Insurance Data Migration
A procedure for planning and executing the transfer of data between systems, storage environments, or formats while maintaining data integrity, completeness, and security.
Purpose
To ensure that data is migrated accurately and completely from a source system to a target system with minimal disruption to business operations and no loss of data integrity.
Scope
Covers all planned data migration activities including system upgrades, platform changes, consolidations, and archive migrations across all business systems and databases.
Prerequisites
- Detailed data mapping document between source and target systems
- Data quality assessment of the source data
- Migration tools and scripts prepared and tested
- Rollback plan in case the migration is unsuccessful
Aligns with ASIC regulatory requirements, General Insurance Code of Practice, and AFSL obligations. Includes audit trail provisions.
Step-by-Step Procedure
Plan the Migration
Define the migration scope, approach, timeline, and responsibilities. Prepare the detailed migration plan.
- 1.1Define the data sets to be migrated and the migration sequence
- 1.2Determine the migration approach such as big bang or phased
- 1.3Prepare the migration timeline with milestones and contingency time
- 1.4Identify and assign migration team roles and responsibilities
Prepare Data Mapping and Transformation Rules
Document how data fields in the source system correspond to fields in the target system, including any required transformations.
- 2.1Map each source data field to the corresponding target field
- 2.2Define data transformation and cleansing rules
- 2.3Identify data that requires manual handling or review
Cleanse Source Data
Review and clean the source data to resolve quality issues before migration, preventing the transfer of inaccurate or incomplete data.
- 3.1Run data quality checks on the source data
- 3.2Identify and resolve duplicate, incomplete, or inconsistent records
- 3.3Obtain business sign-off on data cleansing decisions
Perform Trial Migration
Execute a trial migration using a subset of data to validate the migration scripts, mapping, and transformation rules.
- 4.1Run the migration scripts against a test data set
- 4.2Verify that data is transferred correctly and completely
- 4.3Test data transformations and check for errors
- Run at least two trial migrations to build confidence in the process
Execute Production Migration
Perform the actual data migration during the approved change window, following the migration plan step by step.
- 5.1Freeze changes to the source system during the migration window
- 5.2Execute the migration scripts according to the plan
- 5.3Monitor progress and address any errors in real time
Validate Migrated Data
Verify that all data has been migrated correctly and completely by running validation checks and comparing source and target data.
- 6.1Run record count comparisons between source and target
- 6.2Perform sample data verification by comparing individual records
- 6.3Validate data integrity checks such as totals, checksums, and referential integrity
Obtain Business Sign-Off
Have the business data owners verify and sign off that the migrated data is correct and the target system is ready for use.
- 7.1Present validation results to the data owners
- 7.2Have data owners perform user acceptance testing on the migrated data
- 7.3Obtain formal sign-off confirming migration success
Decommission Source and Close
Once the migration is confirmed successful, decommission the source system if appropriate and close the migration claim.
- 8.1Archive the source system data for the required retention period
- 8.2Decommission the source system when no longer needed
- 8.3Document lessons learned and close the migration claim
Quality Checkpoints
Common Mistakes to Avoid
Expected Outcomes
Percentage of records migrated without errors, measuring the quality of the migration.
Total system downtime during the migration, measuring the impact on business operations.
Frequently Asked Questions
What is a big bang migration versus a phased migration?
A big bang migration moves all data at once during a single cutover window. A phased migration moves data in stages over time. Big bang is faster but higher risk, while phased migration reduces risk but requires managing parallel systems.
How long does a data migration typically take?
Duration varies greatly depending on data volume, complexity, and the number of systems involved. Simple migrations may take hours, while complex enterprise migrations may take weeks including planning, testing, and execution.
What happens if the migration fails?
If the migration fails, the rollback plan is executed to restore the source system to its pre-migration state. The root cause of the failure is investigated and resolved before reattempting the migration.
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