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Many companies spend a lot of money, time and effort to build a data warehouse and OLAP cubes, however they start using them to build the same old 2D reports that they were used to from the past. The standard 2D canned reports (Rows and Columns) can be built from any conventional relational database by writing some standard SQL queries. So why use an OLAP (On Line Analytic Processing) cube for such reports? The OLAP cubes can handle large amount of data and can bring the results to you instantaneously and it is pre-aggregated. They are designed and built using de-normalized dimensional models optimized for faster data retrieval and reporting. They can hold all the data coming out of a data warehouse and they can also aggregate the granular data to many different levels. The big advantage is, the Microsoft SSAS OLAP cube can hold up to 128 dimensions and you can slice and dice the data using all the dimensions you have built into the cube. In addition, you can further slice the data using the hierarchies built within the dimensions. For example; You can slice the data by dimensions like Time, Geography, Product, Employee, and much more. In the Geography dimension you can also further slice the data by Continent, Country, State, County, City and Zip.
Many companies spend a lot of money, time and effort to build a data warehouse and OLAP cubes, however they start using them to build the same old 2D reports that they were used to from the past. The standard 2D canned reports (Rows and Columns) can be built from any conventional relational database by writing some standard SQL queries. So why use an OLAP (On Line Analytic Processing) cube for such reports?
The OLAP cubes can handle large amount of data and can bring the results to you instantaneously and it is pre-aggregated. They are designed and built using de-normalized dimensional models optimized for faster data retrieval and reporting. They can hold all the data coming out of a data warehouse and they can also aggregate the granular data to many different levels. The big advantage is, the Microsoft SSAS OLAP cube can hold up to 128 dimensions and you can slice and dice the data using all the dimensions you have built into the cube. In addition, you can further slice the data using the hierarchies built within the dimensions. For example; You can slice the data by dimensions like Time, Geography, Product, Employee, and much more. In the Geography dimension you can also further slice the data by Continent, Country, State, County, City and Zip.
There are plenty of multi-dimensional analytic tools out there for the business intelligence presentation layer.You could take advantage of such tools to analyze the data coming out of the OLAP cubes and build real business intelligent reporting via dashboards filled with Gauges, Charts, KPIs, Grids, etc. Besides, a cube could also let various executives, managers and analysts in an organization to work independently at different level of data and reporting with added security features as well. Some of tools currently available in the market are Microsoft Performance Point 2010, Panorama, Power Pivot, & Reporting Services
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