Big Data & Data Analytics: Not for the Faint of Heart (or Poor of Purse)

Michael R. Wood is a Business Process Improvement & IT Strategist Independent Consultant. He is creator of the business process-improvement methodology called HELIX and founder of The Natural Intelligence Group, a strategy, process improvement and technology consulting company. He is also a CPA, has served as an Adjunct Professor in Pepperdine's Management MBA program, an Associate Professor at California Lutheran University, and on the boards of numerous professional organizations. Mr. Wood is a sought after presenter of HELIX workshops and seminars in both the U.S. and Europe.

Like every other hot technology that makes it past the infatuation and magic bullet phase, the day comes when executives and IT professionals alike realize that to get the value of the technology in question is going to take focus, discipline and money.

Big data/data analytics (BA/DA) and artificial intelligence (AI) have finally started to reach that stage in their evolution. Gil Press, a Forbes contributor, echoes this view in his article “10 Predictions For AI, Big Data, And Analytics in 2018.” In the article, he opens by referencing a recent Forrester Research report (“Predictions 2018: The Honeymoon for AI Is Over”) citing that companies are finally realizing that effective use of BA/DA/AI requires planning, proper deployment and governance. (Spot on, Mr. Press.)

Diving further into the Forrester report, it appears obvious that BD/DA is not for the faint of heart—or for those lacking deep pockets. Your first clue that it’s an expensive endeavor is Forrester’s references to organizations that have data lakes with over 100 terabytes of unstructured data—information that either does not have a pre-defined data model or is not organized in a pre-defined manner, like text, video and voice. (A data lake, according to TechTarget.com, is a “storage repository that holds a vast amount of raw data in its native format until…

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