Consolidating data using datamarts

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ETL extracts data from several sources, transforms the data to meet business needs using certain business rules, and finally loads (writes) data into a target system.When starting with a Data Warehouse, you’ll typically use ETL to get data directly from source systems to the Data Warehouse, and then from the Data Warehouse to Data Marts as needed.Many shops experience database spread -- the existence of far too many databases, often with redundant data, and often for very discrete needs.In these shops, databases are often built relatively quickly to expedite projects and applications.

Wrap Up Due to time constraints and resources, it usually makes sense for all but the most established enterprises to start with Data Marts and develop a Data Warehouse over time.

Architectural Details Most databases are normalized, which means they are optimized for faster transaction times, such as adding or deleting data.

Normalization works by reorganizing data so that it contains no redundant data and separating related data into tables with joins between tables that specify relationships.

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When an enterprise takes its first major steps towards implementing Business Intelligence (BI) strategies and technologies, one of the first things that needs clarifying is the difference between a Data Mart vs. Understanding this difference dictates your approach to BI architecture and data-driven […] " When an enterprise takes its first major steps towards implementing Business Intelligence (BI) strategies and technologies, one of the first things that needs clarifying is the difference between a Data Mart vs. Understanding this difference dictates your approach to BI architecture and data-driven decision making.

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