Which is the best test data management method?

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Which is the best test data
management method? 

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• 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
  management strategy 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. 

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• 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. 

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• 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 

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• 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.

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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. 
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• Company Name Enov8
• Contact Person Ashley Hosking
• Address Level 5, 14 Martin Place, Sydney, 2000,
  New South Wales,
• Australia
• Email enov8australia_at_gmail.com
• Phone(s) 61 2 8916 6391
• Fax [phone]
• Website - https//www.enov8.com

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