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Is the warehouse the reason the AI pilot stalled?
By Debjani Dhar, Co-founder and CEO · Published · 4 minutes read
The short answer
Often, yes, and the sign is specific. The model worked on a sample, then stalled when someone asked whether its numbers matched the reports finance already trusts. Nobody could answer, because the logic that produces those reports lives in stored procedures and packages nobody has documented. Count the estate, move one domain, prove it, and the AI program gets numbers finance trusts.
Often, yes, and the sign is specific. The model worked on a sample, then stalled when someone asked whether its numbers matched the reports finance already trusts. Nobody could answer, because the logic that produces those reports lives in stored procedures and packages nobody has documented.
How do you know whether the warehouse is the blocker?
If the answers are “not really”, “nobody knows” and “no”, the pilot is waiting on the migration, not on the model.
- Can anyone say, object by object, which procedures produce the numbers the pilot uses?
- If the pilot needs those numbers on a modern platform, how many objects would move, and who understands them?
- Could you prove the moved numbers match the old ones?
What should you do this quarter?
Count the estate. The assessment takes three business days, costs $3,000, and gives you the object count, the complexity, the dead code and a fixed price. Then move one domain and prove it. The AI program gets numbers finance trusts, on a platform its agents can operate.
Next question: what do we tell the board next week?
Key terms
- Logic debt
- the business logic locked in legacy stored procedures, ETL packages, views and schedules, much of it undocumented; the share of technical debt that lives in data logic.
- Estate assessment
- every object counted and banded by complexity, with lineage, dead code and a fixed price, in three business days for $3,000, credited.
FAQ
Frequently asked questions
Legacy data warehouse blocking AI adoption: what does that mean?
It means the numbers an AI program needs are produced by legacy logic that cannot yet be moved, explained or proven. The data is reachable; the procedures and packages that compute it are not documented, and nobody can show their output would match on a new platform. The fix is to count that logic, move it by rule and prove each object.
What do we tell the board next week?
The assessment date, and that a fixed price and timeline follow three business days after it. The assessment counts every object, so the number you bring back is the estate's, not an estimate.
Is Novuz an AI tool?
No. Novuz is a rule-based conversion engine: a semantic parser, an inference layer and a versioned rules library convert about 95% of objects with no model calls. The resolver uses a model only to propose edge-case fixes, and an engineer approves each one.
Sources
- Novuz, the board's AI deadline (novuz.com/rescue/board-ai-deadline)
- Novuz, is our data ready for AI (novuz.com/blog/is-our-data-ready-for-ai)
About the author
Debjani Dhar is co-founder and CEO of Novuz Inc., the deterministic data warehouse modernization company based in Danville, California. She previously led application modernization programs at Accenture.
Next step
The Novuz estate assessment counts every object, finds the dead code and gives you a fixed price in three business days, for $3,000, credited. It is the number the board is asking for.
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