Data Migration

The information technology industry mandates data migration testing to enable the adoption of social, mobile, analytics, and cloud (SMAC) technologies, align with mergers and acquisitions and ensure continuous system upgrades. Comprehensive data migration testing helps make data migration predictable and ensures first-time releases are accurate.

Challenges in data migration programs

  • Poor data quality: Irrespective of being aware of the data defects, new deficiencies are often uncovered after extraction
  • Missing data:  Mandatory fields in source systems turning out to be blank or null
  • Mismatched data: Field overuse is a classic problem of incorrect data. Sometimes, two or more different domains of data can be found in one field that is repurposed after its original use becomes obsolete
  • Missing data requirements: Data fields or values are not captured properly. Business and data transformation rules are not sufficiently researched or documented to the breadth or depth necessary for consolidating multiple systems into one target

Approach in data migration programs

Testing of migrated data from old to new systems could involvemigration testing to ensure the following:

  • Migration of data that was loaded by environment  and batch jobs
  • Cleansing  and standardization of data
  • Good quality of loaded data
  • Complete verification of loaded data and metadata — constraints, triggers, inbuilt functions, and stored procedures
  • Comprehensive testing of data model and data types
  • Good match of target system (database / reports) data with old system