Data dictionary
A data dictionary is a structured reference documenting data elements and their meanings, types, formats, constraints, permitted values, and related metadata.
The Well-Grounded Data Analyst
A data dictionary is structured documentation describing a dataset's fields, meanings, formats, and permissible values.
- How it is used
- Frames initial dataset inspection and guides later exploration, transformation, and analysis choices.
- How deep it goes
- Explains practical reading, schema verification, and dictionary creation, without defining a formal documentation standard.
- Examples
- Uses customer addresses, purchases, events, surveys, traffic counts, property transactions, and mobile events as documented datasets.
- What you can do after
- Evaluate/understand a dataset’s fields, test its documented assumptions, and create documentation when none is supplied.
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100 SQL Server Mistakes and How to Avoid Them
A data dictionary is a document describing data attributes, their meanings, rules, example values, types, dependencies, and lineage.
- How it is used
- Documents attribute meaning and rules to support normalization without false assumptions.
- How deep it goes
- Lists dictionary fields and illustrates lineage, without prescribing a fixed template or tool.
- Examples
- Traces a cookie identifier from an impressions CSV through staging into a marketing schema.
- What you can do after
- Build it from scratch in a spreadsheet by recording attribute metadata and lineage.
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Effective Data Analysis
A data dictionary is documentation that defines a dataset’s fields, data types, valid response options, and related descriptive information.
- How it is used
- Decodes survey datasets so analysts can select and interpret variables for comparisons tailored to organizational questions.
- How deep it goes
- Defines fields, types, responses, and response percentages but does not provide a detailed analysis workflow.
- Examples
- Uses General Social Survey and Monitoring the Future files distributed as CSV, STATA, or SPSS-compatible datasets.
- What you can do after
- Evaluate/understand survey variables well enough to compare populations and investigate differences in important characteristics.
Starting Data Analytics with Generative AI and Python
A data dictionary is a reference that describes a dataset's variables, types, scales, meanings, codes, and transformations.
- How it is used
- Uses variable metadata to test whether proposed research questions are answerable and to prevent missing requirements from halting analysis.
- How deep it goes
- Defines the metadata to record but stops short of prescribing a detailed dictionary format or implementation workflow.
- Examples
- Uses continuous, ordinal, and nominal variables, interval and ratio scales, and documented coding or transformations.
- What you can do after
- Evaluate whether available data supports particular research questions before designing the analytics process.
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AI for Everyday IT
A data dictionary is a structured reference describing the objects, columns, data types, and other metadata in a data system.
- How it is used
- Supports accurate AI-generated queries against unfamiliar application databases and monitoring schemas.
- How deep it goes
- Defines schema context and prompt inputs, but stops short of independently validating generated SQL or guaranteeing correct results.
- Examples
- Uses Commvault metadata and an Oracle memory-configuration view with sample rows and conversion queries.
- What you can do after
- Diagnose database configurations by prompting for queries grounded in supplied schemas, then reviewing the resulting SQL.
Related concepts
- datasetpart of · A dataset is an organized collection of related data items, records, or observations treated as a unit for storage, processing, analysis, or computation.
- CSVhas part · CSV is a plain-text format for tabular data, representing records as rows and fields as values separated by delimiters, conventionally commas, with quoting conventions for special content.
- SQLuses · SQL is a standardized declarative language for defining, querying, and manipulating data and structures in relational database systems.
- read_csvconfigures · read_csv is a function that parses comma-separated or otherwise delimited text into a tabular data structure.
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