Data Genie

One of the biggest challenge of IT organizations which is hitting their profits due to delay in projects and poor quality of code with respect to both functionality and performance, all this is attributed to lack of availability of right data at right time and required volume.

Making right data and volume available on demand for Unit Testing, Quality Assurance, User acceptance Testing, Regression and Performance Testing will save business from losing customers, business to competitors, penalty from regulators and delay in catching fraud.

Major Challenges of Test Data Management which Data Gen Addresses:

Data Privacy

Many applications contain sensitive personal information. There may be government mandates and regulations in place that stipulate the data that must be masked, de-identified, or encrypted. Without a solid process to protect that data, there’s a real risk that valuable and personal information could leak and be used in a malicious manner. A data breach can be extremely expensive to sort out; it can damage reputations and can result in lawsuits and punitive fines.

Data Selection and Sub-setting

You need data that’s relevant to the context of what you’re testing, but how do you manage data requests effectively? You’ll want to use a smaller subset of data in a scaled-down, non-production environment, but it must mimic the production environment. If you don’t get your selection right, test coverage won’t be as good as it could be.

Data Availability on Demand

Data not available on time is revenue lost in terms of lost hours, reduced productivity and delayed project timelines. Test data availability is very critical for organizations to meet timelines for business efficiency and keep check on cost.

Meaningful Data

Generating data is easy but being meaningful adds value to testing in terms test cases coverage as well keeping uniformity to be able link and correlate to other relational tables.

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Data Genie – Addresses following questions

  • What is required to create required data?
  • How much is the cost to create the test data?
  • How many defects are attributes to the test data quality?
  • How quickly the test data is made available?
  • Is right volume made available?
  • Is the test data generation available as self-service?
  • Does it solve the problem of data privacy?
  • Does the test data generation provide data selection and sub-setting?

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