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Datastage Slowly Changing Dimensions
Slowly Changing Dimensions (SCDs) are dimensions that have data that changes slowly, rather than changing on a timebased, regular schedule.
Type 1
The Type 1 methodology overwrites old data with new data, and therefore does not track historical data at all.
Here is an example of a database table that keeps supplier information:
Supplier_Key Supplier_Code Supplier_Name Supplier_State
123 ABC Acme Supply Co CA
In this example, Supplier_Code is the natural key and Supplier_Key is a surrogate key. Technically, the surrogate key is not necessary, since the
table will be unique by the natural key (Supplier_Code). However, the joins will perform better on an integer than on a character string.
Now imagine that this supplier moves their headquarters to Illinois. The updated table would simply overwrite this record:
Supplier_Key Supplier_Code Supplier_Name Supplier_State
123 ABC Acme Supply Co IL
Datastage Implementations – Slowly Changing Dimensions
Basics of SCD
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Type 2
The Type 2 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. With Type 2, we have unlimited history preservation as a new record is inserted each time a change is made.
In the same example, if the supplier moves to Illinois, the table could look like this, with incremented version numbers to indicate the sequence of
changes:
Supplier_Key Supplier_Code Supplier_Name Supplier_State Version
123 ABC Acme Supply Co CA 0
124 ABC Acme Supply Co IL 1
Another popular method for tuple versioning is to add effective date columns.
Supplier_Key Supplier_Code Supplier_Name Supplier_State Start_Date End_Date
123 ABC Acme Supply Co CA 01Jan2000 21Dec2004
124 ABC Acme Supply Co IL 22Dec2004
The null End_Date in row two indicates the current tuple version. In some cases, a standardized surrogate high date (e.g. 99991231) may be used
as an end date, so that the field can be included in an index, and so that nullvalue substitution is not required when querying.
Step 1: Create a datastage job with the below structure
1. Source file that comes from the OLTP sources2. Old dimesion refernce table link3. The SCD stage4. Target Fact Table5. Dimesion Update/Insert link
How to Implement SCD using DataStage 8.1 –SCD stage?
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Figure 1
Step 2: To set up the SCD properties in the SCD stage ,open the stage and access the Fast Path
Figure 2
Step 3: The tab 2 of SCD stage is used specify the purpose of each of the pulled keys from the referenced dimension tables.
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Figure 3
Step 4: Tab 3 is used to provide the seqence generator file/table name which is used to generate the new surrogate keys for the new or latest
dimesion records.These are keys which also get passed to the fact tables for direct load.
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Figure 4
Step 5: The Tab 4 is used to set the properties for configuring the data population logic for the new and old dimension rows. The type of activies
that we can configure as a part of this tab are:
1. Generation the new Surrogate key values to be passed to the dimension and fact table2. Mapping the source columns with the source column3. Setting up of the expired values for the old rows4. Defining the values to mark the current active rows out of multiple type rows
Figure 5
Step 6: Set the derivation logic for the fact as a part of the last tab.
Figure 6
Step 7: Complete the remaining set up, run the job
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mahesh tanpure • 2 years agoArticle gives good understanding of implementation..good job
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