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Fact table

A fact table is an analytical database table that records measurable events or processes through quantitative measures and references to related dimensions.

How 2 Manning books explain it

Effective Data Analysis

A fact table is a tabular structure that records measurable events or processes, typically with numeric measures and references to dimensions.

How it is used
Structures business events for efficient analytical queries within star schemas.
How deep it goes
Explains definitions, modeling criteria, relationships, and design questions, but stops short of a complete implementation.
Examples
Uses sales transactions, page views, clicks, customer activities, and normalized-schema redesign exercises as examples.
What you can do after
Practice/perform by identifying event tables, proposing fact and dimension tables, mapping their keys, and drawing a star schema.

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Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI

An event table stores records of business events measured at particular moments.

How it is used
Organizes time-specific business events as the analytical foundation of normalized warehouse data.
How deep it goes
Defines the table type and contrasts related tables, but stops short of schema design or detailed implementation.
Examples
Uses e-commerce orders, banking transactions, healthcare visits, and internet clickstreams as event examples.
What you can do after
Apply the concept by identifying event records and assembling them with related tables for analysis.

Read how Machine Learning for Tabular Data: XGBoost, Deep Learning, and AI explains fact table →

Related concepts

These guides are generated from the text of Manning books by Manning's knowledge graph and link to the sections they draw on. The full books are available on liveBook and at manning.com.