In some dimension, we may find that we don't have any dimension attributes but only its business key. Transaction Number is an example, other transaction header's attributes are logically organized in other dimensions. (e.g. Transaction date is organized to Date dimension) It doesn't make sense to create a tiny dimension with just the surrogate key and business key. So, we may consider to degenerate the dimension and store the business key (e.g. transaction number) in the fact table. Size and the content nature would be the way of our consideration (e.g. we degenerate the invoice number but not the invoice remarks). We call such a degenerated field in the fact table as the degenerated dimension.
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Extract: Performance Tips
Below listed some common performance tips for extract queries. Extract required columns only and specify in the query, avoid select * Extrac...
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Extract is the first step in the ETL process which obtains data from the source systems. This is our first question. How much data we need t...
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If we are using dimensional data model, make sure to build atomic grain base fact tables. It is true that they takes more space and performs...
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Below listed some common performance tips for extract queries. Extract required columns only and specify in the query, avoid select * Extrac...
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