Data Migration Testing

Plotting a Smooth Path to Data Migration

Businesses spend billions of dollars migrating data between information-intensive applications. Yet up to 75 percent of new systems fail to meet expectations, often because flaws in the migration process result in data that is not adequately validated for the intended task. Because the system itself is seen as the investment, any data migration effort is often viewed as a necessary but unfortunate cost, leading to an oversimplified, underfunded approach. With an understanding of the hidden challenges, managing the migration as part of the investment is much more likely to deliver accurate data that supports the needs of the business and mitigates the risk of delays, budget overruns, and scope reductions that can arise.

Why Migrate Your Data?

Data migrations generally result from the introduction of a new system. This may involve an application migration or consolidation in which one or more legacy systems are replaced or the deployment of an additional system that will sit alongside the existing applications. Whatever the specific nature of any data migration, the ultimate aim is to improve corporate performance and deliver competitive advantage. Accurate data is the raw material that maximizes the value of enterprise applications. However, when existing data is migrated to a new target application, it can become apparent that it contains inaccuracies, unknowns, and redundant and duplicate material. And although the data in the source system may be perfectly adequate for its current use, it may be wholly inadequate, in terms of content and structure, for the objectives of the target system. Without a sufficient understanding of both source and target, transferring data into a more sophisticated application will amplify the negative impact of any incorrect or irrelevant data, perpetuate any hidden legacy problems, and increase exposure to risk.


Testing of a data migration suite is itself often a moving target. The deployment of the new system often gets squeezed by other business priorities, leaving little migration testing time. Unit testing should identify holes in what has been built, but because the unit testing is conducted on a small sample of data, the results are unlikely to be representative of the whole data set.

It is quite often heard that an application is moved to a different server, the technology is changed, it is updated to the next version or moved to different database server etc.. The entire database is migrated to a new version or totally to a new platform. In the both the cases, when the data is pushed to the new environment, it is important to be assured that the records are being correctly migrated and their vital/ essential values are correct, as earlier. SSPL, with its team of experts in this field, help the clients to test the migration with 100% records being analyzed on its tool, and tested with user required parameters.

It helps to identify the shortcomings and data related issues, from the earlier version to the new version. Assures on the critical GoLive day, everything is perfect and as per the expectations.

The technology with its critical technical advancements, help the clients to gain better in-sights of the migrated data tables, fields and records. Few of the technological benefits are listed below:

  • 100% data testing, with no sampling or test records.
  • Once data is captured, the records cannot be modified. User gets most reliable report.
  • There is no limit on the number of records and fields to manage the testing.
  • Fast processing of the tables.
  • Fully customisable logics and conditions can be incorporated in shortest possible time.
  • It can be automated to be performing Auto-Mode testing analytics, and reports could be received over emails.
  • Output reports can be customised as per the needs and requirements.
  • Besides testing, SSPL also support for Data Migration activity.
  • If new application is being migrated, SSPL also perform application testing.

The Risks of Overlooking Data Content

Basing rules on examination of small source data samples and relying on metadata descriptions is a major risk that is likely to mean that:
  • Time and budget estimates will fall short of actual needs.
  • The target system will not perform effectively
  • Workarounds will need to be implemented and resourced
  • Remedial data cleansing work will need to be devised and resourced
  • The costs of missing the deadline will include maintaining the team and incurring continued running costs of legacy systems and downtime on the target application
  • The new system will be blamed, making it harder to gain user acceptance
  • Management confidence will be questioned To know more about our services and solutions, please feel free to write us at