An Online Analytical Process (OLAP) cube is a powerful analytical tool that is optimized for reporting purposes. In this article, we will explore the concept of OLAP cubes and how they can be implemented using SQL Server Analysis Services (SSAS).

What is an OLAP Cube?

An OLAP cube is a multi-dimensional database that allows for efficient analysis of large datasets. It consists of measures, which are the core elements of the dimensional model, and dimensions, which provide referenced information for detailed analysis of the measures.

Creating an OLAP Cube

To create an OLAP cube in SQL Server, we need to start by defining the data source and data source view. The data source view includes the necessary fact and dimension tables from the database.

Once the data source view is defined, we can start creating the OLAP cube. The cube creation process involves selecting the measures columns and choosing the required dimensions. It is important to choose only the necessary measure columns to avoid delays in cube processing.

Adding Attributes and Hierarchies

After the basic configuration of the OLAP cube is completed, we need to add attributes to the dimensions. These attributes provide additional details for analysis. It is essential to add only the required attributes to avoid negative impacts on cube processing and accessing.

In addition to attributes, hierarchies can be created to enhance data analysis. Hierarchies allow users to drill down into the data and analyze it at different levels of granularity.

Accessing the OLAP Cube

Once the OLAP cube is processed, it is ready to be accessed. There are multiple ways to access the processed cubes, including using SQL Server Data Tools, Excel pivot tables, SSRS, PowerBI, and SSMS.

Using Excel pivot tables, business users can leverage the features of Excel to perform ad-hoc analysis on the cube data. They can select dimensions as columns or rows and use hierarchies for more effective analysis.

MDX queries, a special type of query language, can also be used to retrieve data from OLAP cubes. This provides more flexibility in querying and analyzing the cube data.

Conclusion

OLAP cubes are a powerful tool for analyzing large datasets in SQL Server. By creating multi-dimensional databases optimized for reporting purposes, users can efficiently analyze data and gain valuable insights. In this article, we covered the basics of OLAP cube implementation using SQL Server Analysis Services. There are additional advanced features in cubes that can be explored in separate articles.