But when you start working in a multi-dimensional environment, you need to stop thinking from a two-dimensional (relational database) perspective, which will develop over time. When you start learning SSAS, you should have a reasonable relational database background. Browse the cube data using Excel as the client tool.Develop calculated measures and named sets using MDX.Create dimensions, hierarchies, and cubes.
Snapseed Version 2.0 Brings New Filters, Tools, Non-Destructive Editing, and More. In this tutorial we will step through a number of topics that you need to understand in order to successfully create a basic cube. Snapseed Gets New Photo Filters and a Facelift. Sales could then be analyzed using any of these hierarchies for effective data analysis.Ī typical higher level cube development process using SSAS involves the following steps:Ģ) Configuring a schema in BIDS (Business Intelligence Development Studio)ģ) Creating dimensions, measures and cubes from this schemaĤ) Fine tuning the cube as per the requirements Time can also have its own hierarchy like Year->Semester->Quarter. Geography can also have its own hierarchy like Country->City->State. You can think of this data as a pivot table where geography is the column-axis and years is the row axis, and sales can be seen as the values. A typical analysis could be to analyze sales in Asia-pacific geography during the past 5 years. Simple examples of dimensions can be product / geography / time / customer, and similar simple examples of facts can be orders / sales. Multi-dimensional expression (MDX) is the query language used to query a cube, similar to the way T-SQL is used to query a table in SQL Server. These details are generally stored in a pre-aggregated proprietary format and users can analyze huge amounts of data and slice this data by dimensions very easily. From a relational perspective dimensions can be thought of as master tables and facts can be thought of as measureable details. In simple terms, you can use SSAS to create cubes using data from data marts / data warehouse for deeper and faster data analysis.Ĭubes are multi-dimensional data sources which have dimensions and facts (also known as measures) as its basic constituents. SQL Server Analysis Services (SSAS) is the technology from the Microsoft Business Intelligence stack, to develop Online Analytical Processing (OLAP) solutions.