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Which is the best test data management method?

First and foremost, you need to have a strong, highly-functional and efficient test data management strategy that functions perfectly and efficiently to reap all the benefits that it has to offer. <br>

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Which is the best test data management method?

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  1. Which is the best test data management method? 

  2. The test automation process is very crucial for product tests and releases. It also can be the prominent factor to build the trust and credibility for your brand. • Well, first and foremost, you need to have a strong, highly-functional and efficient test data managementstrategy that functions perfectly and efficiently to reap all the benefits that it has to offer.  • However, still, many software developers and quality analysts don't have any ideas about how to design and implement the test data management strategy. • Even professionals who know about it, are confused when it comes to choosing the right data test management method for their products. Well, multiple options will certainly put you in a dilemma. • In this post, we will discuss some of these methods and their unique strengths and weaknesses to help you in the decision making process. 

  3. Data replication from production  • This is the most popular and preferred approach, especially among the beginners. When there is a need for test data to feed in your testing processes, copying data from production is not just the most convenient thing, but it is also a realistic approach. • Well, it is not as easy as it seems as there are some drawbacks to this approach. • The first issue with the data replication approach is the manual feeding of data into testing processes. Now, you might argue that there are scripts and automated jobs available to do the heavy lifting, but data availability when it is needed is also as much crucial as data generation. • Relying on a native approach which is solely based on scripts might not be efficient and sufficient. It might force you to rely on the manual process. • In addition to that, there is also a possibility that this approach is not lending itself well when it comes to negative test cases. • Negative testing is the scenario where the tests validate the system against invalid data. You cannot rely on this approach when you want to test the system against negative testing. 

  4. Also, if you want to test the product when it is in the development process, it cannot be possible with a data replication approach as there is no data available in production to copy from. • Frequently testing the product at different stages of development is the new technique with many benefits. You can't do this with this approach.  • Last, but not the least, this approach might abuse data and by doing so, fail the data compliance rules and regulations. • You might face catastrophic legal, financial and brand credibility consequences.  Data Masking 

  5. The data masking method was developed to address all the limitations of the data replication approach. • Here, test data management tools will use this approach by applying masks to production data. • These masks will remove all the personally identifiable information from the data. • However, it appropriately deals with data compliance restrictions of the precious data replication approach, it too has some downsides. • First, the time this approach takes is even more than the data replication approach. • Well, this is an issue when you need to release the product quickly.  • Furthermore, the data masking approach is not a standalone approach as it just resolves one downside of the data replication approach. • Just one downside, not all of them. Data masking is not a solution if you want to develop a product in the development stages with no production data.

  6. Synthetic data generation  Here, fake or synthetic test data is generated from a data model that is then used for data testing. The values are disconnected with any actual data and tools can preserve the data format, but to generate synthetic data out of nowhere, this approach reduces the risks of exposing sensitive data. However, the downside is you might end up with data which is not similar to production-like, which is the goal of a good TDM strategy. Wrapping up  There are some more methods for test data management, some of them are just variations and combinations of the approaches we discussed here. Apart from generating data, you also need to keep in the mind data quality, data availability and security too. 

  7. Contact Us Company Name : Enov8 Contact Person : Ashley Hosking Address : Level 5, 14 Martin Place, Sydney, 2000, New South Wales, Australia Email : enov8australia@gmail.com Phone(s) : +61 2 8916 6391 Fax : +61 2 9437 4214 Website :- https://www.enov8.com

  8. Thank You

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