Datafold’s AI-powered data migration with automated end-to-end data validation

Data migrations have long been expensive, long, and manual projects for data teams, lasting months or even years (we speak from experience). Since the beginning of the Unix epoch, or maybe even for longer, rewriting legacy SQL, stored procedures, and GUI-based transformations into modern frameworks and conducting manual parity checks has been a tedious and unscalable process.

Last year, Datafold solved this problem with Datafold Migration Agent, an autonomous AI-agent that automatically translates code from legacy systems and validates data parity using Datafold’s proprietary data diffing technology.

Now, we’re extending this approach. DMA now kicks off migrations by automatically validating parity between upstream inputs of legacy vs new databases, to ensure apples-to-apples comparisons of outputs.

This further accelerate migrations to a degree previously thought impossible.

Automated End-to-End Data Validation

Before DMA translates and validates your new SQL code, Datafold ensures that the inputs into your translation pipeline match exactly. To do this, we create a frozen version of the input datasets in both the legacy and new system, and ensure they match exactly—no mismatched values, no missing or added rows.

We call this the DMA Source Aligner.

This allows us to check the work of DMA by automatically running cross-database data diff across your entire production dataset—without any manual effort from your team.

Data teams can now save hundreds of hours on manual data testing and guarantee 100% parity across databases, or full visibility into any unresolvable discrepancies.

DMA provides an audit log of migration success. It is the only tool to both automate code conversion and validate that the data migration is complete because both inputs and outputs match across systems.

Not only will DMA provide accurate new code, it will also provide the full evidence that the code and data in the new system is 100% correct. Specifically, end-to-end automatic data diffing supports:

• Zero manual validation, at scale: DMA now automatically verifies every record across both legacy and new databases to ensure accuracy, without having data teams waste time creating cross-database comparisons for every migrated table.
• Lowers migration risks: With DMA’s AI fine-tuning itself until accuracy is met and parity is 100%, DMA is not only accelerating migration timelines massively, but lowering the risk of inaccurate data in the new system.
• Faster time-to-production: With end-to-end value-level comparisons done automatically by DMA, data teams also have auditable comparisons between systems to earn stakeholder sign-off faster.

Ultimately, data teams reduce weeks or months of manual validation to accelerate migrations with confidence and evidence.

The future of data migrations

DMA continues to set the standard for how data teams undergo migrations at unmatched speed without compromising data quality.

In a world where innovating on data has never been more important, data teams no longer have to make the tradeoff between innovation and migrations with AI-powered code translation and end-to-end automatic data diffs.

If your team is interested in learning more about how DMA can de-risk and accelerate your migration with 100% automated accuracy, please book some time with our team to learn more.