Business Intelligence Analyst or Data Scientist? What’s the Difference?

I am a huge Thomas Davenport fan. His book “Competing on Analytics: The New Science of Winning” was the first book to make organizations aware of the business potential of analytics, even prior to the craziness brought on by Big Data. I happened upon a recent article of his titled “Looking Outward with Big Data: A Q&A with Tom Davenport” and one item from that article really jumped out at me:

“Initially, I didn’t see much of a distinction [between business analytics and big data], and I thought that I could kind of rest on my laurels and not write a book about big data—because the fact is that the analytical tools and approaches used are not all that different for big data. But when I started talking to companies and data scientists, I realized that there really were some fairly substantial differences—some that have yet to be fully articulated and some that are already in evidence.”

There are significant differences between a Business Intelligence (BI) analyst and a Data Scientist, but many folks are still confused. I recently received the following email from a follower (Felix) of my blog series that highlights some of the challenges that organizations are wrestling with on this difference in definitions.

I recently came across your January 9th blog post entitled “Business Analytics: Moving From Descriptive To Predictive Analytics.” Our IT department disagrees on the capabilities of OLAP cubes. To me, a cube does not appear useful for parameterized models or most types of scenario analysis. (I am trained in statistics and other forms of financial modeling.) I showed Figure 1 of your blog to my colleagues, but was told that I do not understand OLAP technology.

Felix’s dilemma is typical of what I see in organizations that have spent considerable time and money building out their Business Intelligence capabilities. To me, the situation is similar to the construction worker discovering the “saw.” Doesn’t mean that the hammer is no longer important, but the saw and the hammer perform entirely different but complementary tasks.

Here was my response to Felix:

Hey Felix, push back on your IT department. There is nothing predictive in OLAP cubes.