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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.
Analysis Services includes a group of OLAP and data mining capabilities and comes in two flavors multidimensional and tabular, where the difference between the two is how the data is presented. [citation needed] In a tabular model, the information is arranged in two-dimensional tables which can thus be more readable for a human. A ...
It is available as an add-in in Excel 2010, as a separate download for Excel 2013, and is included by default since Excel 2016. The data modelling engine inside Power Pivot is shared across Microsoft Power BI and SQL Server Analysis Server (SSAS), and may be referred to as xVelocity, VertiPaq, SSAS Tabular, and Power Pivot. [1]
Paginated reports for Power BI, which can be built with Power BI Report Builder, are a special type of SSRS reports with pagination formatting which can give better control of the layout of reports which need to be printed to paper or PDF. This is in contrast to regular Power BI reports which instead are optimized for presentation or ...
Tableau Software, LLC is an American interactive data visualization software company focused on business intelligence. [2] [3] It was founded in 2003 in Mountain View, California, and is currently headquartered in Seattle, Washington. [4]
Microsoft Dynamics 365 is an integrated suite of enterprise resource planning (ERP) and customer relationship management (CRM) applications offered by Microsoft. [1] Combines various functions such as sales, customer service, field service, operations, finance, marketing, and project service automation into a single platform.
[1] [2] [3] Automated activities can include data profiling or data visualization or tabular reports to give the analyst an initial view into the data and an understanding of key characteristics. [1] This is often followed by manual drill-down or filtering of the data to identify anomalies or patterns identified through the automated actions.
Data vault modeling was originally conceived by Dan Linstedt in the 1990s and was released in 2000 as a public domain modeling method. In a series of five articles in The Data Administration Newsletter the basic rules of the Data Vault method are expanded and explained.