2 Replies Latest reply: Jul 27, 2014 3:15 PM by Ahsan Shah RSS

    Logic Behind OBIA Facts

    user1417283

      We are implementing OBIA HR, Student Information, Finance, and Procurement Analytics with PeopleSoft as a source.  It seems there are many things that we are expected to know rather than to have them documented.

       

      First we are implementing HR, and only Workforce Deployment, hoping that would be a mature product (we tried the new Student product with too many initial problems).  We have gotten the initial load to run.  The first dashboard has the most important stat: Headcount.  This is central to all of Workforce Deployment, and to HR analytics.

       

      But how is it calculated?  There is no documentation about the logic employed, only a one-sentence definition typed into the Fact property.  Using this definition, we are unable to figure out the headcount we get.

       

      It seems that we are supposed to reverse engineer the ETLs to find out how this works, but that is time consuming and risky (if we don't catch everything) and for a supposedly out-of-the-box solution, should be unnecessary.

      I would appreciate any input to help point us in the right direction.

        • 1. Re: Logic Behind OBIA Facts
          Srini VEERAVALLI

          Check Lineage doc for that module, you may find links from cool-bi.com

          • 2. Re: Logic Behind OBIA Facts
            Ahsan Shah

            There is no Guide or DOC thats spells this out for you, lineage guide wont help you.  My recommendations are as following:

             

            1.  Try to understand the general logic of all OBIA facts...there is a SDE extract, SIL, and PLP process.  This applies to all areas, not just HR

            2.  Understand the grain of the FACT table in question.  For instance, for HR, there is a MONTHLY (W_WRKFC_EVT_MONTH_F) fact table that aggregates yoour headcounts, HR events, at the MONTHLY level.  Also, there are various types of transactions in this table incluing EVENTS, JOBs, etc.  This is fed from a more granular fact such as W_WRKFC_EVT_F table.  Its possible these are using CSV file lookups, etc that you configure. 

            3.  Once you understand the target Facts, you can then go to the other SDE mappings to understand how they go from Sourse-> staging.  For example, you will see the SQL calculating the baseline logic.

             

            The docs can help give a general idea but you have to do this type of analysis to really understand the logic. 

             

            if helpful, mark correct