The whole premise of Analysis Services (SSAS) is to place business logic into a central repository (a database). This central repository should be easy to understand from the average reporting user. Simplicity for SSAS databases starts with the Dimension and Fact tables in a data mart or data warehouse. These tables need to have as little additional computed columns as necessary. With this design, adding additional Measures to the SSAS database, both Multidimensional Cubes, and Tabular Models, can help with performance monitoring of the company’s indicators.

Introduction

I am a DBA consultant and several times, in the past, I have been asked for a good tool to generate fast reports to get information about the company like total sales, sales per year, month, week, etc

SSAS is a Business Intelligence (BI) technology that Microsoft bought from Panorama Software in 1996. After the acquisition, the technology was upgraded and evolved and now it is part of the tools that come with SQL Server. This tool is an extremely powerful tool to create analytical reports fast. It works with cubes that are designed to generate reports with optimal performance using aggregated information stored in the cube.

In this article, a demonstration of the tabular model will try to related multidimensional cube design to the path forward Microsoft is giving used s with new versions of Analysis Services. Even though the descriptive names are changing, the tabular model still accomplishes the centralized business rules multidimensional cubes gave the business intelligence world. This is enforced by speed obtained from in-memory technology and simplification of the interface for the masses.

In Data Warehouse language, slicing and dicing is done with Dimension Attributes. Sometime a developer feels the need to provide everything to end users, whereas seasoned Business Intelligence Architects understand to provide only the attributes from the requirements. It is a hard path to follow and the seasoned architect’s experience might be the better option.

Connecting to tables in SQL Server Analysis Service (SSAS) databases is easy. Maybe too easy. The learning curve for developing in a Multidimensional Cube is steep, although a Tabular Model has lessened this curve. The power of encapsulating the business logic of aggregations and analytics into an Analysis Service database is too great not to embrace Analysis Services in an enterprise environment.

In the previous article, Analysis Services (SSAS) Multidimensional Design Tips – Data Source View and Cubes, we discussed best practices for SSAS Multidimensional cubes and data source views. In this article, we continue the series with design tips for creating dimensions as the subject. As with the previous article, most tips are suited for SSAS 2008 (most likely 2005 as well) to 2016 and later versions. Analysis Services Tabular is not covered in this article.

In this article, we’ll discuss some tips and best practices regarding the design of OLAP cubes in Analysis Services Multidimensional (SSAS). Most tips – if not all – are applicable for SSAS 2008 to 2016 (and later most likely). Since Analysis Services Tabular – the in-memory columnstore OLAP database from Microsoft – is a completely different design experience, it will not be included in this article.

For someone new to SQL Server Analysis Services, a decision must be made on whether to use a Multidimensional Cube or Tabular Model. Both types can be installed on the same server, but they must be different instances. That could mean additional license costs. But, with the developer’s edition, both can be installed and reviewed before a production decision is made. Data Source connections are the first step to review with both versions.