Data foundations: glossary
The building blocks of where data lives and how it moves: warehouses, pipelines, schemas, keys and models.
- Data WarehouseA data warehouse is a central database designed for reporting and analysis, which collects cleaned data from many source systems in one place.
- Data LakeA data lake is a storage area that holds large amounts of raw data, structured or not, in its original format until someone needs it.
- Data MartA data mart is a smaller, focused slice of a data warehouse built for one team or subject, such as sales or finance.
- ETL (Extract, Transform, Load)ETL is the process of extracting data from source systems, transforming it into a clean, consistent shape, and loading it into a destination such as a warehouse.
- ELT (Extract, Load, Transform)ELT loads raw data into the warehouse first and transforms it there afterwards, using the warehouse's own processing power.
- Data PipelineA data pipeline is an automated series of steps that moves data from one or more sources to a destination, often cleaning it along the way.
- Database SchemaA database schema describes how a database is organised: its tables, their columns and data types, and how the tables relate to each other.
- Primary KeyA primary key is a column, or a set of columns, whose value uniquely identifies each row in a table.
- Foreign KeyA foreign key is a column in one table that refers to the primary key of another table, linking their rows together.
- Database NormalizationNormalization is the practice of organising tables so that each fact is stored in one place, which avoids repetition and inconsistent updates.
- Star SchemaA star schema is a way of modelling data for analysis, with a central fact table of events surrounded by dimension tables that describe them.
- Fact TableA fact table stores the measurable events of a business, one row per event, such as a sale, a click or a shipment.
- Dimension TableA dimension table holds the descriptive attributes of the things in your facts, such as customers, products, locations or dates.
- OLAP (Online Analytical Processing)OLAP describes systems and queries built for analysis: scanning and summarising large amounts of historical data across many dimensions.
- OLTP (Online Transaction Processing)OLTP describes systems that record day-to-day transactions quickly and reliably, such as taking an order or updating a balance.
- Data ModelingData modeling is the process of deciding how data is structured: which tables exist, what each row represents and how the tables connect.