Data Science Marries Analytics, Business

Susan Hall
Slide Show

Eight Essentials of Business Analytics

Find out what's going on inside market-leading companies that sets them apart.

As companies amass an ever-greater volume of data, the IT and business data analysts appear headed for a collision similar to Reese's peanut butter and chocolate. But will it be the real, sweet deal?


Who knew there was such confusion over the emerging role of data scientist? A recent survey of practitioners of Big Data analytics by TDWI found an array of people within companies doing the deep dive into data and concludes:

This breadth of job titles is significant because it shows that analytics is not just for an analytic specialist. On the contrary, analytics is becoming a standard competency for a wide range of business and technology people.

In a post at Information Management, Forrester's James Kobielus attempts to clarify what is and isn't "data science." He says it's all about using statistical algorithms and tools to find hidden patterns in historical data sets, but it involves "the suits" as much as the statistics people. What it's not? BI report-building and such that show obvious patterns. He writes:

In establishing a data science center of excellence in your organization, you must institute forums, processes, training, tools, and other initiatives that bring people with these diverse skills together to collaborate on common projects. You must also encourage people from each camp to cross-train in the other's area. Business analysts must learn more sophisticated statistical techniques than their schooling instilled in them and more sophisticated tools than their spreadsheets. Statistical analysts must attach themselves to business groups or functions and learn how to apply their quantitative smarts to real operational problems.

In a second piece that ponders whether "data scientist" is merely a flavor-of-the-month job title, he talks about the value of this work:

If you can uncover new patterns in customer sentiment before your rivals, then you can address them before the competition could even cobble together a clue. If you can adjust the media mix behind your digital marketing campaign in real time to ensure the right messages get to the right audiences, you can save the campaign, and possibly your company, from going down the tubes. And by iterating through behavioral analytics models on your customer experience platform, you can conduct "real-world experiments" that help strengthen satisfaction and retention.

Sounds handy, indeed.

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