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Data Analysis Expressions (DAX) is the native formula and query language for Microsoft PowerPivot, Power BI Desktop and SQL Server Analysis Services (SSAS) Tabular models. DAX includes some of the functions that are used in Excel formulas with additional functions that are designed to work with relational data and perform dynamic aggregation .
Power Query is built on what was then [when?] a new query language called M.It is a mashup language (hence the letter M) designed to create queries that mix together data. It is similar to the F Sharp programming language, and according to Microsoft it is a "mostly pure, higher-order, dynamically typed, partially lazy, functional language."
DAX expressions allow a user to create calculated columns and measures to summarize and aggregate large quantities of data. Queries in the model are reduced to xmSQL, a pseudo-SQL language in the storage engines that drive the data model. [11] A companion feature to Power Pivot named Power Query may be used to perform ETL processes prior to ...
Multidimensional Expressions (MDX) is a query language for online analytical processing (OLAP) using a database management system. Much like SQL, it is a query language for OLAP cubes. [1] It is also a calculation language, with syntax similar to spreadsheet formulae.
The first release of Power BI was based on the Microsoft Excel-based add-ins: Power Query, Power Pivot and Power View. With time, Microsoft also added many additional features like question and answers, enterprise-level data connectivity, and security options via Power BI Gateways. [ 10 ]
In tableau software, data blending is a technique to combine data from multiple data sources in the data visualization. [17] A key differentiator is the granularity of the data join. When blending data into a single data set, this would use a SQL database join , which would usually join at the most granular level, using an ID field where ...
The Nested Set model is appropriate where the tree element and one or two attributes are the only data, but is a poor choice when more complex relational data exists for the elements in the tree. Given an arbitrary starting depth for a category of 'Vehicles' and a child of 'Cars' with a child of 'Mercedes', a foreign key table relationship must ...
Views can represent a subset of the data contained in a table. Consequently, a view can limit the degree of exposure of the underlying tables to the outer world: a given user may have permission to query the view, while denied access to the rest of the base table. [2] Views can join and simplify multiple tables into a single virtual table. [2]