Data Migration

Data Migration – getting data ready for business

There are several reasons for migrating your data to a new platform, but they all have one thing in common. Your data has to be prepared for the move.

Are you planning to adopt a new platform:

• for cost-efficiency or process streamlining, through platform or application consolidation?
• so you can discard a legacy Oracle database in favour of Azure, Google Cloud Platform or Amazon Web Services?
• because of a business merger or acquisition?

Whatever the reason, before you can migrate your data you need to understand what it is now, and what it needs to be, to make it suitable for your new platform.

Preparation for migration

There are 4 stages to preparing your data for migration:

STAGE 1

Extract the data from your legacy systems

STAGE 2

Discover the data quality and create a data profile, so you can assess it against the new platform’s requirements

STAGE 3

Build remediation plans and processes to ensure data is fit for purpose

STAGE 4

Reduce data inconsistencies by:

- standardizing

- enriching

- cleansing.

Once the data has been migrated (using a suitable ETL tool) the legacy system should be decommissioned and retired, and the underlying data removed.

However, the need for data quality doesn’t end once the data has migrated:

• Governance roll-out – governance principles established during migration should be rolled out to other projects
• Continuing control – data stewards should be empowered and enabled to ensure monitoring and management of data continues after migration.

The Agile approach

By using agile methodology, Agile Solutions makes your data migration more effective and more successful.

Agile methods provide an iterative mechanism for implementing the processes and moving the data, which helps to:

• maximize visibility into the migration process
• optimize participation from the business
• ensure business ownership of the data.