A data mart is a subset of a data warehouse oriented to a specific business line. Data marts contain repositories of summarized data collected for analysis on a specific section or unit within an organization, for example, the sales department.
A data warehouse is a large centralized repository of data that contains information from many sources within an organization. The collated data is used to guide business decisions through analysis, reporting, and data mining tools.
Data Mart
Focus: A single subject or functional organization area
Data Sources: Relatively few sources linked to one line of business
Size: Less than 100 GB
Normalization: No preference between a normalized and denormalized structure
Decision Types: Tactical decisions pertaining to particular business lines and ways of doing things
Cost: Typically from $10,000 upwards
Setup Time: 3-6 months
Data Held: Typically summarized data
Data Warehouse
Focus: Enterprise-wide repository of disparate data sources
Data Sources: Many external and internal sources from different areas of an organization
Size: 100 GB minimum but often in the range of terabytes for large organizations
Normalization: Modern warehouses are mostly denormalized for quicker data querying and read performance
Decision Types: Strategic decisions that affect the entire enterprise
Cost: Varies but often greater than $100,000; for cloud solutions costs can be dramatically lower as organizations pay per use
Setup Time: At least a year for on-premise warehouses; cloud data warehouses are much quicker to set up
Data Held: Raw data, metadata, and summary data