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  2. Data Analysis Expressions - Wikipedia

    en.wikipedia.org/wiki/Data_Analysis_eXpressions

    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.

  3. Azure Data Explorer - Wikipedia

    en.wikipedia.org/wiki/Azure_Data_Explorer

    It supports complex analytics query operators, such as calculated columns, searching and filtering on rows, group by-aggregates and joins. [ 25 ] The engine service exposes a relational data model : At the top level ( cluster ) there is a collection of databases, each database contains a collection of tables and stored functions.

  4. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    Extensibility. Dimensional models are scalable and easily accommodate unexpected new data. Existing tables can be changed in place either by simply adding new data rows into the table or executing SQL alter table commands. No queries or applications that sit on top of the data warehouse need to be reprogrammed to accommodate changes.

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  7. Dashboard (computing) - Wikipedia

    en.wikipedia.org/wiki/Dashboard_(computing)

    Power BI can be used to display trends over time. For example, a company can create a time plot that shows its costs and revenues over a certain period. The data can then be arranged to show per day, month, quarter, year, etc. This requires simple formatting tools so the data can quickly be changed and compared. Power BI allows the user to ...

  8. Table (database) - Wikipedia

    en.wikipedia.org/wiki/Table_(database)

    In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]

  9. In-memory processing - Wikipedia

    en.wikipedia.org/wiki/In-memory_processing

    Another drawback is that SQL is designed to efficiently fetch rows of data, while BI queries usually involve fetching of partial rows of data involving heavy calculations. To improve query performance, multidimensional databases or OLAP cubes - also called multidimensional online analytical processing (MOLAP) - may be constructed.