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Database table

As explained in Effective Data Analysis

A table is a structured data collection arranged in rows representing records and columns representing attributes.

A database table is a logically organized set of tabular data: each row is a record, and each column contains information about that record. In a data warehouse, tables bring together information collected from different sources and give analysts data to query. section 1.2.2

Tables sit alongside views, which hold curated query results, and schemas, which organize tables. Making tables useful can involve joining relevant data, providing join keys, and correcting inconsistent data types. section 1.2.2 section 11.3.1

Historical weather data

A tourism company stores daily weather records by zip code so they can connect with existing data. A date_saved field preserves forecast history, while a most_recent field helps operational teams find the latest forecast. section 11.3.1

How Effective Data Analysis covers it

How deep it goes
Defines rows and columns, then illustrates practical querying and table-structuring considerations.
Examples
Uses a city-population table for state totals and a weather table for daily forecasts, retention, and joins.
What you can do after
Apply SQL to group table records by state and calculate summed population.
How it connects
Links tables with data warehouses, schemas, views, SQL queries, join keys, and ETL workflows.

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This explainer was generated by Manning's knowledge graph from the text of Effective Data Analysis. The section links point to the parts of the book it draws on.