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  2. Dimension (data warehouse) - Wikipedia

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

    A time dimension with a grain of seconds in a day will only have 86400 rows. A more or less detailed grain for date/time dimensions can be chosen depending on needs. As examples, date dimensions can be accurate to year, quarter, month or day and time dimensions can be accurate to hours, minutes or seconds.

  3. System time - Wikipedia

    en.wikipedia.org/wiki/System_time

    The following tables illustrate methods for retrieving the system time in various operating ... \> DATE C:\> TIME: 10 ms ... Joda Time, The Joda Date/Time Library (Java)

  4. Online analytical processing - Wikipedia

    en.wikipedia.org/wiki/Online_analytical_processing

    Each measure can be thought of as having a set of labels, or meta-data associated with it. A dimension is what describes these labels; it provides information about the measure. A simple example would be a cube that contains a store's sales as a measure, and Date/Time as a dimension. Each Sale has a Date/Time label that describes more about ...

  5. 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.

  6. Fact table - Wikipedia

    en.wikipedia.org/wiki/Fact_table

    The fact table also contains foreign keys from the dimension tables, where time series (e.g. dates) and other dimensions (e.g. store location, salesperson, product) are stored. All foreign keys between fact and dimension tables should be surrogate keys, not reused keys from operational data.

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    mail.aol.com

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  8. Time series database - Wikipedia

    en.wikipedia.org/wiki/Time_series_database

    Time series datasets can also have fewer relationships between data entries in different tables and don't require indefinite storage of entries. [6] The unique properties of time series datasets mean that time series databases can provide significant improvements in storage space and performance over general purpose databases. [ 6 ]

  9. Bitemporal modeling - Wikipedia

    en.wikipedia.org/wiki/Bitemporal_Modeling

    Bitemporal modeling is a specific case of temporal database information modeling technique designed to handle historical data along two different timelines. [1] This makes it possible to rewind the information to "as it actually was" in combination with "as it was recorded" at some point in time.