Audit and Reconciliation in Data Migration: Hopp’s Approach
Data migration is never just about moving data from point A to point B.
It’s about ensuring that what arrives at the destination is accurate, complete, and trustworthy.
This is where audit and reconciliation come into play: critical processes that validate the integrity of migrated data and provide stakeholders with confidence.
The diagram shows Hopp’s audit and reconciliation process: Source Data flows through the Migration Engine to Target Data. Audit Data Collection occurs during migration and feeds into the Audit Results Interface.
External reconciliation processes validate the final outcome against business expectations.
Why Audit and Reconciliation Matter
In simple migrations, reconciliation might mean comparing counts: “If x minus y equals z, everything is fine.” But in complex migrations, where data is transformed, merged, split, or enriched, this simplistic approach falls short.
Business rules, legacy structures, and transformation logic introduce complexity that makes one-to-one comparisons impossible.
The Challenge
- Transformations Change Everything: Duplicate customers may be merged, products redefined, or portfolios split. These changes mean the target data often looks very different from the source.
- Data Quality Risks: Transformations can correct errors but also introduce new inconsistencies, making validation harder.
- Legacy Complexity: Old systems with intricate dependencies require careful mapping and planning.
Traditional reconciliation approaches often involve duplicating transformation logic to align expected results with migrated data.
Hopp strongly advises against this.
Why? Because duplicating logic doubles the effort and risk, errors in both sets of rules can mask serious issues.
Hopp’s Take on Audit and Reconciliation
Hopp is built for complex data migrations, where extensive transformations are the norm.
Our philosophy is simple:
- Expose, Don’t Duplicate: Instead of replicating transformation logic, Hopp provides audit interfaces that capture the actual results of migration.
- Audit Data Collection: As each business object is migrated, Hopp collects audit data documenting the input and output of the migration engine. This includes full data lineage, enabling clear visibility into what changed and why.
- Runtime Integration: Audit data is stored alongside business objects in the Hopp Runtime, ensuring consistency even when objects are re-iterated.
- Audit Result Interface: Operators can trigger an audit job from the portal to retrieve all collected audit data for reconciliation against external expectations.
This approach bridges the gap between business expectations and migration results without redundant transformations. It’s efficient, transparent, and reduces risk.