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raccourcis clavier

The Problem

Stakeholders ask what happened but engineers hand them raw tables — how do you turn warehouse data into decisions?

Formal Definition

Per Wikipedia: “Business Intelligence is the layer of dashboards, KPIs and self-service queries that sit on top of a warehouse for decision making.”

Explanation

BI is the dashboard of a car — warehouse is the engine, but driver only sees speed and fuel on the dials.

How It Works

  1. Define KPIs like CLV and RFM
  2. Model marts for reporting
  3. Build dashboards in BI tool
  4. Schedule refresh via automation
  5. Share insights with stakeholders

Visual Explanation

business_intelligence A Warehouse B BI Layer A->B step 1 C Decision B->C step 2

Semantic Network

semantic_business_intelligence THIS Business Intelligence REL1 Related THIS--REL1 related REL2 Prereq THIS--REL2 builds from

Key Properties

  • Self-service reduces ticket load
  • Needs governance on metric definitions
  • Drill-down needs good dimensional model

Real-World Example

SELECT rfm_segment, COUNT(*) FROM mart GROUP BY 1

Connections

Edge Cases & Gotchas

  • Vanity metrics — tracking visits not conversion
  • Dashboard sprawl — 50 dashboards nobody opens