![]() Power BI uses DAX to query both tabular and multidimensional models.īecause DAX is primarily designed for tabular models, there are some interesting and useful mappings, and constraints, that must be understood when using DAX against multidimensional models. While DAX is considered easier to use, it's also more focused on simpler data visualizations like tables, charts, and maps in reports and dashboards. DAX, however, was originally designed for tabular data models. Beginning with SQL Server 2012 SP1, Analysis Services supports using both DAX and MDX against multidimensional and tabular models. MDX is optimized for common visual patterns like PivotTables in Excel and other reporting applications that target multidimensional business semantics. Historically, reporting applications use MDX (Multidimensional Expressions) as a query language against multidimensional databases. Also note that Tabular will only work if there is sufficient memory for the entire cube in memory, otherwise you won’t be able to open the database.This article describes how Power BI uses DAX (Data Analysis Expressions) queries to report against multidimensional models in SQL Server Analysis Services. You can always just build a tabular cube to allow for the use of Power View. Say you built a multidimensional model before tabular was released, but now want to use Power View. Keep in mind the option on creating both types of models against the same data warehouse. how many new distinct customers this month), tabular is better because it stores data in a way that discount count is very fast (writing a measure vs changing the data model and reprocessing the data) ![]() In situations where a multidimensional model requires a distinct count (i.e. quantity totals by day), tabular is better because it can avoid snapshots by making up-to-date calculations at query time (thanks to its speed because the data is in memory) In situations where a multidimensional model requires the use of snapshots (i.e. Instead it requires a much faster “Process Recalc” You can extend the data model without reprocessing the whole database by using calculated columns. It’s less expensive to use in terms of time, resources and skill requirement It uses xVelocity/Vertipaq, which is much faster than Multidimensional ![]() It uses DAX, which is much easier to use than MDX, and least for the basics (but mastering DAX and optimizing DAX is hard) It uses your existing relational model, so there is usually no need to create a star schema (which usually means using ETL to create new dimension and fact tables in a Data Mart or Data Warehouse). I would recommend going with Tabular if possible, as it is better to use for these reasons: If you need any of the following features, you must use Multidimensional: Actions, Custom Assemblies, Custom Rollups, Custom Drillthrough Actions (but BIDS Helper adds support for actions in a PivotTable in Excel but not in PerformancePoint), Linked objects, or Translations.If your solution requires complex modeling, choose Multidimensional.If you need Many-to-Many relationships, choose Multidimensional (can be done in Tabular but difficult).If you need extreme speed and consistently fast query time, choose Tabular.If you need complex calculations, scoping, and named sets, choose Multidimensional.If you need access to many different external data sources, choose Tabular. ![]() If you need writeback support, you have to use Multidimensional.If your dataset is extremely large, go with Multidimensional.If you want to use Power View, you have to use Tabular.If you want to use DAX, you have to use Tabular.Well, there is no clear-cut answer, but there are some factors that can make you choose one over the other: Which model should you use, Multidimensional vs Tabular?
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