Open Thoughts on Analytics
JAN 3, 2012 8:54am ET

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Data Science Skepticism

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I don't think you'd get much argument from the data science community that the emerging field involves components of business, technology and statistical science. “Veteran” DS'ers will also note both inquisitive and skeptical dispositions as keys to success in the discipline.

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Comments (4)
As a former statbrat and BI professional - now data driven marketer, I'll agree with your perspective that technically, there is not much difference between the DS and BI professional except in the use of statistical packages (yes, Excel can do stats but this is a layman's use for that type of work). Where I do think the distinction lies is how certain of the analytic outcome and to what use is it for that is the determining factor. BI more often than not answers the question of business and business process performance in a dashboard. DS takes it a step further to gain insight into more allusive aspects of the business and prediction. It is not the exactness of the answer that DS provides, but a possibility and probability. BI is absolute as it typically crunches the entire data set and tallies up.

In marketing it is A/B testing of email vs. factor factorial. A/B is easier, faster, and points in the right direction. Factor factorial lets me squeeze out the 1/2 percentage improvement on a wider B2C campaign that could translate into significant revenue increases. 9 times out of 10, A/B works just fine and BI wins. It is that perspective that is probably most impactful to the establishment of DS.

Posted by michele g | Tuesday, January 03 2012 at 1:03PM ET
Steve,

I am in agreement with you that being skeptical with a dash of cynicism is healthy. Bias can certainly lead to trying to prove preconceived notions.

I would like to add a different element. I believe data scientists can be leaders, not necessarily like the executive leaders at the top of the organization chart. I refer to the definition where leaders have followers. However, effective leadership requires periods of solitude which I believe can aid in being skrptical.

What does solitude have to do with leadership? Solitude means being alone, and leadership necessitates the presence of others - the people you're leading. When we think about leadership in American history we are likely to think of Washington, at the head of an army, or Lincoln, at the head of a nation, or King, at the head of a movement - people with multitudes behind them, looking to them for direction. And when we think of solitude, we are apt to think of Thoreau, a man alone in the woods, keeping a journal and communing with nature in silence."

Solitude allows one to be alone with your thoughts. Arguably solitude is crucial to carry out the task of leadership and being a data scientist. Everyone needs this to provide one the chance to deeply consider the lasting improvements and skills their organization will need to for sustained organizational performance improvement. These include exploiting the emerging practices of business analytics and deploying and integrating enterprise performance management methodologies. These include strategy maps, scorecards, dashboards, risk management, activity-based costing, predictive analytics, rolling financial forecasts, and many others.

Data scientists need to take time to think and to first frame a problem before they start solving it.

Gary Cokins, SAS

Posted by Gary C | Tuesday, January 03 2012 at 1:36PM ET
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