The importance of data testing and how to do it right
Data testing should be an integral part of any project – but what should you do if you don’t have a testing team in place?
As the IoT rapidly expands we’re producing more and more data, with recent estimates claiming that each individual person created 1.7MB of data every second in 2020. That’s a staggering 2.5 quintillion bytes of data produced by humans every single day.
Data is one of the most valuable assets for any organisation that’s committed to long-term growth. Whether it’s developing applications, websites or data products in general, the amount of information being gathered and processed can be significant. An organisation that doesn’t have data at the heart of its digital transformation plans is likely to fall behind quickly.
Maintaining data quality is critical in building a successful business, particularly as it now underpins so many facets of day-to-day operations. Good quality data means better business decisions and better outcomes for customers. According to Gartner’s ‘How to Create a Business Case for Data Quality Improvement’ report, the average financial impact of bad data on businesses is $9.7 million (£7.13 million) per year.
However, once an organisation knows it has good and valid data in place, it may want to look at how to establish testing functions to leverage that information across various projects for the benefit of the business.
The role of testing
If this is the case, then it's crucial to establish testing functions that are fit for purpose. Specific projects and products will need test plans written that focus on the deliverables of the project. Once these requirements have been identified, data sources must be checked before test cases are designed and executed.
Once data has been verified and validated, the role of the tester is to check if the dataset will produce the necessary outputs for the project that will be leveraging it. For example, a system may be designed to search a database of C-suite executives and contact those individuals via email. The data will then be tested, to ensure that each record pertaining to a C-suite exec has a valid email address, and report failures for records that don’t. Meanwhile if another feature of the system is enabling data extraction based on a condition given by an end user, for example extract C-suite executives at organisations with 500+ employees, the tester will interrogate with a different criteria i.e. if the system fetches the correct data set for the condition given.
It’s important to understand that this form of data testing is not concerned with authenticity or structure – ideally the datasets will have been authenticated and verified prior to any specific data testing routines.
The tester will essentially execute the test, log the results and report any errors with the outcome. One important consideration is in test data performance, the processing speeds and loading times to help fulfil the task. It’s also vital to have good test data generation tools in place, allowing your testers to load and stress-test the information. Moreover, where your data is stored is critical – is the information held in a data farm, across cloud spaces or a mix of the two?
Once all these considerations have been addressed, data testers can be recruited from within the company or as off-site resource depending on the budget and complexity of the testing.
If the workload demands on internal teams is likely to be an issue then looking outside the business may be the best way forward. Fortunately, there are companies that specialise in these kinds of testing projects.
Finding testing resource
Bringing in external tech resourcing from overseas is no longer seen as something that can hinder business progress. The COVID-19 pandemic has meant that many organisations are now having to operate with a distributed workforce, and the question marks over having staff operating from multiple geographical locations are quickly eroding. As remote working becomes the norm, many of the issues over communication and productivity are being ironed out through necessity. What was once a challenge is now something that’s an accepted part of how organisations operate.
One such organisation that can help with testing demands is Merit. It offers services to optimise product performance and remove errors during the build, launch and usage phase. Merit has established off-shore Software Development Engineers for Test (SDETs), with strong experience of collaborating with UK companies.
Resources can be scaled up or down as required, with Merit providing the flexibility to adjust team size depending on demand. For example, clients can increase the headcount during the holiday season to ensure that their on-site team isn’t overly stretched or that there is no compromise on work quality. The external testing teams can also operate to mirror UK office hours, and come with existing knowledge of workflow management tools so they can match all internal processes.
Data testing is hugely important because of the trust it engenders. Testing gives confidence, meaning organisations can progress with projects, lift productivity and help drive long-term success. Subsequently, data can be used to steer the future of an enterprise. Yet, as datasets grow, with multiple sources such as customer transactional data, browsing history and social media data, testing this data becomes even more important.
However, not every business has the internal resource to implement and execute a thorough testing strategy. With Merit, gaps in skills and knowledge can easily be filled, creating a unified team to deliver on any testing requirements. This combination of internal and external talent will leave a business well-positioned to make use of data and march on with its digital transformation plans.
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