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Your Data is Bad - Does it matter if you know in 3 hours or 3 Minutes ?

These days every discussions in analytic and business intelligence areas eventually end up with "speed of analysis". Since SAP introduced HANA - the buzzword is about speed, real time, near real time dashboards. Everybody wants to talk about a cloud application - so they can get up & running with applications tomorrow, and if its deployed on HANA - more than happy since they get it faster. So CIO can start getting his dashboard from next week, every time he looks at it - its just near real time. Isn't it faster ROI ? Gone are the days when it used to take few months to get systems up and running, 3 hours everyday to get those BI reports and tune those dashboards where "Go Live" was a big event.

The only question remains - When CIO looks at that new dashboard created in 3 minutes rather than 3 hours - how much time does it take to tell you that your data in the system is bad.  No surprise here.

Last week I was talking to a procurement executive from a reputed media company. They are going through this peculiar problem of "defining taxonomy" to address their dynamic business transactions - a photographer takes a photo of Brad Pitt taking coffee on the NY street and comes to them - gets paid $2000 and goes away. No PO, No Supplier, probably just a invoice with a gibberish - "Brad Pitt Photo" and a money paid. Now if that happens everyday with a fast social media, digitized world where you need to be the first one to get hold and publish it - you don't care about the "Process". Result - Bad Data. When a CIO - CFO looks at the "spend analysis" dashboard - which tells them there are "Other" category transactions which accounts for 28% of spend - guess a reaction.

Not to say - speed of analysis is less important, but as the title of this blog suggests - priority is important. If your data is bad - doesn't matter if you get analysis in 3 hours or 3 minutes time. If your data is good - anyway it doesn't matter 3 hrs or 3 minutes, since you know where to fix the problem already. Important part is - DATA Quality

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