The potential of big data is only limited by the creative thinking of your business stakeholders, and that may be the most important concept in the “thinking like a data scientist” process. The “thinking like a data scientist” process guides the business stakeholders into envisioning how big data can optimize their key business processes, create a more compelling customer engagement and uncover new monetization opportunities. But neither the business stakeholders, nor the data scientists, can likely do that envisioning entirely by themselves.
The data scientists with whom I have worked are brilliant. They have the ability to apply unique data enrichment techniques and a bounty of analytic algorithms in an attempt to identify those variables and metrics that are better predictors of performance.
However without the business stakeholders helping them by identifying the right hypotheses to test, the variables that will be better predictors of performance, and the business decisions that they need to make, the data science process can end up being rudderless – without a clear sense of direction and an understanding of what success looks like – a solution looking for a problem.
I will be covering our “thinking like a data scientist” process at the New York Strata+Hadoop World conference September 29 through October 1.
I will be presenting “Think like a data scientist: Build your big data blueprint” 5:25pm–6:05pm Wednesday, September 30. The workshop session will be complete with a workbook, so like I tell my students at the University of San Francisco School of Management (I teach a course called The Big Data MBA), come to class ready to work.
And oh yeah, there just might be a special surprise for those folks who come to the session and complete the workshop.
Importance of Thinking Differently
Maybe the biggest inhibitor to creative thinking is the baggage about data and analytics that we have picked up over the years. Organizations need to embrace the power of “thinking differently,” especially with respect to:
- Data as a strategic asset to be gathered, enriched and shared, versus data as a cost to be minimized
- The potential of predictive (what is likely to happen) and prescriptive (what should I do) questions versus of just mechanically capturing descriptive (what happened) questions
- The power of data science to quantify those variables and metrics that are better predictors of performance, versus business intelligence that just reports on what happened while monitoring current business performance
- Building analytic profiles at the individual (human, machine) level to uncover individual behaviors, tendencies, propensities, interests, passions, associations and affiliations that can lead to specific actionable insights, versus relying on aggregated data to uncover general market trends
Jeff Abbott of EMC Consulting’s Big Data marketing team has created a most excellent “Think Like a Data Scientist” Interactive Guide. It outlines how we drive the creative collaboration process between business stakeholders and data scientists to identify and utilize predictive and prescriptive analytics to create new sources of business value.
Hey you data scientists!! There is a guinea pig opportunity. Data Scientists attending Strata Hadoop World New York are invited to join an exclusive group of two dozen participants in a live User Feedback Program and get access to exclusive content and connect directly with EMC’s Big Data Solutions Product Management team. Join this program and share your insights on user experience and usability feedback for the Federation Business Data Lake. Sign up is only 1 click away or come by the EMC booth (#319) during the show.
The most impactful, yet biggest challenge, to drive value out of big data doesn’t lie with the technology, but lies with getting the business stakeholders to think like a data scientist.
I think the Jules Verne quote from the book “Around the World in Eighty Days” perfectly describes the relationship between the business stakeholders and the data scientists:
“Anything one man can imagine, other men can make real.”
The moniker “Dean of Big Data” may have been applied in a light-hearted spirit, but Bill’s expertise around data analytics is no joke. After being deeply immersed in the world of big data for over 20 years, he shows no signs of coming up for air. Bill speaks frequently on the use of big data, with an engaging style that has gained him many accolades. He’s presented most recently at STRATA, The Data Science Summit and TDWI, and has written several white papers and articles about the application of big data and advanced analytics to drive an organization’s key business initiatives. Prior to joining Consulting as part of EMC Global Services, Bill co-authored with Ralph Kimball a series of articles on analytic applications, and was on the faculty of TDWI teaching a course on designing analytic applications.
Bill created the EMC Big Data Vision Workshop methodology that links an organization’s strategic business initiatives with supporting data and analytic requirements, and thus helps organizations wrap their heads around this complex subject.
Bill sets the strategy and defines offerings and capabilities for the Enterprise Information Management and Analytics within EMC Consulting, Global Services. Prior to this, he was the Vice President of Advertiser Analytics at Yahoo at the dawn of the online Big Data revolution.
Bill is the author of “Big Data: Understanding How Data Powers Big Business” published by Wiley.
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