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  2. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    The snowflake schema is in the same family as the star schema logical model. In fact, the star schema is considered a special case of the snowflake schema. The snowflake schema provides some advantages over the star schema in certain situations, including: Some OLAP multidimensional database modeling tools are optimized for snowflake schemas. [3]

  3. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    The star schema is an important special case of the snowflake schema, and is more effective for handling simpler queries. [2] The star schema gets its name from the physical model's [3] resemblance to a star shape with a fact table at its center and the dimension tables surrounding it representing the star's points.

  4. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    A transactional table is the most basic and fundamental. The grain associated with a transactional fact table is usually specified as "one row per line in a transaction", e.g., every line on a receipt. Typically a transactional fact table holds data of the most detailed level, causing it to have a great number of dimensions associated with it.

  5. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    The dimensional model is built on a star-like schema or snowflake schema, with dimensions surrounding the fact table. [3] [4] To build the schema, the following design model is used: Choose the business process; Declare the grain; Identify the dimensions; Identify the fact; Choose the business process

  6. Slowly changing dimension - Wikipedia

    en.wikipedia.org/wiki/Slowly_changing_dimension

    The outrigger attributes should have distinct column names, like “Current Income Level,” to differentiate them from attributes in the mini-dimension linked to the fact table. The ETL team must update/overwrite the type 1 mini-dimension reference whenever the current mini-dimension changes over time.

  7. Codd's 12 rules - Wikipedia

    en.wikipedia.org/wiki/Codd's_12_rules

    All information in a relational data base is represented explicitly at the logical level and in exactly one way – by values in tables. Rule 2: The guaranteed access rule : Each and every datum (atomic value) in a relational data base is guaranteed to be logically accessible by resorting to a combination of table name, primary key value and ...

  8. Standard column family - Wikipedia

    en.wikipedia.org/wiki/Standard_column_family

    Each column is a tuple consisting of a column name, a value, and a timestamp. [2] In a relational database table, this data would be grouped together within a table with other non-related data. [3] Standard column families are column containers sorted by their names can be referenced and sorted by their row key. [4]

  9. Column family - Wikipedia

    en.wikipedia.org/wiki/Column_family

    In analogy with relational databases, a column family is as a "table", each key-value pair being a "row". Each column is a tuple consisting of a column name, a value, and a timestamp. In a relational database table, this data would be grouped together within a table with other non-related data. Two types of column families exist: