ETL (Extract Transform Load) extract data from the Data Warehouse and populate one or more Data Marts for use by groups of decision makers in the organizations. The Data Marts can be Dimensional (Star Schemas) or relational, depending on how the information is to be used and what “front end” Data Warehousing Tools will be used to present the information.
Each Data Mart can contain different combinations of tables, columns and rows from the Enterprise Data Warehouse. For example, an business unit or user group that doesn’t require a lot of historical data might only need transactions from the current calendar year in the database. The Personnel Department might need to see all details about employees, whereas data such as “salary” or “home address” might not be appropriate for a Data Mart that focuses on Sales.
Why to create Datamart
The following are the reasons to create Datamart:
- To partition data in order to impose access control strategies.
- To speed up the queries by reducing the volume of data to be scanned.
- To segment data into different hardware platforms.
- To structure data in a form suitable for a user access tool.
Typical Data Warehousing Environment
Some Data Mart might need to be refreshed from the Data Warehouse daily, whereas user groups might want refreshes only monthly.
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