from ODS to Dimensions

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from ODS to Dimensions

Post  jon on Sun Sep 11, 2011 7:10 pm

I have a database with 30 tables storing snapshot of daily summaries. These summaries have different metric info. For example, say it is tracking metrics of 10 brick and mortal banks, it will store the info of 10 stores on a daily basis, regardless if the store opens on Sun or not.

As you can imagine, data grows very fast. On days that the bank has no activities, database tables will be keep a copy of the metrics any way. therefore, all historical information are stored. there is no plan to change this process of ODS.

What I would like to know is if there is any tips and examples on designing dimensional model based on this type of ODS.



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Re: from ODS to Dimensions

Post  KS_EDW on Thu Sep 15, 2011 11:25 pm

I’d think that daily snapshots of 30 locations would grow relatively slow @ a 30 rows per day rate? Is there more granular data you’d be receiving, such as receipts, line items, etc.?

Whatever the case, from what you’ve posted… I’d say you’ll be good to treat the data as normal transactions with a grain of date and location. You could build out an indicator in the fact to show that the operation was open/closed on a particular day… or stop the “closed” rows in the ETL. None the less… it sounds like business as usual from a dimensional modeling perspective.

Hope this helps.

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