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Asher Bill
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what is the difference between a data warehouse and a data mart?

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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