We recently co-wrote a white paper with Sogeti that focuses on SAP test data and what you need to consider as best practices in creating quality SAP test data. Working with them on this project reminded us how much the data you use for testing new implementations and developments can influence the outcome of your testing process.
Working within the realm of SAP, we know that it can become technical very quickly. I tried to explain the value of good test data to a friend, and noticed that there is a correlation between the different elements highlighted in the white paper and the fascinating world of Formula 1.
In both cases, to reach the finish line you need a well-orchestrated mix of speed, precision, and strategy. To win on high-speed tracks, Formula 1 drivers must be able to cover the track accurately by adopting best practices that optimise quality, efficiency, coverage, and safety. It's the same with SAP test data; to align your systems to business needs, you need to focus on security, speed and efficiency.
In this blog, we explore the six best practices in SAP test data, so you can make sure that all your test data moves securely down the track, and all changes are ready for the Production environment.
If you would prefer to skip to the more technical read, you can download the white paper here.
1) Speed & Agility
In Formula 1, shaving milliseconds off a race is vital to victory. Similarly, speeding up the test data provisioning process is essential to the effectiveness of SAP testing.
Over 77% of companies use a manual approach to managing their test data (Tricentis research, 2021), which slows the testing process and delivery. But with constant business changes, it is vital to keep up with new implementations, application changes, and upgrades on the Production system, by testing it more quickly and securely than ever before. You can achieve this by using an automated test data solution to speed up the process of providing data for testing.
Rapid provisioning of test data, like speed in a race, not only saves time, but also allows teams to iterate and improve quickly. Leveraging software to automate some of the manual work is not only best practice but essential in adopting an agile approach to development and testing.
2) Security, risk & compliance
In a high-risk sport like Formula 1, designing a car to protect the driver is a key part of the design process from the start. Similarly, data privacy legislation requires you to include privacy by design as part of your test data strategy. In non-production environments, you allow broader access, and therefore need to scramble data so that it doesn't fall into the wrong hands.
Speed versus security versus accuracy
Designers of a Formula 1 car carefully consider all requirements and select materials that have unique properties; extremely strong and robust for safety, but also lightweight and fit for purpose.
Scrambling test data is essential for security. But from a tester's perspective there is the worry that anonymising the data will not give your testing the accuracy required. And this is definitely something to consider when you anonymise the data; you need to make sure that your scrambling solution doesn't break the data, thus no longer representing the Production environment.
3) Cost & efficiency
In a pit stop, every second counts. Similarly, optimising SAP's test data management processes can have a significant impact on a company’s efficiency and budget. According to the Cap Gemini Quality Report for 2020–2021, large enterprises allocate 22% of their IT budget to QA activities.
Often, to arrive at meaningful and representative test data, companies make a complete copy of the Production system. This is not only time-consuming and difficult, but also very costly, both in terms of manual work hours and storage costs.
With tools such as EPI-USE Labs’ Data Sync Manager™ (DSM) Suite, you can select a portion of the data based on the last month’s transactional data and all master data to create a system with a reduced footprint of your Production environment. Using this method, you can save up to 80% of storage space.
Like a well-executed pit stop, efficient test data practices allow you to reduce your costs and allow your Basis team to be more streamlined.
4) Coverage
A Formula 1 driver needs to know every corner of the track to ensure victory, and not encounter any surprises or snags along the way.
If we compare this to the SAP testing process, we see that coverage is just as important. The key is to test effectively, with as much coverage as possible, and using as few resources as possible. If you have the necessary resources, you can test every corner of the system, but there are times when you have to prioritise to be more efficient.
To stay within the constraints of time and budget, tests can be made for the most critical business functionality first, then moving on to less critical processes, and so on, until a sufficient set of test cases covers the business-critical functionality. Test data management tools such as DSM can facilitate the creation of data scenarios and ensure that the most critical aspects of the SAP system are thoroughly tested, ultimately leading to a successful race to Production.
The way that AI and machine learning will influence this aspect going forward is an interesting topic; we could see more coverage from AI bots, but we need to look at how we train those bots to be accurate and safe.
5) Quality
To make it to the podium as one of the best drivers, several variables come together: strategy, training, speed... but, above all, the quality of your driving technique, the car, and your performance that day.
It's the same with SAP projects: to be able to carry out good tests, which give you confidence in the results, you need high quality test data.
Test data needs to be accurate, realistic and representative of your Production system. This means having sufficient, recent and consistent data across all systems. By ensuring the quality of test data, you can accelerate development cycles, reduce defects, and deliver reliable solutions, running the race safely and confidently.
6) Achieving victory
In conclusion, to win the SAP race, organisations must adhere to test data management best practices. By focusing on quality, speed, efficiency, coverage and security, companies can achieve extraordinary results in SAP testing.
Just as a Formula 1 driver aspires to reach the podium in every race, mastering SAP test data management will position companies on the winners' podium for excellence and security.
For more of the technical details, download the white paper by EPI-USE Labs and Sogeti on SAP test data best practices.
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