Matillion × Landkreditt
Matillion x Landkreditt, 30x processing gain on a decade-old data warehouse
30x performance improvement in data processing
Hitting the performance ceiling to running a modern, scalable data platform
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Why it works
The case study anchors to three concrete, customer-specific numbers (4x, 30x, 50%) that are clearly tied to the migration outcome rather than vendor-wide claims. The mechanism is explained in enough operational detail (control tables, generic jobs with variables, Python scripts, Azure DevOps pipelines) that a data engineering team could attempt a similar approach. The secondary New Capability thread is genuine: nine years of historical data that was previously excluded is now accessible, which the team describes as enabling analytics that were not possible before.
Steal this
Name the internal platform. Landkreditt branded their data platform DAIRY and unpacked the acronym, which turns an abstract infrastructure story into a memorable internal product launch. That framing gives the case study a concrete protagonist beyond the vendor and makes the transformation feel owned by the customer.
Click to enlarge ↗ This is editorial commentary and curation. The case study, screenshot, and all metrics are Matillion's published work; we link to the source and lead with our analysis.