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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.
SQL Server has limitations on row size if attempting to change the storage format of a column: the total contents of all atomic-datatype columns, sparse and non-sparse, in a row that contain data cannot exceed 8016 bytes if that table contains a sparse column for the data to be automatically copied over.
XLeratorDB uses Microsoft SQL CLR(Common Language Runtime) technology. [7] SQL CLR allows managed code to be hosted by, and run in, the Microsoft SQL Server environment. SQL CLR relies on the creation, deployment and registration of .NET Framework assemblies that are physically stored in managed code dynamic-link libraries
A pivot table usually consists of row, column and data (or fact) fields. In this case, the column is ship date, the row is region and the data we would like to see is (sum of) units. These fields allow several kinds of aggregations, including: sum, average, standard deviation, count, etc.
Power Pivot can scale to process very large datasets in memory, which allows users to analyze datasets that would otherwise surpass Excel's limit of one million rows. [9] Power Pivot allows for importing data from multiple sources, such as databases (SQL Server, Microsoft Access, etc.), OData data feeds, Excel files, and other sources ...
Row-oriented benefits from fast insertion of a new row. Column-oriented benefits from fast insertion of a new column. This dimension is an important reason why row-oriented formats are more commonly used in Online transaction processing (OLTP), as it results in faster transactions in comparison to column-oriented.
Common operations include slice and dice, drill down, roll up, and pivot. OLAP slicing Slice is the act of picking a rectangular subset of a cube by choosing a single value for one of its dimensions, creating a new cube with one fewer dimension. [ 5 ]
All attributes (columns) are optional unless an explicit requirement is issued to require such. Type validation can also optionally be added this way. This allows a table to incremental grow more rigid, closer to a regular RDBMS table. With some minor adjustments, SQL or a variation could the query language to make it familiar to users.