You can have the most accurate data in the world.
With the data up to the minute.
Provided in any format.
And you can still derive the incorrect conclusion.
Because nobody taught us how to extract insight from the data.
Yet we're all supposed to believe that's its easy.
The thing to keep in mind, we've had access to data for a long time now.
And we view the business in a rear view mirror.
Now that we have newer technology, at cheaper prices, the average person has access to tools once run by actuaries, statisticians and high financed projects.
All the technology is now at our disposal.
And that's why I believe there is a need for a data scientist to derive value from the data, both big and complex.
Because the CEO, SVP, VP, Directory, Manager, Supervisor may not be able to deduce the insight on their own.
The trick is to dumb down the technology enough to allow typical data analysts to find the insights.
Bring the software to the data analyst rather than send the data analyst to the technology.
That person's role is to understand data in it's raw format, be able to move the data around, clean up the data, apply business rules to the data, mash the disparate data sets, produce reports, visualizations, process Big Data, as well as understand the business enough to form valid conclusions and insights, and present these ideas to the senior management, the entire gamut.
There is a need for this person, whatever label they're given: Data Scientist, Data Analyst, Data Engineer, Data Monkey, etc.
Sling the data around, using technology, to interpret the business.
Data, Technology, Analytics.
Self Service won't solve all three components in my opinion.
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