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  2. Dimension (data warehouse) - Wikipedia

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

    A junk dimension is a dimension table consisting of attributes that do not belong in the fact table or in any of the existing dimension tables. The nature of these attributes is usually text or various flags, e.g. non-generic comments or just simple yes/no or true/false indicators.

  3. Database model - Wikipedia

    en.wikipedia.org/wiki/Database_model

    The basic data structure of the relational model is the table, where information about a particular entity (say, an employee) is represented in rows (also called tuples) and columns. Thus, the "relation" in "relational database" refers to the various tables in the database; a relation is a set of tuples. The columns enumerate the various ...

  4. Star schema - Wikipedia

    en.wikipedia.org/wiki/Star_schema

    Dimensions can define a wide variety of characteristics, but some of the most common attributes defined by dimension tables include: Time dimension tables describe time at the lowest level of time granularity for which events are recorded in the star schema; Geography dimension tables describe location data, such as country, state, or city ...

  5. Snowflake schema - Wikipedia

    en.wikipedia.org/wiki/Snowflake_schema

    "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle behind snowflaking is normalization of the dimension tables by removing low cardinality attributes and ...

  6. Data warehouse - Wikipedia

    en.wikipedia.org/wiki/Data_warehouse

    The integrated data are then moved to yet another database, often called the data warehouse database, where the data is arranged into hierarchical groups, often called dimensions, and into facts and aggregate facts. The combination of facts and dimensions is sometimes called a star schema. The access layer helps users retrieve data. [5]

  7. Dimensional modeling - Wikipedia

    en.wikipedia.org/wiki/Dimensional_modeling

    The third step in the design process is to define the dimensions of the model. The dimensions must be defined within the grain from the second step of the 4-step process. Dimensions are the foundation of the fact table, and is where the data for the fact table is collected. Typically dimensions are nouns like date, store, inventory etc.

  8. Dimensional fact model - Wikipedia

    en.wikipedia.org/wiki/Dimensional_fact_model

    A dimensional attribute is a property, with a finite domain, of a dimension. Like dimensions, a dimensional attribute is represented by a circle. For instance, a product may be described by its type, category, and brand; a customer may be represented by city and nation. The relationships among the dimensional attributes are expressed by ...

  9. List of column-oriented DBMSes - Wikipedia

    en.wikipedia.org/wiki/List_of_column-oriented_DBMSes

    C-Store: C++ The last release of the original code was in 2006; Vertica a commercial fork, lives on. DuckDB: C++ An embeddable, in-process, column-oriented SQL OLAP RDBMS Databend Rust An elastic and reliable Serverless Data Warehouse InfluxDB: Rust Time series database: Greenplum Database C Support and extensions available from VMware. MapD: C++

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