Execute build and test plans; run detailed data profiling and quality checks on target systems, identify orphan records and handover for UAT.
Decommission source systems and run in parallel for specified time. Archive and purge data where required. Ensure an ongoing process to measure and correct Data Quality issues is proven.
Determine the scope and stakeholders involved, begin to define upstream and downstream impacts of the data migration.
Identify critical data elements and segregate data into categories. Assess data age and determine data linkages.
Identify source/target mappings. Identify data transformations and run detailed data quality and profiling checks. Identify trends, outliers and anomalies.
Test all data transformations identified in the solution design, review data flows to improve consistency, accuracy, validity, completeness, timeliness & fitness for use of data.
When it comes to data migrations, failing to prepare is preparing to fail.
Many organisations undergoing a data migration encounter unforeseen challenges that increase budgets and throw off timelines.
With the help of our data quality management platform, you gain visibility into your data and achieve greater control over the migration process. De-risk and streamline your migration project to ensure you successfully move your data to the new environment on time and on budget.
In many cases, the complexity and magnitude of data migration is underestimated. At Experian, we partner with our clients and specialist providers to develop the migration scenario most suitable for your needs and requirements.