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  2. Dimension (data warehouse) - Wikipedia

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

    As examples, date dimensions can be accurate to year, quarter, month or day and time dimensions can be accurate to hours, minutes or seconds. As a rule of thumb, time of day dimension should only be created if hierarchical groupings are needed or if there are meaningful textual descriptions for periods of time within the day (ex. “evening ...

  3. 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 ).

  4. Early-arriving fact - Wikipedia

    en.wikipedia.org/wiki/Early-arriving_fact

    In the data warehouse practice of extract, transform, load (ETL), an early fact or early-arriving fact, [1] also known as late-arriving dimension or late-arriving data, [2] denotes the detection of a dimensional natural key during fact table source loading, prior to the assignment of a corresponding primary key or surrogate key in the dimension table.

  5. Slowly changing dimension - Wikipedia

    en.wikipedia.org/wiki/Slowly_changing_dimension

    In data management and data warehousing, a slowly changing dimension (SCD) is a dimension that stores data which, while generally stable, may change over time, often in an unpredictable manner. [1] This contrasts with a rapidly changing dimension , such as transactional parameters like customer ID, product ID, quantity, and price, which undergo ...

  6. Database schema - Wikipedia

    en.wikipedia.org/wiki/Database_schema

    The term "schema" refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases). The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database.

  7. MultiDimensional eXpressions - Wikipedia

    en.wikipedia.org/wiki/MultiDimensional_eXpressions

    In this example, the query defines the following result set information The SELECT clause sets the query axes as the Store Sales member of the Measures dimension, and the 2002 and 2003 members of the Date dimension. The FROM clause indicates that the data source is the Sales cube.

  8. Dimensional fact model - Wikipedia

    en.wikipedia.org/wiki/Dimensional_fact_model

    For example, each sale is measured by the number of units sold, the unit price, and the total receipts. A dimension is a property, with a finite domain, that describes an analysis coordinate of the fact. A fact generally has multiple dimensions that define its minimum representation granularity.

  9. Bitemporal modeling - Wikipedia

    en.wikipedia.org/wiki/Bitemporal_Modeling

    MarkLogic introduced bitemporal data support in version 8.0. Time stamps for Valid and System time are stored in JSON or XML documents. [2]XTDB [3] (formerly Crux) is an open source database that indexes documents using an EAV data model and provides point-in-time bitemporal SQL & Datalog queries.