Tips for Tackling Test Data Management
When you’re testing an application, you really need to emulate the end user workflows, and you can’t do that without the right data. Good test data will bring your testing environment closer to the live settings that the product is used in the wild, and boost your coverage quality. How do you ensure that you have the correct data, at the right time, in the required quantity? You need to do a little planning and effectively manage your test data.
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The problem with Test Data Management
You’re looking at 3 key challenges when it comes to effective test data management:
- Data validity and consistency – How old is the data? Where did it come from? Can you guarantee its integrity?
- Data privacy – Are you adhering to government and industry regulations? Are you safeguarding customer privacy? Are you protecting your data?
- Data selection and sub-setting – Can you scale down the production environment and choose a representative subset of data? Is your selection process effective?
In order to deal with these challenges, you are going to need to apply a process that poses the right questions at each stage, and devise a system that answers them.
Organize your process into a simple, step-by-step approach and be methodical. You need to start by looking at where you’re going to pull data from. Think about how to identify the kind of data you need and how to generate it. If the data is going to come from production, then there’s a good chance that it will contain sensitive details, and you’re going to have to think about how to anonymize it, or de-identify it. Consider encryption or masking, and always analyze who has access and restrict where applicable.
Once you have a good idea of where your data is going to come from, and you’ve taken steps to mitigate the risk of data breach, you need to make sure that you’re getting the right data. You need a set of criteria for selecting subsets of data, you need to make sure it is refreshed regularly, and you need to validate its integrity. Maintenance questions about how the data will be stored, refreshed, and migrated should be answered at the outset.
Even with a solid process in place, you must remember to make sure the workflow is fully traceable. You may need to audit (and re-audit) later, and clarity makes the debugging process a lot easier. It may be possible to automate your integrity checks and refresh schedule, to create a set of self-healing scripts that combat false negatives and failures based on obsolete data and replace them according to your pre-determined criteria.
There’s more to test data management than most people realize, and a failure to tackle the main challenges head-on can create serious problems in identifying real issues within the application down the line. Plan carefully before you start testing. Make sure that your data selection, migration, and validation process is secure and effective. Evaluate the process and make ongoing improvements wherever you can.
The right test data management plan can really boost the quality of your test coverage.