Impact Analysis – “Hawk Eyes” of SAS Data Integration Studio
Harsh Gajjar is SAS Business Intelligence (BI) and SAS Design Integration (DI) rising star in India. Today he is discussing how to use the SAS DI Studio Impact Analysis feature.
As we have observed majorly in large enterprises, particularly the Banking and Finance sectors, there is always a huge amount of data building up every day. Moreover, one cannot ignore the fact that every observation in the database is linked up or important in some or the other way. So if you need to make a change to a data table, you need to understand the impact of that decision on your downstream data and reports. Currently, I will be focusing on the chief enhancement of Impact Analysis in data integration.
Analyze your Data Impact
Here, I am showing the application of Data Integration in enterprises and the advantage of Impact Analysis in SAS Data Integration (DI) Studio. SAS DI Studio offers the ability of creating jobs, which can be used to populate various tables and creation of analytical reports. SAS DI Studio is an end-to-end solution in creation of the data warehouse.
SAS Data Integration Studio User’s Guide describes impact analysis like this:
“Impact analysis identifies the tables, columns, jobs, and transformations that are affected by a change to a selected table or column. Reverse impact analysis identifies the tables, columns, jobs, and transformations that contribute to the content of a selected table or column. Use impact analysis before changing or deleting a Meta data object, to see how that change can affect other objects. Use reverse impact analysis to trace the source data that contributes to the content of a selected table or column.”
Scenario Based Illustration
We have created various jobs in order to create surplus tables and report’s based on the Customer’s Order Information. Now I want to know what happens if I change or delete the metadata of a source table. Basically, I want to know the impact or the change that will be result due to such modification’s in my source table. Here the data and snapshot presented are examples taken from SAS DI User’s Guide.
So here I just right-click the Orders (Foundation) Fact Table and click on Analyze, which brings up the following window.
Now on viewing, the Impact Analysis you can clearly observe that the Orders table is connected to many jobs and the metadata is being used in building up various target tables and reports. Thus, one can understand that a change in the metadata of the source table will impact the following jobs and target tables.
There are 2 views available here: one (as shown above) and the second one is below. This view gives you a diagrammatic view of the linkup’s where the metadata of the order table is used.
I like this view since it gives an end-to-end analysis of impact on change in the source table. Apart from that, it also shows the contents of the table through Contents tab.
This is one of the best enhancements of SAS Data Integration; I observe it is a major advantage for huge enterprises since they have large customer’s, sales, products, policies datasets that are so ever changing data. Changes can be clearly observed before running jobs on such huge amount of data like changing the default account number’s, changing the product code, deleting observation coming up in certain period, etc.. In such situations, this can be a boon for a SAS DI Programmer since they can scrutinize the outcome due to changes in the source tables.
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