Glossary
The terms you will hear during a data project, explained simply
- Certified dataset
- A dataset that is documented, checked and approved by its data owner, and serves as the reference for reports and AI
- Certified report
- A reference report built only on certified datasets and approved through a certification cycle
- Conversational BI
- Querying your data in natural language and getting figures as answers, based on documented semantic models
- Data catalogue
- The inventory of your data: what it means, where it comes from, who is accountable for it and how to use it
- Data dictionary
- The detail of every table and every column: name, description, format, rules and examples
- Data owner
- The business leader accountable for a data domain. They approve definitions, set the rules and settle disagreements
- Data platform
- The infrastructure that collects, stores and prepares your data for BI and AI, for example Microsoft Fabric, Databricks or Snowflake
- Data quality
- Data that is accurate, complete, up to date and consistent from one team to the next, measured by rules and thresholds
- Data steward
- The data owner’s operational relay. They document the data, monitor quality and fix discrepancies day to day
- Governed self-service BI
- A model where business teams build their own analyses, on a certified foundation and under shared rules
- Master data
- The data shared across the whole company: customers, products, suppliers, sites. One version, managed once
- Semantic model
- The layer that turns your technical tables into business concepts, with the definitions and calculation rules of your indicators
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