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DATA WAREHOUSING
Multi Dimensional
Data Modeling.
Fact Table Types
2
   Transaction
         Track processes at discrete points in time when they
          occur
       Periodic snapshot
         is a fact table that records activity during a repeating
          predictable time period, like the monthly summary of
          a bank account
       Accumulating snapshot
         A snapshot of the most recent state of something and
          therefore the dimensional foreign keys and the facts
          are, in general, over-written as time progresses

3
   Transaction-grained fact tables are often
        richly dimensional and usually have only a
        single fact (the amount of the transaction).




4
   Periodic snapshot records are generally
        repeated each reporting period as long as the
        thing being measured (like the account) is in
        existence.




5
   Periodic snapshots are appropriate for long
        running processes that extend over many
        reporting periods.




6
   Accumulating
    snapshots, are
    used for short
    processes that
    have a definite
    beginning and end,
    such as an order
    being filled.

7
   For an order, we would usually make a record
        for each line on the order, and we would
        revisit the record making updates as the
        order progressed through the pipeline




8
   The simplest implementation of an
        accumulating snapshot does not give you
        intermediate points in the history of, for
        example, an order.




9
   Accumulating snapshots typically have
     multiple dates in the fact table representing
     the major milestones of the process.
     However, just because a fact table has several
     dates doesn’t dictate that it is an
     accumulating snapshot.
      The primary differentiator of an accumulating
      snapshot is that we typically revisit the fact rows
      as activity takes place.
10
Dw design fact_tables_types_6
Dw design fact_tables_types_6
   The Data Warehouse Toolkit.Second
    Edition.The Complete Guide to Dimensional
    Modeling.Ralph Kimball.Margy Ross

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Dw design fact_tables_types_6

  • 1. DATA WAREHOUSING Multi Dimensional Data Modeling. Fact Table Types
  • 2. 2
  • 3. Transaction  Track processes at discrete points in time when they occur  Periodic snapshot  is a fact table that records activity during a repeating predictable time period, like the monthly summary of a bank account  Accumulating snapshot  A snapshot of the most recent state of something and therefore the dimensional foreign keys and the facts are, in general, over-written as time progresses 3
  • 4. Transaction-grained fact tables are often richly dimensional and usually have only a single fact (the amount of the transaction). 4
  • 5. Periodic snapshot records are generally repeated each reporting period as long as the thing being measured (like the account) is in existence. 5
  • 6. Periodic snapshots are appropriate for long running processes that extend over many reporting periods. 6
  • 7. Accumulating snapshots, are used for short processes that have a definite beginning and end, such as an order being filled. 7
  • 8. For an order, we would usually make a record for each line on the order, and we would revisit the record making updates as the order progressed through the pipeline 8
  • 9. The simplest implementation of an accumulating snapshot does not give you intermediate points in the history of, for example, an order. 9
  • 10. Accumulating snapshots typically have multiple dates in the fact table representing the major milestones of the process. However, just because a fact table has several dates doesn’t dictate that it is an accumulating snapshot.  The primary differentiator of an accumulating snapshot is that we typically revisit the fact rows as activity takes place. 10
  • 13. The Data Warehouse Toolkit.Second Edition.The Complete Guide to Dimensional Modeling.Ralph Kimball.Margy Ross