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  2. Power Query - Wikipedia

    en.wikipedia.org/wiki/Power_Query

    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# programming language, and according to Microsoft it is a "mostly pure, higher-order, dynamically typed, partially lazy, functional language."

  3. Microsoft Power BI - Wikipedia

    en.wikipedia.org/wiki/Microsoft_Power_BI

    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 ]

  4. Dimension (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Dimension_(data_warehouse)

    A slowly changing dimension is a set of data attributes that change slowly over a period of time rather than changing regularly e.g. address or name. These attributes can change over a period of time and that will get combined as a slowly changing dimension. These dimension can be classified in types: [3]

  5. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    Single data (fact) table surrounded by multiple descriptive (dimension) tables Developers often don't normalize dimensions due to several reasons: [5] Normalization makes the data structure more complex; Performance can be slower, due to the many joins between tables; The space savings are minimal; Bitmap indexes can't be used; Query performance.

  6. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    Fact_Sales is the fact table and there are three dimension tables Dim_Date, Dim_Store and Dim_Product. Each dimension table has a primary key on its Id column, relating to one of the columns (viewed as rows in the example schema) of the Fact_Sales table's three-column (compound) primary key (Date_Id, Store_Id, Product_Id).

  7. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    Example of a star schema; the central table is the fact table. In data warehousing, a fact table consists of the measurements, metrics or facts of a business process. It is located at the center of a star schema or a snowflake schema surrounded by dimension tables. Where multiple fact tables are used, these are arranged as a fact constellation ...

  8. Measure (data warehouse) - Wikipedia

    en.wikipedia.org/wiki/Measure_(data_warehouse)

    In a data warehouse, a measure is a property on which calculations (e.g., sum, count, average, minimum, maximum) can be made. A measure can either be categorical, algebraic or holistic. A measure can either be categorical, algebraic or holistic.

  9. Change data capture - Wikipedia

    en.wikipedia.org/wiki/Change_data_capture

    A current version is maintained for the table, or possibly a group of tables. This is stored in a supporting construct such as a reference table. When a change capture occurs, all data with the latest version number is considered to have changed. Once the change capture is complete, the reference table is updated with a new version number.