- Avoid duplication/redundancy of data
- Minimize space requirements
- Enable fast retrieval and updates of these transactions
This is because aggregation is being done on the fly for each query, and combined with the additional filters (WHERE clauses), quickly starts eating up our SQL Server resources. Not only are the reports slow, but other business users experience significant system slowdowns as well.
A Data Warehouse (DW) on the other hand, which is part of an Online Analytical Processing (OLAP) system, is built for one purpose alone - fast, efficient reporting.
In a DW system, data from the OLTP system will be read, de-normalized, and (typically) stored in a Star Schema, as a set of Dimension and Fact tables. This is often done using SQL Server Integration Services (SSIS). From these tables, tools within SQL Server Analysis Services (SSAS) can be used to build cubes, which contain not only our data but also its pre-calculated aggregates based upon definitions that we specify within SSAS. This results in many advantages:
- Super-fast reporting
- No impact on the OLTP system
- Data Mining (DM) and Business Intelligence (BI) solutions can be readily built
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