The data-discovery fallacy
Doug, you hit the nail on the head when you say "Organizations have to realize that arming everybody with tools ... won't necessarily unleash a wave of data-driven decisions or, more importantly, correct decisions."
The current cry of "everyone is an analyst these days", is very wide of the mark.
Data-discovery is a key BI technology, and in the hands of experts and power users adds huge value in organization, However simply passing on the same tools to operational end users (who make up the vast majority of an organization) is neither productive or advisable.
Data can help almost everyone in an organization do a better, more productive job. However, expecting them to dig for it themselves is the wrong way to go about it.
I always fall back to two questions :-
1) What do you want your sales teams doing a) selling or b) analysing data ?I have yet to hear the answer "b".
2) When you want a weather forecast (which is a big data, predictive problem) what do you do a) get one with a couple of clicks from a no-training-required web site or b) fire up your data-discovery tool and point it at your weather data lake? Again I have never hears the answer "b" (except from meteorologists, but they are the analysts in this version of the story)
A lot of this comes back to the hi-jacking of the term "self-service". I would (strongly) argue that getting a weather forecast from your favourite web site is self-service information delivery, but there is no hint of a self-service BI tool in sight.
In fact, if you think about it, self-service in everyday life means the opposite to what it does in BI. After all if you go to a self-service restaurant, you are not shown into the kitchen to cook your food, instead you choose from a convenient selection of pre-prepared offerings.
BI teams have a lot to learn about end-user BI from the fast food industry :-)
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2/9/2015 | 12:56:46 PM
The current cry of "everyone is an analyst these days", is very wide of the mark.
Data-discovery is a key BI technology, and in the hands of experts and power users adds huge value in organization, However simply passing on the same tools to operational end users (who make up the vast majority of an organization) is neither productive or advisable.
Data can help almost everyone in an organization do a better, more productive job. However, expecting them to dig for it themselves is the wrong way to go about it.
I always fall back to two questions :-
1) What do you want your sales teams doing a) selling or b) analysing data ?I have yet to hear the answer "b".
2) When you want a weather forecast (which is a big data, predictive problem) what do you do a) get one with a couple of clicks from a no-training-required web site or b) fire up your data-discovery tool and point it at your weather data lake? Again I have never hears the answer "b" (except from meteorologists, but they are the analysts in this version of the story)
A lot of this comes back to the hi-jacking of the term "self-service". I would (strongly) argue that getting a weather forecast from your favourite web site is self-service information delivery, but there is no hint of a self-service BI tool in sight.
In fact, if you think about it, self-service in everyday life means the opposite to what it does in BI. After all if you go to a self-service restaurant, you are not shown into the kitchen to cook your food, instead you choose from a convenient selection of pre-prepared offerings.
BI teams have a lot to learn about end-user BI from the fast food industry :-)