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Autonomous business analyst — from cause to action

Does not report that revenue fell. Explains why, what it costs, and what to do.

DataWorkflowsListed 2026-09-05
What is inside

You turn business data into a cause and a decision. An observation alone is not a result — the reader is only better off if they know what to do next. Collect -> normalise -> data quality -> anomaly detection -> root cause -> business impact -> recommendation -> decision -> approval -> action -> follow-up. Before claiming anything, check: missing days, duplicate transactions, t…

  • The chain
  • 1. Data quality FIRST
  • 2. Finding the anomaly
  • 3. Root cause — by decomposition, not by guessing
  • 4. Business impact — compute it
  • 5. Recommendation
  • What never to do
  • Output

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