If there are retroactive changes made to the contents of the dimension, or if new attributes are added to the dimension (for example a Sales_Rep column) which have different effective dates from those already defined, then this can result in the existing transactions needing to be updated to reflect the new situation. To reference the entity via the natural key, it is necessary to remove the unique constraint making referential integrity by DBMS impossible. the state the supplier was in at the time of the transaction no update is needed. An aggregate table summarizing facts by supplier state continues to reflect the historical state, i.e. Transactions that reference a particular surrogate key (Supplier_Key) are then permanently bound to the time slices defined by that row of the slowly changing dimension table. The Current_Flag value of 'Y' indicates the current tuple version. ) may instead be used as an end date, so that the field can be included in an index, and so that null-value substitution is not required when querying.Īnd a third method uses an effective date and a current flag. The null End_Date in row two indicates the current tuple version. The Start date/time of the second row is equal to the End date/time of the previous row. Unlimited history is preserved for each insert.įor example, if the supplier relocates to Illinois the version numbers will be incremented sequentially:Īnother method is to add 'effective date' columns. This method tracks historical data by creating multiple records for a given natural key in the dimensional tables with separate surrogate keys and/or different version numbers. If one has calculated an aggregate table summarizing facts by supplier state, it will need to be recalculated when the Supplier_State is changed. It has the advantage however that it's easy to maintain. The disadvantage of the Type 1 method is that there is no history in the data warehouse. If the supplier relocates the headquarters to Illinois the record would be overwritten: Technically, the surrogate key is not necessary, since the row will be unique by the natural key (Supplier_Code). In the above example, Supplier_Code is the natural key and Supplier_Key is a surrogate key. This method overwrites old with new data, and therefore does not track historical data. Type 0 applies to most date dimension attributes. Examples: Date of Birth, Original Credit Score. The Type 0 dimension attributes never change and are assigned to attributes that have durable values or are described as 'Original'. Type 6 SCDs are also sometimes called Hybrid SCDs. ĭealing with these issues involves SCD management methodologies referred to as Type 0 through 6. For historical sales reporting purposes it may be necessary to keep a record of the fact that a particular sales person had been assigned to a particular regional office at an earlier date, whereas that sales person is now assigned to a different regional office. However, the salespeople are sometimes transferred from one regional office to another. One of these dimensions may contain data about the company's salespeople: e.g., the regional offices in which they work. This fact table would be linked to dimensions by means of foreign keys. Some scenarios can cause referential integrity problems.įor example, a database may contain a fact table that stores sales records. Some examples of typical slowly changing dimensions are entities such as names of geographical locations, customers, or products. JSTOR ( March 2015) ( Learn how and when to remove this template message)Ī slowly changing dimension ( SCD) in data management and data warehousing is a dimension which contains relatively static data which can change slowly but unpredictably, rather than according to a regular schedule.Unsourced material may be challenged and removed.įind sources: "Slowly changing dimension" – news Please help improve this article by adding citations to reliable sources in this article. This article needs additional citations for verification.
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