Some of the tangibles that also play a role are the BI Semantic Model (BISM) and the “different flavors of analysis” that were introduced originally with SQL Server 2012. Obviously there could be more considerations you should take when making this decision for your organization, but those could differ depending on your organization, team, and other factors. In this series of posts we’re going to be covering 5 main considerations. Source: Petkovic Dusan (2020), Microsoft SQL Server 2019: A Beginner’s Guide, Seventh Edition-McGraw-Hill Education.Have you been or are you currently working on a project where you are trying to determine which flavor of Analysis Services (Tabular or Multidimensional) you should have used or should use? Recently, I was doing a presentation on SSAS Multidimensional best practices and following the presentation one of the attendees asked a very good question, “When it comes to SSAS Tabular versus SSAS Multidimensional how do I know which one to choose?” We discussed some of the various aspects of each one, but during the conversation I realized I needed to put a presentation and ultimately a blog post together on this topic. (See also the section “Data Warehouse Design” in Chapter 22.)ĭevelopment of BI solutions is easier if you use the Multidimensional model rather than a relational model, which is supported by the Tabular model. The former model is easier to use in the case where many dimensions should be modeled. As you already know, BI solutions based on the Multidimensional model are designed using the dimensional model, while for the design of the Tabular model solutions, the ER model is used. If your solution requires complex modeling, choose the Multidimensional model. The reason is that the Tabular model is based upon the relational data model, and the loading of external data for a relational database system is significantly faster than for multidimensional database systems. If your solution has many external data sources that are different in their nature (tables, data files, etc.), the use of the Tabular model is recommended. However, when you enable the writeback process, you can submit data into the cube in the current session, making it instantly visible to other users of the Analysis Services database. This feature is advantageous because when you write data back to a relational database, you have to wait until the cube is processed before the latest data becomes available. NOTE The writeback process writes data back to Analysis Services rather than to the relational database system that provides the raw data. Processing writeback is possible only using the Multidimensional model. This capability is called writeback, and it is the enabling feature behind what-if analysis, forecasting, and financial planning in BI applications that use Analysis Services as the server. (For this reason, the Multidimensional model is recommended for use of Corporate BI solutions, while the Tabular model should be used for Department and Team BI solutions.)Īmong other things, Analysis Services is a tool that can modify the data you are analyzing. The reason is that the Multidimensional model is designed so that the huge volume of data is stored efficiently. If the size of your dataset is extremely large, use the Multidimensional model. DAX is much easier to use and learn than MDX. As you already know, you can use MDX exclusively with the Multidimensional model and DAX with the Tabular model. NOTE One important factor is the use of the programming language. Ability to access many different data sources.The size of the dataset (a set of all data sources).The following list shows the most important factors: Several features can be used to evaluate both of these models. This section helps you to determine when to use the Multidimensional model and when to use the Tabular model.
0 Comments
Leave a Reply. |
Details
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |