved, is hard to out-argue.”

Liverpool Football Club (Liverpool FC) is one of the world’s most renowned soccer institutions, with a massive global fan base and a rich history of success. As a prominent brand in the sports industry, the club has recognized the importance of digital transformation and embarked on a journey to improve its operations and fan experiences.

One of the key challenges Liverpool FC faced was managing its large digital media workflows and handling vast volumes of content. The club generates and distributes a substantial amount of digital content across various platforms. This includes live match broadcasts, highlights, interviews, behind-the-scenes footage, and promotional materials. The sheer magnitude of Liverpool FC’s digital media workflows posed significant challenges in terms of content creation, distribution, storage, and accessibility.

Understanding the need for change

Traditional on-premise infrastructure Liverpool FC has traditionally relied on proved to be inadequate for efficiently managing the club’s digital media workflows, says Drew Crisp, its senior vice president of digital.

“Initially, we would have done this anyway because all of our media archives are on-premise and were on traditional 24 spinning disks, and actually accessible [only] when you're in the office,” he tells ITPro. It was always the plan to get data into the cloud, Crisp adds, as it would be “faster, quicker, easier to access”. 

Liverpool FC faced numerous challenges with its infrastructure, including slow data access, limited remote access capabilities, performance bottlenecks, and the physical limitations of storing and processing large volumes of content. He adds COVID-19 accelerated plans. “It brought forward a bunch of stuff because hybrid working doesn't lend itself particularly well to accessing archive when it's on a bunch of hardware that's in the office.”

Recognizing the importance of data as a critical asset, Liverpool FC crafted a robust data management strategy to support its operations. Crisp stresses how important this was, adding: "We needed a capability that is remotely accessible, really quick and really easy to use, but also which could enable us to do future things – not just with archived content, but post-production content we could share with partners."

This would also improve the decision-making processes. By harnessing the power of data analytics, Liverpool FC could gain valuable insights into fan behavior, preferences, and engagement patterns. These insights would guide its marketing efforts, fan engagement initiatives, and overall business strategies. A data-driven approach would help Liverpool FC understand its fans better, tailor its content offerings and deliver personalized experiences to its global fan base.

Scoping out a cloud partner

To overcome these challenges and unlock new opportunities for growth, efficiency, and fan engagement, Liverpool FC embraced the cloud by partnering with Wasabi as its storage provider. The club revolutionized its digital workflows through this agreement and maximized the potential of its vast media library.

“I mean, the biggest advantage, as we see with wasabi cloud is we don't have to pay for egress. From a commercial model perspective, as well as speed and efficiency, actually, it does an awful lot for us. Because you don't pay commercially, you can ingest really quickly and then you can get into operation,” says Crisp.

Neither the club nor Wasabi encountered major challenges, and the migration's success means the club is exploring how else it can use the cloud in the future. Ultimately, Liverpool FC’s decision to move to the cloud has provided a solid foundation for future improvements to its end-to-end content workflow.

Wasabi’s cloud storage has allowed Liverpool FC to store and access its media content with ease and speed, eliminating the performance issues and physical limitations of its previous on-premise infrastructure. It's also provided Liverpool FC with scalability and flexibility, allowing it to adjust its storage capacity according to changing needs and demands.

This has translated into measured improvements. Liverpool FC can now share and access data across various teams and departments within the club, which facilitates better collaboration and communication. It’s also streamlined workflows, reducing the time and resources required for content creation, distribution and management.

Crisp says the organization’s editors are “probably three times more efficient in its eight-hour day than they would have been previously waiting for all sorts of things to upload, download and edit on the fly”.

“From an efficiency and time point of view, that means that they can get through more content and create more content significantly faster,” he continues. “I'd say probably, we probably do 20-30% more content now than we did previously.”

Databricks has launched a raft of new features for its flagship Lakehouse data lake platform, including artificial intelligence (AI) and natural language improvements as well as data governance features.

With Lakehouse AI, customers can develop generative AI applications, including large language models (LLMs), within the platform itself, with tools spanning the breadth of the AI lifecycle. This includes data collection, model development, and monitoring.

“This gives you control over your intellectual property,” said Databricks CEO Ali Ghodsi during his keynote address at Databricks Data + AI Summit 2023. He added every company in the next five years “will be an AI and data company” and would need the tools to create their own LLMs to be competitive, rather than rely on third-party services.

What is LakehouseIQ?

LakehouseIQ is the firm’s ‘knowledge engine’ that’s designed to make natural language interfaces, like chat bots, more accurate and relevant to the needs of a particular organization.

Sitting as a fabric between data and a front-end interface, the tool uses generative AI to understand a business’ unique culture, jargon, and data usage patterns, among other factors.

It ingests a vast quantity of internal material, including organizational charts, notebooks, and more, in order to understand how best to answer questions users ask via any chat interface.

It’s designed to be specific to each business, so natural language interactions are far more accurate and context-sensitive than classic chat bots. While not a chat bot or virtual assistant itself, it’s designed to improve the reliability and performance of these tools.

Databricks has made Lakehouse IQ available as an API, and the firm plans to integrate this into open source libraries.

New AI features in Lakehouse

Vector Search gives developers the capacity to improve accuracy of generative AI responses. The features creates vector embeddings based on files found in Unity Catalog — the central hub that gives customers access control, auditing, lineage and data discovery capabilities across their workspaces.

It creates vector embeddings from Unity Catalog files, and automatically updates them through integrations with Databricks Model Serving. Developers can also add query filters to provide better outcomes.

Improvements to AutoML also adds low-code functionality to finetuning LLMs. Any tweaks customers make to their LLMs will be owned by the enterprise, with data kept in-house and not shared with any third parties. This model can also be sahred within an organization with Model Serving, Unity Catalog and MLflow integrations.

Finally, Databricks has launched several open source models through its marketplace including MosaicML’s MPT-7B and Hugging Face’s Falcon-7B, as well as Stable Diffusion.

On the LLMOps front, MLflow AI Gateway lets customers centrally manage credentials for software as a service (SaaS) models or APIs, and provide access-controlled querying. This also allows for prediction caching to track repeat prompts and rate limiting to reduce costs.

MLflow Prompt Tools, meanwhile, is a no-code feature that allows users to compare different outputs from various models based on prompts that are automatically tracked within MLflow.

New governance features in Lakehouse

Also new in Lakehouse is LakeHouse Federation capabilities, which has broken down silos between data systems that previously existed on the platform. As a result, businesses are now able to discover, query and govern data across all their systems without the need to copy or move data. 

Query federation comprises catalog and querying functionality to consolidate and map out data asses from different platforms beyond the confines of Databricks, including MySQL, PostgreSQL, Redshift, Snowflake, Azure AQL Database, Azure Synapse, BigQuery, and others. Users can secure, audit and access data from one interface rather than having to move the data between different platforms.

Additional governance tools in Unity Catalog also lets customers apply access policies on any data asset that’s registered, including tables, rows, columns and tags. This comes ahead of future plans to define data access policies and push them out to other data warehouses.

The Lakehouse Federation's capabilities also include giving users a common approach to discovering and exploring both structured and unstructured data with a single query. Domain-owned data sources for analytics and AI use cases are also rapidly exposed, offering faster access to data. Finally, the changes make it possible for users to apply a single permission model for the data estate.

Businesses must be more aware of the data requirements for artificial intelligence (AI), and use this period of focus on AI risks to prepare for the quantum computing ‘threat’. 

That’s according to John Roese, global chief technology officer (CTO) at Dell, who shines a light on the main challenges businesses face when adopting AI models, and the lessons they can learn from the deployment of generative AI.

Roese acknowledges the computing bottleneck associated with training AI models, but denies this is the main hurdle holding businesses back when deploying the technology.

“The bigger issue for an enterprise use of a large language model (LLM) is in order to train it, you have to have access to the right data and provide the data to the training infrastructure,” he tells ITPro at Dell Technologies World 2023. “Most customers have not done enough work on their data management.”

Stripping out bias

As an example of good data management, Roese cites Dell’s work over the past four years to eliminate non-inclusive language from its content library and internal code environment. These include labels like ‘whitelist’ and ‘blacklist’.

If an LLM was trained on the firm’s content repository, Roese explains, it would be unlikely to not incorporate the biases of these words. Firms that don’t curate data before using it to train AI models intended for products such as chatbots could inadvertently create services that reflect an inherent racism or misogyny, as demonstrated by Microsoft’s Tay scandal.

“If you want to create a chatbot or an LLM that reflects your dataset, it will reflect your dataset – the good, the bad, and the ugly – and it’s important to know that you've created a dataset that is reflecting your values.”

Roese also notes LLMs work best with unstructured data, as neural networks seek to create connections of their own rather than relying on arbitrary structures. As a result, he says, businesses need to ensure that their data is “sitting in the right place” to be used for training to avoid having to spend lots of time restructuring data down the line.

Are the majority of firms aware of these requirements at present? “No, they're not,” Roese admits. “And that's very disturbing to be perfectly honest.”

AI is a dress rehearsal for quantum

Generative AI has been hailed as one of the most significant technological developments of the century. At Dell Technologies World 2023, CEO Michael Dell compared it to the invention of the internet or PC.

In recent months, many have highlighted the risks of generative AI, with analysts calling it an existential threat, and pioneers calling for a temporary development pause. 

But Roese recommends businesses use the big upheaval generative AI has triggered as a “learning experience” to better position themselves for future technologies that will disrupt the sector to a far greater extent.

“Everybody's talking about generative AI as if it is the destination – but it isn’t,” Roese stresses, arguing people are so “shell-shocked” by the headline-grabbing technology that they have failed to give proper thought to what comes next. “The answer to that is actually quite simple in my mind, it's quantum,” he continues.

The primary use case for quantum, Roese explains, is clear: quantum machine learning. He notes while generative AI is branded as “disruptive” and sparking fear in some, it’s just the logical progression of existing technologies.

“Imagine if it now ran at five orders of magnitude higher performance. And that, inevitably, is coming.”

Maintaining cyber security in the face of developments in quantum computing is something that will become increasingly important as we approach the 2030s.

Experts suggest it’s a matter of if, not when, standards such as AES encryption break down, for example. Once encryption is cracked, the security of data will be wholly undermined.

The private sector isn’t alone in the race to quantum, as many nation-states have already announced huge investments aimed at proactive quantum development and adoption.

In the Spring Statement, UK Chancellor of the Exchequer Jeremy Hunt announced a £900 million ($1.1 billion) fund for quantum computing research, as part of a wider £2.5 billion ($3.1 billion) investment program for UK quantum.

Companies will have to navigate this disruption in the near future, Roese warns, and would do well to use the choppy waters of generative AI as a dress rehearsal for weathering the coming storm of quantum computing.

Multi-cloud data management specialist Veritas has revamped its Veritas Partner Force program to include improved incentives and rewards for cloud-based deals.

Launched to channel partners last month for the fiscal year 2024 (FY24), the refresh also features a simplified transaction process, as well as brand-new training and accreditation programs.

The company said the changes have been designed to help accelerate partners’ transition to the cloud and drive growth with secure cloud data management solutions. 

According to Veritas’ own research, 43% of UK businesses currently do not have complete visibility into data stored in cloud environments. 

“As more businesses in the UK embrace the cloud, we recognize the need to support our partners in delivering a seamless transition for our customers,” said Oliver Norman, VP of channels and alliances at Veritas.

“To this end, we are simplifying our channel platform processes, enabling our partners to focus on their core strengths of providing exceptional customer service. That’s why the FY24 program will be a game-changer for us.”

Veritas said this latest iteration of its program will support the company in achieving its key primary channel goals - including delivering growth on its secure cloud data management platform Veritas Alta. 

The firm will assist and incentivize partners to take advantage of the growing cloud market, providing new training, accreditation, and rewards. 

Partners will also now have a single comprehensive target to achieve across new business and renewals, as well as software, services, and appliances, to help meet tiering requirements.

Veritas will work with partners on demand generation activities to attract net new customers, with improved rewards for bringing new customers on board, as well as reward those that help existing customers apply the platform to new use cases.

It said there are also plans to launch new initiatives across FY24 as it looks to further improve the resources available to two-tier channel and managed service providers.

Bob Olwig, executive vice president of global partner alliances at World Wide Technology, praised Veritas’ innovation and reliability in driving the pair’s strategic relationship. 

“This year’s Veritas Partner Force program makes it easier for us to learn about the exciting new products that Veritas is delivering, easier for us to sell them, and easier for us to earn rewards along the way,” he said.

“Our customers are facing new and more complicated cloud data management challenges, and Veritas gives us the solutions we need to answer those challenges with a channel wrapper that provides everything we need to be successful.”

Global businesses running cloud, data center, and infrastructure operations have been urged to spend time reshaping their capabilities amid challenging economic conditions.

Pressure on infrastructure and operations (I&O) teams is expected to grow over the next year as organizations contend with rising costs, acute macroeconomic strain, and a rapidly evolving business landscape, according to experts at Gartner. 

Paul Delory, VP analyst at Gartner, said that 2023 will be a year for organizations to “refocus, retool, and rethink” their infrastructure capabilities and technology stack as many seek to optimize operations and work around tightening budgets. 

“In the current economic climate, the biggest problem companies face in 2023 may not be IT infrastructure,” he said. “I&O teams, however, will be impacted by economic and geopolitical forces and will have a vital role to play in ameliorating their effects.”

“This won’t be a year to realize grand ambitions, but it marks a moment to refocus, retool and rethink your infrastructure. In every crisis lies opportunity, and in this case, the chance to make positive changes that may be long overdue.”

Gartner’s claims were revealed at its IT Infrastructure, Operations & Cloud Strategies Conference, hosted in Sydney. 

Analysts highlighted four key areas in which business operations are being transformed amid a period of economic uncertainty and re-evaluation for firms. 

1. Optimizing and ‘refactoring’ cloud infrastructure

Despite a rapid uptake of public cloud in recent years, Gartner warned that “many deployments are ad hoc and poorly implemented", which is having an adverse effect on organizations’ ability to maximize their cloud estate. 

Across the year, the consultancy said I&O teams will “have an opportunity to revisit assembled or poorly architected cloud infrastructure” as firms scramble to get the most out of their IT estate. 

“The focus of refactoring cloud infrastructure should be on optimizing costs by eliminating redundant, overbuilt or unused cloud infrastructure; building business resilience rather than service-level redundancy; using cloud infrastructure as a way to mitigate supply chain disruptions; and modernizing infrastructure,” Gartner said. 

This sharpened focus on optimization will deliver cost savings and efficiency improvements long-term if done correctly, Gartner added. Research from the firm found that 65% of application workloads will be “optimal or ready” for cloud delivery by 2027, marking a significant increase from 45% in 2022. 

Underused cloud infrastructure is an issue that’s emerged in organizations in recent years due to a surge in pandemic-related cloud adoption.

However, with rising cloud costs impacting businesses globally in the last 15 months, this issue has come to the fore for many. 

Spiraling costs have prompted organizations to ‘reassess’ their relationship with the cloud and cut back on spending.  

2. New application architectures driving infrastructure changes

I&O teams are under intense pressure to meet evolving demands for new types of infrastructure, Gartner said. This includes an increased focus on edge infrastructure for “data-intensive” applications, serverless edge architectures, and 5G mobile services. 

By 2026, Gartner predicts that 15% of on-premises production workloads will run in containers, up from less than 5% in 2022. 

This highlights the need for more flexible infrastructure, however, the consultancy warned that teams “must evaluate options with” care and consider their ability to manage and integrate new workloads while working in the face of time constraints.

“Don’t revert to traditional methods or solutions just because they’ve worked well in the past,” said Delory. “Challenging periods are times to innovate and find new solutions to meet business demands.”

Containers have increasingly become a go-to way for developers to build, test, and deploy applications across multiple environments, including on-prem data centers and in the cloud. 

Research from NetApp, for example, shows that containers require less system resources than traditional or hardware-based virtual machine environments.  

Greater efficiency, enhanced application development, and increased portability are also among key benefits of containers highlighted by NetApp. 

3. Data center teams adopting cloud principles on-prem

According to Gartner, 35% of data center infrastructure will be managed from a cloud-based control plane by 2027, from less than 10% in 2022. 

This increase is being propelled by the fact that “data centers are shrinking and migration to platform-based colocation providers”, the firm noted. This, combined with new as-a-service models for physical infrastructure is providing organizations with “cloud-like service-centricity” to on-prem infrastructure. 

In the year ahead, Gartner said I&O professionals should focus on “building cloud-native infrastructure within the data center” to optimize and streamline operations. 

Gartner’s research also urged teams to focus heavily on migrating workloads from owned facilities to co-location facilities, or embrace as-a-service models for physical infrastructure. 

Migrating and integrating workloads poses challenges for businesses, however. 

With firms facing an increasing array of cloud-related options spanning public, private, and hybrid cloud, making the correct decision based on their individual circumstances, needs, and financial capabilities could make or break a successful migration. 

4. Skills growth a key priority for businesses

The pervasive issue of skills deficits will continue to plague businesses in the year ahead, meaning that attracting and retaining talent will be critical to ensuring success in infrastructure modernization projects. 

“Lack of skills remains the biggest barrier to infrastructure modernization initiatives, with many organizations finding they cannot hire outside talent to fill these skills gaps. IT organizations will not succeed unless they prioritize organic skills growth,” Gartner said. 

To tackle this growing issue, I&O leaders must make operations skills growth their “highest priority” in 2023. This includes encouraging I&O staff to “take on new roles”, expand skills through training programs, and encourage cross-functional training to ensure a broader range of applicable skills throughout teams. 

This heightened focus on cross-functional training could be key for organizations moving forward, with the consultancy’s own research predicting that 60% of data center infrastructure teams will have “relevant automation and cloud skills” by 2027. 

This marks a significant increase from just 30% in 2022, highlighting the growing appetite for firms to develop more multi-skilled teams. 

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.

Data has become a competitive advantage, helping businesses anticipate and react to change. But with data in multiple formats and locations, costs quickly add up and expertise becomes a limiting factor, forcing businesses to fall back on spreadsheets and disconnected databases.

The cloud has emerged as a critical tool for businesses of all sizes to more easily access and synthesise data to gain greater insight and make better decisions--predicting trends, improving operations, and identifying new customers and business opportunities.

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Attitudes towards data governance have shifted in the last 12 months from something that’s nice to have to a must-have, as businesses look to better measure and monetise their data.

Getting it right has never been more important, with disparate data estates growing and risks around regulatory enforcement, private litigation and company reputation becoming more prominent.

With this in mind, Giovanni Cervellati, research manager, European intelligent analytics and data strategies research at IDC Europe, says the majority of organisations are concerned about data loss, compliance breaches and lost opportunities. This has made data governance a priority as businesses look to boost data resilience, ensure continuous compliance and mitigate risks.

“Almost 70% of organisations view data privacy and security as key investment areas and 54% view data sovereignty, privacy and governance as factors to be addressed,” he notes.

Benefits of strong data governance

Good data governance helps organisations of all kinds to achieve their ideal business outcomes, ensure robust audit trails and improve decision-making. Saul Judah, VP analyst at Gartner, highlights a prime example.

“[One organisation] built business support by showing that its data and analytics transformation would enable the rapid calculation of crucial, cross-functional business KPIs,” says Judah. “The COVID-19 crisis showed the wisdom of this approach, and consequently, its data and analytics team was able to pull together crucial data to inform executive decision-making about the crisis in a short time.”

If an organisation isn’t implementing basic principles around data governance, then it’s hard to see how they can run an efficient business model and build and retain customer trust adds David Mason, information and fundraising compliance manager at the Salvation Army.

“If you’re not keeping accurate records, it is hard to see how you can effectively communicate with your customers,” he cautions, adding if you don’t tell people how you’re going to use their personal data, it shouldn’t be a surprise if they no longer want to hear from your organisation. As far as data protection goes, organisations should consider the priorities of the data subject first, and the business second.

“Most data governance is happening behind the scenes; we’ve got a strong framework in place for assessing and managing risk and recording processing activities,” he continues. “Our data protection officer (DPO) acts as the conduit between the business and the data protection regulator. Proof that our supporter-first approach is working can be highlighted by the fact that we receive very few complaints about our direct marketing activities – none about emails sent in 2021/22, and only 30-odd from over four million addressed mail packs in the same period.”

What’s in store for data governance in 2023?

In 2023, data governance strategies will be shaped around the growth of data volumes, cyber security threats, and the need to build digital trust.

Awareness around data governance is heightened

The pandemic accelerated a shift in attitudes, with data governance becoming a boardroom priority. The rise of hybrid working, for example, meant organisations needed to become more aware of data storage, data usage and data processing. This greater awareness is also essential to all businesses undergoing digital transformation projects.

Indeed, a digital or cloud transformation is all underpinned by data, says Waseem Ali, CEO of data recruitment agency Rockborne, and former head of data strategy at Lloyd’s of London. “Companies that don’t draw out the end-to-end flow of data across their systems and understand what’s happening to that data at different stages of its journey will struggle to make informed decisions,” he says.

More of the organisation is involved

According to Forrester’s 2022 data and analytics survey, 75% of organisations are expanding data literacy training, while 36% plan to have an executive in the role of head of data governance. With this in mind, “we predict that we will see more data governance discussions in organisations of all industries and sizes,” says Kim Herrington, a senior analyst at Forrester.

Gartner’s Judah reports seeing several major trends that support the move from data and analytics governance as a centralised, IT-led, asset-centric approach to a multi-style, business context-specific capability. These are adaptive governance, business outcome-focused governance, trust-based decision rights models, collaborative governance teams and platform-enabled governance.

“Allowed to materialise, these trends will enable data and analytics governance to become an effective change agent for transforming the organisation into a market-responsive composable enterprise,” Judah notes.

Keeping a watchful eye on legislation

A range of further legislative changes, meanwhile, are going to continue to add complexity to the governance landscape this year, says Will Richmond-Coggan, a data protection expert at law firm Freeths.

“These changes, together with wider-ranging enforcement activity and an ever-increasing public awareness of the rights individuals enjoy in connection with their data, will all continue to contribute to this taking a central position in the metrics by which a business’s success is judged,” he says.

Pitfalls to avoid in your data governance strategy

It’s important to remember there’s no “one size fits all” when it comes to data governance – an overly complex programme that’s a mismatch of risk and resource simply won’t work.

It’s also crucial to recognise that everyone in the organisation has a role to play and equip them accordingly. The key, though, is remembering this isn’t something that needs to be approached with suspicion or fear.

Good governance can lead to all sorts of improvements in terms of efficiency, better visibility of assets and processes, and increased confidence that when risks arise – either internally or externally – the business’s systems and processes are robust enough to withstand them says Richmond-Coggan.

“Approaching governance from that perspective will help to ensure that the work entailed is actually beneficial for the business and results in a governance regime which is living, supportive of the business’s wider strategic goals, and consequently more readily adopted as part of the organisation’s culture,” he concludes.

Research from the Enterprise Strategy Group (ESG) reveals that IT professionals struggle to identify the most valuable data available to them, so priority investments include the centralisation of data with increased security controls, as well as comprehensive analytics to identify complex attacks. As a solution, organisations are investing in SIEM infrastructure but admit they find it difficult to manage it effectively.

In this technical product review of IBM Security QRadar SIEM, ESG makes several observations, including QRadar's ability to prioritise events, lower costs, integrate with both IBM and 3rd party solutions, and more.

Download the full report for more details and how to overcome the most challenging attributes of SIEM for your business.

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Over the past decade, financial technology has revolutionised the way businesses and consumers conduct and manage financial transactions, and data visualisation has played a big role in that revolution.

This whitepaper, explores 12 financial charts that developers can use to visually represent and communicate their data story and how FusionCharts can help devs simplify their FinTech application development.

Download now to learn more.

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Cloud computing firm Appian has championed its newly-released Appian Data Fabric system, claiming the system's real-time read/write feature offers capabilities that aren't offered by any competing vendor.

In the keynote that opened its annual Appian Europe conference, the system, which launched as part of Appian 22.4 last week, was the central talking point. The solution combines the automation and low-code development for which Appian is known across a single virtual data model, allowing customers to access unified data and identify areas in which to implement systems such as robotic process automation (RPA).

Appian insisted that while rival data fabric systems are available, none can offer its ease of adoption. The firm said 45% of its customers have already leveraged Data Sync, a process for caching source data that is at the heart of the data fabric system, and stated that for all its benefits Appian Data Fabric is no step up from these existing systems.

The workloads, automations, and queries set up by customers already laid the groundwork for Appian Data Fabric, as metadata from all of this can be used to optimise data management within the platform.

For example, by analysing how a customer builds its processes, what it automates, and which queries that analysis will require, Appian’s data fabric can automatically repartition and re-index data within its virtual model to ensure it can be accessed with maximum efficiency.

“When other clients say ‘oh yeah, we have a data fabric,’ what they're talking about is probably much more like a data lake,” said Michael Beckley, CTO and a founder at Appian.

“They might be able to analyse data from different locations. But being able to write transactions to the fabric in real-time, and read from it, that’s what the Appian data service can do, that no one else can.”

In his keynote address, Beckley also stressed that the data fabric is an improvement to the system that customers already use rather than a new product, and comes with no new training requirements or added cost.

He also stated that the company sees Data Fabric as an alternative to rip and replace models, or any vendor lock-in, giving the example of a data fabric that connects Oracle, Microsoft, and Salesforce alongside the Appian database.

“The answer is not just Appian. The answer is using Appian to take advantage of the technology investments you already have. And with Appian's data fabric, we're confident you'll be able to do that.”

A data fabric is a data management architecture that integrates multiple data pipelines or cloud environments in an end-to-end data environment, allowing customers to access their data through an optimised access point that requires little to no code.

The firm claimed that Appian Data Fabric has doubled search speeds, requires customers to use 75% less code to build charts, and allows zero-code apps to be built up to ten times faster than previously possible.

Last year, Gartner named data fabric as a key technology trend for 2022, noting its potential for adding to existing infrastructure. Since then, a number of companies have offered data fabric systems, such as Google Cloud.

Down the line, Appian said its existing data system could also be used to measure parameters such as carbon impact across a number of silos.

Gartner recently published findings that marked sustainability as a key technology trend for 2023, and that businesses investing in it are doing so to tackle disruption, and reap its short and long-benefits.

Malcolm Ross, deputy CTO at Appian, told IT Pro that regulatory pressure increases in a recession, and that environmental, social, and corporate governance (ESG) will be core to this.

“ESG is definitely the next GDPR-level type of regulatory oversight that companies will have to report their carbon footprint. They will have to report how their governance modelling, their board, is accurately collecting the culture of that organisation or that country as well.”

Ross also stated that efficiency savings through efforts such as automating the back office are unlikely to provide meaningful results with sustainability in mind. He argues that only holistic oversight, allowing for proper identification of weaknesses through processes such as big data analytics, will be necessary.

“You're not going to become better at ESG and sustainability, by just doing automation what you need is visibility.”

Head of process mining Karina Buschsieweke told IT Pro that Appian’s data fabric is already capable of providing this visibility, and that growing regulatory pressures might lead to more specific focus on this process down the line.

“How process mining works is, you have attribute data, so you have a process and you can add as many attributes to that as you like, so can be location, product, etc.," said Buschsieweke

"But it could also be CO2 as a further data attribute. Now, of course, today the major challenge for all companies is where to get the CO2 impact data from, because that's also a whole different issue - how to standardise it, and make it comparable.”

“However, if you have the data already, you could do this with our solution today. And then probably, there could be features that might even make it easier for customers than this. I think at some point in the future, companies will be required to report on CO2 the same way as they have to report their euros.”

Backup, recovery and data management solutions provider Veeam has been selected as the data protection provider of the new Lenovo TruScale backup as a service (BaaS) platform.

Veeam becomes the first data protection solution added to TruScale and will provide Lenovo users with ‘pay as you go’ BaaS via Lenovo’s infrastructure as a service (IaaS) platform.

Announcing the move, the firm said the solution aims to modernise enterprises’ data protection strategy, help manage growing data volumes, tackle increasing performance and multi-workload demands, as well as lowering total cost of ownership (TCO) with a flexible cost model.

“As a leader of modern data protection, we’re proud to be a part of Lenovo TruScale to deliver expert-built and managed BaaS and disaster recovery as a service (DRaaS),” said John Jester, chief revenue officer at Veeam.

“This new Veeam and Lenovo solution will help enterprises reduce the complexity of modernising their data protection strategy from legacy solutions and ensure confidence in the protection of their data.

“They can focus on what matters most – their customers, innovation, and strategic initiatives to propel their business forward.”

The new collaboration builds on the companies’ existing relationship, which has already seen the pair offer intelligent data management solutions for Lenovo software-defined infrastructures since 2020.

This enterprise-level data protection now combines Lenovo ThinkSystem Servers and its DE and DM storage series with Veeam’s backup and replication functionality to maximise availability and simplicity for customers.

Optimised for daily IT requirements, the offering promises reliable recovery and reduced management time, digital resiliency for rapid recoveries, data sovereignty, as well as protection for the data centre, edge, and cloud.

General availability of Lenovo TruScale backup as a service with Veeam is expected to arrive in 2023.

“Lenovo TruScale delivers the devices, infrastructure, services and solutions, from pocket to cloud, that our customers need, with the simplicity and flexibility of a scalable consumption model,” said Dale Aultman, VP and GM, TruScale and managed services, solutions, and services group at Lenovo.

“Veeam is the first data protection partner being added to TruScale for data management portfolio, allowing customers to control their data while letting Lenovo manage the infrastructure. This partnership provides customers with robust and reliable data protection and data loss prevention, future-proofing their businesses as they digitalise.”

Is your data security team working with siloed security tools and processes? Is this standing in the way of enabling secure data usage and sharing for your organisation?

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Microsoft has been accused of leaving thousands of customer records open to the public on a misconfigured server, and only taking steps to secure it after receiving a warning from a security research firm.

Researchers at SOCRadar, a cyber security company, said they had detected sensitive data belonging to 65,000 entities in 111 countries on a misconfigured Azure Blob Storage server, it revealed on Thursday.

First discovered on 24 September, the firm found 2.4 terabytes of data publicly available, containing sensitive information belonging to Microsoft and its customers, including data on files dated between 2017 and August 2022. Researchers have said the data contained over 335,000 emails, 133,000 projects, and 548,000 exposed users.

The exposed files also included Proof-of-Execution (PoE) and Statement of Work (SoW) documents, user information, product orders/offers, project details, PII (Personally Identifiable Information) data, and documents that may reveal intellectual property.

Once SOCRadar detected the data, its researchers investigated a storage area in a bucket where SQLServer backups are stored. Further investigations of the backups led researchers to discover links between the misconfigured bucket and other Azure Blob Storages. The company claimed that the amount and scale of the leaked data made it the most significant B2B data leak in the recent history of cyber security.

The research team informed Microsoft of the leak on 24 September, which then reconfigured the server to make it private within several hours. The pair then collaborated on investigating the leak and successfully mitigated the risk of exposure.

Microsoft has said it has found no indication that customer accounts or systems have been compromised as a result, but it has notified those affected by the incident directly.

It said the data included names, email addresses, email content, company name, and phone numbers, and may have included attached files relating to business between a customer and Microsoft, or an authorised Microsoft partner.

However, Microsoft has accused SOCRadar of exaggerating the severity of the incident, which has been blamed on an unintentional misconfiguration on an endpoint and not the result of a security vulnerability. Microsoft also claimed the server was not in use across the Microsoft ecosystem.

“We appreciate SOCRadar informing us about the misconfigured endpoint, but after reviewing their blog post, we first want to note that SOCRadar has greatly exaggerated the scope of this issue,” stated the company. “Our in-depth investigation and analysis of the data set shows duplicate information, with multiple references to the same emails, projects, and users. We take this issue very seriously and are disappointed that SOCRadar exaggerated the numbers involved in this issue even after we highlighted their error.”

SOCRadar has also provided a free service where companies can search their company names to see if they are impacted by any of the leaks. In response, Microsoft said it was disappointed by the release of a search tool, adding it was not in the best interest of ensuring customer privacy or security, and potentially exposing them to unnecessary risk.

It recommended that if security companies want to provide a similar tool, they should follow basic measures to enable data protection and privacy. This includes implementing a reasonable verification system, following data minimisation principles to ensure information is only delivered to that verified user, and not giving information out that belongs to different customers.

Researchers at cyber security firm WithSecure have issued an advisory, warning that the method used to generate encrypted messages in Microsoft Office 365 can be cracked relatively easily.

Microsoft Office 365 Message Encryption (OME), a feature offered within the Office 365 suite, allows enterprise users to send encrypted messages as an HTML attachment via email.

Microsoft says the function is useful for sending sensitive data such as medical records, but WithSecure contends the service uses an insecure method of operation for encryption, allowing threat actors to infer the structure of encrypted messages.

OME messages are generated using Electronic Codebook (ECB), in which the text of the message is broken down into cipher blocks that are individually encrypted using a key stored and managed by Microsoft, through Azure Rights Management (Azure RMS). Each character within the plaintext is directly substituted for a cipher text character, according to the key.

However, through this method identical blocks of plaintext will return identical blocks of encrypted text, allowing patterns within the content to be identified. This is particularly the case with emails, which have structures that are more easily predicted than other types of messages typically sent through end-to-end encrypted (E2EE) apps, such as Signal or WhatsApp.

Emails within organisations, which are likely to contain repeating headers or footers, might be especially vulnerable to this kind of malicious decryption, as patterns reveal the encrypted substitutions for plaintext. If a message from an organisation always signed off in the same way, an attacker with access to a database of such messages would be able to partially decrypt each one.

WithSecure has advised organisations to consider alternative channels of communication for sensitive company information.

Recipients are required to access messages through a one-time passcode, valid Microsoft account, or work account in order to decrypt messages, and end-users can revoke access to sent emails at any time.

However, OME imposes no usage limitations on the attachment itself. It's possible, therefore, that threat actors could intercept the attachments, print them, or be forwarded them by the original recipient with little remediation possible on the sender’s end.

WithSecure reported the issue, which it classifies as a vulnerability, to Microsoft on 11 January. However, after several repeated attempts to contact the tech giant, and a notice that it would go public with the disclosure, WithSecure claims it received the following message from Microsoft on 21 September:

"The report was not considered meeting the bar for security servicing, nor is it considered a breach. No code change was made and so no CVE was issued for this report."

Researchers cite Microsoft compliance documentation to posit that ECB is used to maintain backwards compatibility with legacy versions of Office, which only support Advanced Encryption Standard (AES) 128-bit ECB.

In addition to OME, enterprise users can use two other encryption services within Office 365. These are Information Rights Management (IRM), and S/MIME, which both offer greater control over the access rights of sent messages. Messages sent through these alternatives are also encrypted using different methods of operation, but come with their own accessibility benefits and drawbacks.

“The rights management feature is intended as a tool to prevent accidental misuse and is not a security boundary," a Microsoft spokesperson told IT Pro.

"To help prevent abuse we recommend customers follow best security practices, including keeping systems up to date, enabling multi-factor authentication, and using a real time anti-malware product.”

Microsoft also stated that its use of ECB encryption supports legacy applications, and that it is working on alternative encryption protocols for future product versions.

This article has been updated to include a statement from Microsoft.

Car manufacturing giant Toyota has admitted that a server containing the data of 296,019 customers was openly-accessible for the past five years.

The company discovered on 15 September that the source code for its T-Connect app and website had been posted on a public GitHub repository in December 2017.

Although this in itself was an issue, the issue was compounded with the discovery that the source code included an access key to a data server containing the email addresses of nearly 300,000 customers.

The company has since made the repository private, and changed the access key to the server but the extreme delay in discovering the leak, believed to have been inadvertently made by a third-party developer working on T-Connect, has caused concern.

Customers who had signed up for the company’s T-Connect service since July 2017 are potentially affected by the leak, which exposed email addresses and the customer management number assigned to each customer by Toyota.

Toyota expressed regret for the incident in a blog post and admitted that although there is no evidence that threat actors accessed the information, it cannot be ruled out at this time.

“Having all the email addresses available will give bad actors the chance to start targeted phishing attacks, personalised to the recipient, and if Toyota does not implement continuous email security and anti-phishing training, this could easily result in a far greater security problem than just the leaked emails,” said Markus Strauss, head of product management at Runecast.

Beyond the impact to customers, data breaches and leaks can cause reputational damage to affected firms. The company has warned affected customers to be wary of suspicious emails, and to look out for telltale signs that they are malicious or part of a wider phishing campaign.

“We have no confirmation of a leak of data beyond this information. There is no impact for our customers in Europe,” Toyota told IT Pro in a statement.

“We sincerely apologise for any inconvenience and concern this may have caused to our customers and will continue to work with our contractors to ensure thorough management of the handling of personal information to provide services that our customers can rely on.”

Gartner Peer Insights is a free peer review and ratings platform designed for enterprise software and services decision makers. Reviews go through a strict validation and moderation process in an effort to ensure they are authentic.

The “Voice of the Customer” is a document that synthesizes Gartner Peer Insights’ reviews into insights for IT decision makers. This aggregated peer perspective, along with the individual detailed reviews, is complementary to Gartner expert research and can play a key role in your buying process, as it focuses on direct peer experiences of implementing and operating a solution.

In this document, only vendors with 20 or more eligible published reviews during the specified 18-month submission period are included. Reviews from end users of companies with less than $50M in revenue are excluded from this methodology.

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Organisations of all sizes are accelerating the number of applications being spread across cloud ecosystems. The demand for data to power cloud apps, improve AI models, and deliver on digital business initiatives has never been higher. This report focuses on cloud Master Data Management (MDM) as a key enabler of those initiatives.

The cloud enables enterprises to differentiate and innovate with MDM at a much more rapid pace than was ever possible before. The cloud is a disruptive technology: when compared to on-premises deployments, cloud enables elastic scalability, faster times for server deployment and application development, and reduced costs for storage.

Download this whitepaper to learn how the cloud can open up a great number of service possibilities for MDM, which can directly impact business results.

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The Master Data Management (MDM) market is evolving to meet the needs of a broader range of stakeholders who are seeking the business agility afforded by a single, trusted, enterprisewide view of master data. Data and analytics leaders should use this research to inform their MDM solution choices.

Gartner defines MDM as a technology-enabled business discipline in which business and IT work together to ensure the uniformity, accuracy, stewardship, governance, semantic consistency and accountability of an enterprise’s official shared master data assets.

Download this whitepaper to discover the pros and cons of the current vendors in the MDM solutions market.

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Master data management (MDM) is the gold standard of data management and analytics, but many organisations struggle to select the right solution to meet their needs. With a host of MDM vendors offering packaged solutions, it is sometimes difficult to understand how they differ, or which MDM platform would be the best fit to achieve an organisation’s goals.

Therefore, it is important to first identify your desired business outcomes and understand what features are needed so you can select an MDM solution that is the best fit for both short-term and long-term needs. Choosing an MDM solution that’s not aligned properly can result in wasted time, resources, and money.

Download this whitepaper to learn the key considerations in selecting an MDM platform.

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Data is one of the most strategic assets for any business because it fuels digital transformation. The right data enables you to engage effectively with existing and potential customers, deliver a unique brand experience, empower strong business decisions, increase operational efficiency, and much more.

Yet organisations struggle with disparate, duplicate, and conflicting information from a wide range of data sources across the enterprise. Growing data volumes, new information sources, and increased velocity of data add to the challenges.

Download this whitepaper to see how Master Data Management (MDM) provides a “single source of the truth” to enhance targeting efforts, unleash cost savings, and improve operational returns for your business.

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Organisations deploy a master data management (MDM) strategy to gain a single, trusted source of reliable information to deliver business value. Until recently, those seeking an MDM solution had to choose between a fullfeatured on-premises master data management platform or a more limited cloud-based solution.

For the agility to deliver results at the speed of innovation, you need an all-in-one MDM solution with the robust capabilities to meet all your end to-end requirements in the cloud.

This eBook describes why organizations are increasingly looking to move their MDM strategy to the cloud, and what to look for in a cloud based solution that can successfully support your MDM strategy.

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Data platform company Splunk has filed a lawsuit against rival Cribl, alleging that its CEO and other employees stole source code and technical secrets for its own advantage.

Splunk alleged that former employee Clint Sharp, who left the company in 2017, took code without permission that he then used when he co-founded Cribl the same year.

Additionally, it claims that since its formation Cribl has illegally sourced technical documents from outgoing Splunk employees in order to undermine the company.

“Mr Sharp founded Cribl using code he intentionally and unlawfully took from Splunk when he was a Splunk employee without a licence or permission to do so,” read the complaint.

“Since that time, Cribl and Mr Sharp have recruited numerous Splunk employees to Cribl, and have systematically encouraged employees to take Splunk’s confidential technical and business documents with them. In turn, Cribl has used the information it misappropriated to compete unfairly against Splunk.”

In a blog post, Splunk alleges that it attempted to settle the matter privately, but that this was unsuccessful. It characterises Cribl’s actions as a “coordinated campaign of misappropriation” and claims that the company used Splunk’s Technology Alliance Partner (TAP) programme to further its theft.

After launching in 2017, Cribl joined the TAP program, an agreement that allows partners to add to Splunk’s Enterprise platform, through the use and limited copying of Splunk software.

However, the TAP program agreement states that partners may only use the software to demonstrate the use of extensions with the software and to develop extensions further. Using copies of the software to determine source code would constitute a violation of the terms of agreement.

"The allegations in Splunk’s lawsuit are false, and we will defend against these baseless claims," Cribl stated in a blog post.

"We have built interoperability using our own hard work and open source implementations, such as Eventgen. While Splunk tries to stifle competition through litigation, we will keep our relentless focus on our customers to give them choice and control over their data."

Splunk has requested an injunction against Cribl, Clint Sharp and all associated Cribl entities, from further infringing Splunk copyrights. It has also requested an accounting of the profits that Cribl has made from the activity and subsequent damages. The company has requested a trial by jury.

"Proving infringement of copyright in source code, as Splunk is alleging here, tends to be difficult," said Michael Buckworth, founder at UK law firm Buckworths. "A former employee would be incredibly foolish to use a carbon copy of code he has misappropriated; rather he would likely recode the software to deliver substantially similar functionality.

"New code achieving the same outcome as existing code is unlikely to infringe copyright in existing code leaving the damaged party to look at patent infringement or breach of contractual obligations," he added.

"Splunk may believe that they can prove each allegation that they have made with the result that they could secure significant damages from Cribl, or even have it shut down.

"Alternatively, this may be a strategic move to dry up investment and other financial support in Cribl. There is nothing that will turn off investors more than a high-profile IP dispute! Either way both parties will now need to prove their position and live with significant costs if they fail.”

Splunk operates in more than 21 regions internationally, providing customers with a suite that provides oversight over their data and allows them to conduct big data analytics. It also aims to improve observability across multi-cloud environments. Last year it announced a new cloud security suite in addition to its other offerings.

Cribl supplies data management solutions to its customers, aiming to provide data flexibility and stack observability. Its service Cribl Stream is used by DevOps engineers and other industry professionals in order to process data in real time, supply context to data, and encrypt sensitive fields.

IT Pro has approached Splunk for comment.

This article has been updated to include a statement from Cribl.

Data quality has traditionally been mandated to fulfill compliance and governance requirements and to reduce operational risks and costs. It's a competitive advantage that data and analytics (D&A) leaders must continuously engage with in order to achieve those goals.

The data quality management practice has been maturing in recent years and the vendor landscape is focused on addressing many of the market requirements. It covers much more than just technology. It includes workflow, roles, collaboration and processes (such as those for monitoring, reporting and remediating data quality issues).

Download this paper to learn why evaluating and selecting data quality solutions is much less of a specialized IT task than it was formerly. It now requires greater collaboration with business leaders and users.

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Just as pilots run through a pre-flight checklist before they ever leave the ground, taking steps to increase your understanding of and confidence in your data in the cloud is key to better data-driven decisions that send your business initiatives soaring.

Our eBook “Setting Your Sights on Data Intelligence” is your pre-flight checklist for navigating your data landscape in the cloud and landing safely with horizon-expanding insights. You will learn about:

• Ensuring you can find, understand, trust, and access your data
• Understanding data relationships and flows
• Harnessing AI and machine learning to support data-driven decisions

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It’s hard to believe how much financial technology, or fintech, has changed the realms of traditional banking and lending institutions. Now, thanks to ubiquitous digital technologies and the widespread flow of data, loans and insurance can be arranged on a smartphone app.

But as third-party provided fintech is heavily reliant on the secure exchange and processing of data - typically with apps - it’s an attractive target for bad cyber actors, which means it’s in dire need of cutting-edge data security, such as Confidential Computing.

A smart answer to these challenges is to conduct fintech and decentralised finance activity within the secure enclaves of a Confidential Computing implementation. Confidential Computing can combine with blockchain technologies to allow users to provide attestation and verification services for privacy and security.

Download this whitepaper to see how Confidential Computing can combine with hardware security modules to ensure that access is limited only to the right people, and only for specific authorised tasks.

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IT infrastructure services provider Kyndryl has announced a new strategic partnership with Teradata, a multi-cloud data platform for enterprise analytics.

The collaboration aims to help customers apply artificial intelligence (AI) and data modernisation techniques across their IT environments to boost the performance of various projects and speed up time-to-value.

Kyndryl’s data and AI services, as well as its infrastructure management tools, will be paired with Teradata’s high-performance cloud analytics and data platform in a move the pair claim will help customers migrate their on-premises data warehouses to the cloud with hyperscaler platforms.

In an announcement, the companies said they will help customers harness AI to gain better insights from their hybrid and multi-cloud data environments by designing, enabling, and supporting enterprise data modernisation solutions.

“We are thrilled to partner with Teradata who is a trusted and valued technology partner to many customers, providing a best-in-class analytics and data platform for enterprises across the globe,” said Nicolas Sekkaki, applications, data and AI global practice leader at Kyndryl.

“We look forward to deepening our partnership so we can deliver greater value and results that help companies transform and compete in their industries and around the world.”

London-based Teradata has created VantageCloud, a connected multi-cloud analytics platform for the enterprise, designed to help businesses leverage data and analytics to drive performance.

The firm says this new strategic partnership will help customers to leverage Kyndryl’s expertise – which includes advisory, implementation, and managed services – to get the most out of the platform.

There will also be a focus on delivering industry-specific analytics services geared toward customer modernisation challenges across key verticals such as manufacturing, communications, financial services, retail and CPG industries.

“This joint expertise will enable our customers to drive more actionable insights and higher value from their data through advanced analytics and AI/ML initiatives,” said Lisa Stewart, SVP of worldwide partners and alliances at Teradata.

Formed just last year as a spin-off from IBM, IT infrastructure services provider Kyndryl designs, builds, and manages complex mission-critical information systems for customers across more than 60 countries.

The firm’s partnership with Teradata is the latest in a string of collaborations struck since it went solo at the tail end of 2021. Recent deals include a hybrid cloud and edge partnership with Lenovo, a cyber resilience collaboration with Dell, as well as a delivery partnership with Oracle, which was announced back in June.

The company also has agreements in place with the three largest cloud providers, AWS, Google Cloud and Microsoft.

If you’re reading this, you’ve recognised that it’s time for data governance. The challenges that brought you here could be anything from compliance and customer centricity initiatives to productivity improvements and decision support, to name a few. Whatever your driver, one truth should be self-evident: you can’t lead data-driven digital transformation without end-to-end enterprise data governance.

But governing data across the entire enterprise is hard work. It’s a huge responsibility and it demands the involvement of many stakeholders. That’s why “just enough” data governance could be the right move for you.

Download this asset to discover why it’s all about reducing the scale of the data governance challenge by doing enough to earn early credibility that builds to critical mass.

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Informatica offers a suite of cloud integration and cloud data management solutions, including Integration Platform as a Service (iPaaS), for connecting disparate applications and data deployed in diverse environments. Informatica Intelligent Cloud Services (IICS) is a comprehensive iPaaS consisting of data integration, application integration, and data management services for multi-cloud, hybrid environments.

To better understand the benefits and costs associated with an investment in Informatica iPaaS, Nucleus conducted an in-depth return on investment (ROI) assessment of several customers using Informatica technology. These customers realised an average ROI of 321 percent over a three-year period, with an average payback period of four months.

Download this guide to learn more.

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Data teams need to get more productive, and fast, to reconcile booming data supply and demand. Autonomous data management (AutoDM) solutions can help ease bottlenecks for data teams by using metadata, automation, and artificial intelligence to standardise and accelerate data delivery.

While the concept is not new, advances in computing power and advanced analytics algorithms make AutoDM viable for many modern enterprises.

Download this resource to follow the steps shown to achieve the best results with AutoDM software.

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As a data leader, you already know that data plays a key role in your company’s digital transformation. But it can be frustrating to manage this resource across many channels within your organisation.

A recent survey of 300 data leaders (CDOs, CAOs and CDAOs) in the United States, Europe and Asia Pacific showed that companies juggle data across five different data management solutions on average, which has prompted 46% of those surveyed to invest in new technology to integrate multiple solutions over the past two years.

Download this paper now to see why it's time to prioritise more than just solution integration, and why you need to integrate business and culture objectives to benefit your organisation and its data consumers.

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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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Cloud adoption is growing exponentially, and it is a key enabler to every digital transformation. As organisations move to the cloud for agility, scalability and flexibility, they are adopting cloud-native, intelligent, automated solutions, and multi-cloud platforms.

At the same time, they're consolidating and modernising their traditional on-premises data warehouses and data lakes to take advantage of cost savings and operational efficiencies of the cloud. Cloud and analytics modernisation go hand-in-hand.

Download this report to appreciate how today's focus is less on justifying the move to the cloud but more on how to get there faster, and learn how to overcome the common data management mistakes that can hinder analytics modernisation.

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Salesforce has announced the arrival of Salesforce Genie, its new hyperscale data platform that creates real-time customer profiles to help businesses deliver personalized experiences.

Detailing the platform at its Dreamforce ’22 event, Salesforce said Genie powers the entire Customer 360 CRM platform to provide a “more automated, intelligent, and real-time” experience.

Complete with its data lake, the platform is designed to help businesses deliver highly personalized experiences across sales, services, marketing, and commerce, that continually adapt to customer needs in real-time.

“Every business leader wants to take advantage of real-time data to create compelling, personalized customer experiences — milliseconds matter in this new digital-first world,” commented David Schmaier, President and Chief Product Officer, Salesforce.

“That’s why we built Genie, our most significant innovation ever on the Salesforce Platform. Genie makes every part of Customer 360 more automated, intelligent, and real-time.”

Genie gathers and stores real-time data streams at scale and combines them with Salesforce transactional data. It does this using built-in connectors that bring in data from across all channels – including mobile, web, and APIs – as well as legacy data through MuleSoft and historical data from proprietary data lakes.

It then transforms this data into a real-time customer graph which acts as a unified customer profile record. Everything in this graph is visible and actionable across the entire Customer 360, industry solution, AppExchange, and customer apps.

Salesforce says the offering enables Einstein AI and Flow automation services to create more responsive and dynamic actions and engagement based on real-time data. The platform also runs on the firm’s public cloud infrastructure Hyperforce, which provides data residency, security, privacy, and regulatory compliance controls.

Partnerships also expand Genie’s abilities, Salesforce added. These include real-time data sharing between Salesforce and Snowflake, tailored AI model building with Amazon SageMaker, first-party advertising with the likes of Amazon Ads or Meta, as well as a new Genie collection on AppExchange.

Penny Gillespie, VP and analyst at Gartner, said Genie has the potential to bring real-time personalization across the entire enterprise.

“It harmonizes disparate data with privacy consent and compliance, automation, intelligence (Einstein), and speed,” she said. “It enables the discernment of millions of records to have one unified customer profile which is neither easily achieved nor highly available today with suggested real-time actions—be it a presentation layer change for a digital experience or coaching a sales or service employee.”

With the ability to know and discern every aspect of what a customer is trying to achieve, Gillespie added that the days of asking customers a lot of questions to help them may now be surpassed.

“Coupling the power of customer knowledge with AI has the power to solve the customer’s problem before the customer has even framed the problem—regardless of whether the area is service, sales, etc,” she explained.

“The result is truly effortless customer experiences which we know foster customer satisfaction, loyalty, and repurchase.”

Salesforce’s Customer Data Platform, which is powered by Genie, is available now, alongside Genie for Industries, Tableau + CDP Connector, and MuleSoft Anypoint Connector. Further integrations will be released from December and into 2023, the company said.

Financial services have always been ahead of many industries in their use of consumer data technology. However, financial services are now facing challenges from increased regulation, high expectations from tech-savvy consumers, and more agile competitors.

Embracing further technology advancements will allow financial companies to remain competitive, and reduce costs while delivering even better customer service, but the question remains for CIOs on where to begin.

Download this guide which provides a clear direction for thought leaders on how to leverage big data analytics and how to grow share in the financial sector through digital capabilities.

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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."

With the vast amount of data produced on a daily basis, companies are responsible for storing, protecting, and analysing this information to optimise their performance. And when sourcing technology to support these data initiatives, organisations consider reliability and performance as their top priorities.

This study from ESG looks into the top capabilities and attributes that businesses consider to be the most valuable when it comes to data infrastructure, and reviews Dell’s PowerStore and how it can improve data resiliency.

Download this report to read about the specific software capabilities of PowerStoreOS and see the results of ESG’s technical validation.

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The events of recent years have caused an increase in technology investments, as organisations embrace digital transformation in order to maintain performance. For small and medium-sized businesses (SMBs), there’s a further need to ensure they’re getting the most out of these digital assets when budgets are tight.

This eBook discusses the growing need for modern storage solutions, and how organisations that refresh their storage hardware can continue to meet business performance needs, while cost-effectively driving growth.

Download this whitepaper to discover Dell EMC’s portfolio of storage solutions, offering optimisation and flexibility as your business needs change, with payment options to suit.

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Cohesity has announced the appointment of Sanjay Poonen as its new CEO and president, with the former VMWare COO also joining the data management company’s board of directors.

The industry veteran will now lead Cohesity’s next phase of growth as the vendor looks to build on its strong standing in the IT industry.

“Cohesity sits at the intersection of three of the highest-priority business issues today – cyber security, cloud, and data management – and is poised to become a major powerhouse with industry analyst firms naming the company a leader and one of the fastest growing in its category,” he said in an announcement.

In his most recent role as COO of VMware, Poonen oversaw sales, marketing services, and alliances, and was instrumental in doubling the company’s revenues from $6 to $12 billion. He also played a key role in deals with industry giants such as AWS, Microsoft, Google, and Oracle.

Prior to his role at VMware, Poonen served as President of SAP, leading the software firm’s Applications, Industries, and Platform teams, serving in engineering and sales roles that helped double the company’s revenues to $20 billion.

At Cohesity, he replaces outgoing CEO and founder Mohit Aron, who will now lead the company’s product innovation and roadmap as founder and chief technology and product officer.

“As we scale, it is important to me to have a tighter focus on where I spend my time to have the greatest impact,” Aron explained. “I approached the Board with the goal of finding a seasoned and proven executive that I could partner with to achieve our ambitious goals.

“I’m excited to work with Sanjay as we continue to grow and disrupt the $25 billion data management market.”

In a post detailing why he took the role of Cohesity CEO, Poonen highlighted a combination of the vendor’s people, data protection product, partner pool, as well as the $25 billion total available market opportunity that the vendor is aiming for.

“Cohesity is built for a multi-cloud era, with a superior modern platform that includes a self-managed and SaaS approach – this creates an opportunity for the next decade plus,” he said. “If we continue to execute, Cohesity is poised to become a major powerhouse in the industry.”

Addressing partners, Poonen underlined his commitment to helping them be a “force multiplier” of the benefits of Cohesity’s data management and data security solutions.

“With your help, we can greatly amplify the number of customers we can access on our own, so we need you!” he said. “We are grateful for our corporate investors – Amazon, Cisco, HPE – who have not just invested in the company but are also strategic partners.

“And, to VMware, Pure Storage and Nutanix, they have also been strategic partners to us, I am excited about the untapped opportunity we have before us.”

Discover why IBM ranked second highest in the Data Fabric Use Case according to Gartner analysts.

“A data fabric enables faster access to trusted data across distributed landscapes by utilising active metadata, semantics and machine learning (ML) capabilities. It is an emerging design; data fabric isn’t a common use case in the market yet. We picked it as a forward-facing use case — not every vendor has the full set of capabilities to deliver a data fabric design.”

Download this free Gartner® report to see how IBM is addressing this emerging design and has ranked second highest in the Data Fabric use case.

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The accelerating adoption of modern technologies—cloud, mobility, the internet of things (IoT), and now work-from-home facilitators—has led to an increase in the complexity of IT infrastructure, as well as a proliferation of data. These factors put organisations and their IT infrastructures at greater risk for malicious attacks, human errors, and negligent behaviour.

Businesses now need to have a foward-thinking approach to cyber security, and prepare themselves by implenting storage solutions that can recover quickly from cyber attacks and safeguard critical data.

Download this whitepaper to learn the importance of data management and storage in a comprehensive cyber resilience strategy.

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