SSAS 2012 2008 Introduction to SQL Server Analysis Services for beginners and scenarios to use SSAS 

1. SSAS 2012 is the technology that is provided by SQL Server to create cubes. 
2. Organizations use cubes to manage large volumes of data so that complex queries can be retrieved in a more efficient manner than if the queries were to be executed against a relational database. 
3. With cubes, there is also the ability to preaggregate data and store them in the cube for faster retrieval of summary information.
4. The most underused aspect of SSAS is data mining that enables a business to perform trend analysis and identify relationships between data that may not be immediately apparent to end users when looking at the data. 
5. Analysis Services is a fantastic tool that can host the data in a central point as information
6. SQL Server Analysis Services provides the ability to efficiently query multidimensional data. It also provides the capability to use data mining to extrapolate trends and patterns within data. 
7. There are core components that you should be aware of to create a cube.
8. At its core, data sources must be defined to provide connection information to the source data for the cube. You can then define data source views to define the specific tables on which the cube is based. This will typically involve dimension tables and fact tables from a data warehouse.
9. You can then define dimensions within the cube against dimension tables within the data warehouse. The dimensions will provide contextual information and act as the axis for the cube. For improved readability, you can also define hierarchies to allow the user to drill down into the dimension data.
10. On completing the creation of the dimensions, we can then run the cube wizard to create the cube. The wizard allows you to create a cube using existing dimensions or from data from a table. 
11. You can also create an empty cube if you do not have the data available. Once the cube is created, you can configure cube partitions. This enables you to spread the data over multiple physical disks to improve the performance of cube processing and querying data in the cube. 
12. SQL Server Analysis Services also provides additional OLAP objects to extend the functionality of the cube, including calculated members, KPIs, actions and translations.
13. For data mining, you can use new or existing data sources and data source views to point to the source data. The source data for data mining can be an existing cube or data from a table or a view. 
14. You can then create a data mining structure that integrates the source data with a data mining algorithm, known as a data mining model in order to find patterns in the data using the data mining model. On completing this, you have the ability to view and validate the results that are returned back to the data mining viewer.