Home Datastage Related Datastage Training Big Data Unix Database Interview Related Certifications Discussion Forum Feedback Many thanks for visiting my Blog..!!Please share this blog using Tweet 0 0 Share 1 4 Share This Blog..!! 0 Like S 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 Search SEARCH YOUR PROBLEMS SOLUTION IN THIS BLOG Select Language ▼ TRANSLATE THIS BLOG VISITOR'S VIEW COUNT 8 0 6 2 5 9 Log In Devendra Kumar Yadav 181 followers Follow ABOUT ME : CLICK ON G+ BUTTON TO FOLLOW ME OTHER DATASTAGE QUESTIONS SOLUTIONS 1 More Next Blog» Create Blog Sign In
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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:
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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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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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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