When measuring Key Performance Indicators (KPIs) of Business Processes, the size of the data warehouse you are creating are surprisingly tiny when compared to data warehouses that store sales data.
In that sense, they are very similar to data warehouses that store Financial Data and allow you to slice and dice that data, whether they be income or expenses.
In data warehouses that store Point of Sales (POS) systems data, they are dealing with tens of thousands of SKUs and thousands of stores or outlets. The sales data that is generated in just one day could easily run into gigabytes. This is what builds up to terabytes of data over longer periods like a quarter or a year.
Unlike Sales Data, Process KPI data may be tiny in size. Each Business Process has usually about 20 to 25 KPIs per day or per shift. Some processes depend upon the number of people execute that process - like Agents handling Customer Service or Support calls on the phone. Mostly, they are summarized information that get rolled up divisions or departments.
Process KPI data when collected may run into a few gigabytes a month when compared to hundreds and thiousands of gigabytes for Sales data.
So when we call for a Process Datawarehouse as compared to a Sales Datawarehouse, they are very similar in the kinds of slcing and dicing reports that they may provide. But the backend data supporting them may be an order of magnitude smaller.
This also means that you need less powerful processors and disk space for storing all this data. You can implement many of these kinds of Process Datawarehouses with off-the-shelf reasonably inexpensive deskop or rackmounted low end servers!
All the more reason, that for business critical processes, collecting process KPI data and using them for Continuous Process Improvement becomes compelling!
It's not the size of the dog in the fight, it's the size of the fight in the dog. - Mark Twain
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