This means the measures are not strongly typed and can have different data types. Measures in multidimensional models are variants. Power BI can show display folders and the measures and KPIs in them. To help simplify more complex multidimensional models, model authors can define a set of measures or KPIs in a cube to be located within a display folder. If there are calculated measures that do not have an associated measure group, they're be grouped under a special table called Measures. Measures within a measure group appear as measures. Measure groups in a multidimensional cube are shown in the Power BI Fields list as tables with a calculator icon. Measure group cube dimension relationship This mapping is exposed to Power BI by using the DISCOVER_CSDL_METADATA schema rowset. Objects in a multidimensional models are then represented as tabular objects in Power BI. Multidimensional to tabular object mappingĪnalysis Services provides a tabular model metadata representation of a multidimensional model. To learn more about syntax for individual functions, see the DAX function reference. The syntax of DAX formulas is very similar to that of Excel formulas, and uses a combination of functions, operators, and values. DAX expressions cannot be used where an MDX expression is required and vice-versa, and some DAX functions, like PATH, are not applicable in multidimensional modeling at all. A DAX query to a multidimensional model can reference a measure or other calculation that is defined in that model, but those calculations must be authored using the MDX language. You cannot use measures created by a DAX expression in a multidimensional model. Interaction between MDX and DAXĭAX expressions are supported only within tabular models. This article describes how DAX queries work against a multidimensional model. In addition to being a calculation language, DAX can also be used to execute queries. DAX is also used to create custom measures, calculated columns, and row-level security rules. In tabular models, DAX is used against a relational data store comprised of tables and relationships. DAX was initially designed to be similar to the Excel formula language. SQL Server 2012 and SQL Server 2014 Enterprise or Business Intelligence editions are also supported, however, these versions are now out of mainstream support. Power BI uses DAX to query Analysis Services multidimensional models in SQL Server 2016 and later Enterprise or Standard editions. 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. This article describes how Power BI uses DAX (Data Analysis Expressions) queries to report against multidimensional models in SQL Server Analysis Services.

Tabular and multidimensional models