What this chapter covers
Data as an asset and the data value chain. From the relational database (tables, keys, SQL) to the data warehouse, the data lake and the lakehouse. Data quality, master data and data governance. Business Intelligence and reporting. Corporate Performance Management: planning, budgeting, forecasting, consolidation, KPIs and scorecards, and how CPM closes the loop with the ERP. Descriptive, diagnostic, predictive and prescriptive analytics.
What changes with AI
Conversational BI, the semantic layer, continuous forecasting, and four checks before trusting a number produced by AI.
Seen in class
- Conversational BI on a fictitious company's data warehouse: the same questions answered by a dashboard and by an AI assistant that chooses among curated queries, with the queries it ran shown on screen.
- The analytics simulation, in groups (see the Simulation page).
Materials and practice
SlidesAvailable after class
HandoutAvailable after class
Self-CheckQuiz and exam practiceExerciseA worked case with solutionSimulationThe lab of this chapter