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extra custom fields

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Post  j Wed Nov 13, 2013 6:14 pm

What is the best way to design data ware house ( star schema) for custom fields
I have multiple data source system which essentially collecting the same information but with a lot of extra fields per system and I need to report those extra fields as well..
I would like to create a central data warehouse contain data from multiple data source ( with conformed dimensions) but at the same time I would like to store extra fields from different data source as well.. what is the best way to design this? Should I create separate fact tables contain only extra fields per data source? and join to the main fact table ( conformed dimensions)….
What is the best way to design stat schema when there are a lot of custom fields from different data sources?

j

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Join date : 2010-05-15

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Post  BoxesAndLines Thu Nov 14, 2013 12:11 pm

Extra custom fields are typically dimension data, think 3rd party demographics, reference data, etc. Integrate this data into your existing facts just like any other dimensional data.
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Post  j Thu Nov 14, 2013 4:02 pm

Thansk..but

Problem is there will be hundreds of extra fields cannot be conformed per each data source..

For example, source 1 and 2 have the same granularity for fact, but each has hundreds of extra fields

source 1

OrderID age gender extracolumn1 extracolumn 2 extracolumn 3..etc


Source 2

Order ID age gender extracolumn5 extracolumn6 extracolumn7..etc


Source 3
----


I don’t want to put them all in one fact table with conformed fields since a lot of them will have null value and the fact table will be very wide…

Is there better way to do sore extra fields specific to each data source?

j

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Post  Mike Honey Thu Nov 14, 2013 8:22 pm

Hi j,

I would build a dimension for Order (with any common attributes, eg age, gender), then mini-dimensions (one for each source). The dimension business key for all these dimensions would be OrderID, and I would ensure that each mini-dimension gets the same surrogate key as the Order dimension. That way you can join directly from the fact to any mini-dimension.

It does sound like the data modelling phase has been skipped and you are building a data-dump / copy of the source system data.  In a successful DW/BI implementation, each attribute is analyzed for relevance & reporting requirements, and then categorized into separate dimensions.  For example, probably age and gender should be attributes of Customer or a similar dimension.

This approach avoids the issue you raised and also avoids wasting human and computer work on extracting, loading and storing data that is never used.

Good luck!
Mike
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Post  BoxesAndLines Thu Nov 14, 2013 9:31 pm

Very well put Mr. Honey.
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Post  j Fri Nov 22, 2013 4:03 pm

Thanks for the reply,
Actually, these are patient data coming from different hospitals. Even though they share the same granularity, each hospital collects a lot of different fields as well as common fields (i.e. age, gender, diagnosis…)
Is it better to create a separate fact table per hospital in relational data warehouse layer and join each fact table in reporting layer by common dimension using view or something in BI reporting layer?
 If I try to combine each data set to one fact , I think it will be really messy and it won't be easy to scale out??? ….What is your suggestion?

j

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