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Making Sense Of Data

For several years now, data analytics has been a big part of any gig I have been a part of. Some themes recur across a lot of large companies I've worked for - there is a lot data floating around, the linkages between different data sets is often weak if not altogether missing and finally there is no single version of the truth. What makes things even more interesting is that powers that be will want to mine this data cesspool for business intelligence they can act on to gain competitive advantage. By now, we are asking for the impossible and yet somehow we pretend that it is possible to deliver on it.

There is a strong tendency to gloss over systemic issues around data quality and jump right into analysis, predictive modeling and such. When I read about Trimetric, my first thought was to kick the tires with some of the data I deal with day to day - data that is often not as clean as it needs to be to arrive at consistent conclusions. Maybe it can actually do as it says it can - "help you make sense of data". Maybe I will find out or learn something about the data that I don't know yet. Whatever, the outcome in my specific case, the idea of Trimetric is an excellent one.
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