Dr. Eric Siegel, founder of Predictive Analytics World, says it’s time business users take the power to create predictive analytics into their own hands. Welcome the era of the DIY data scientist.
Today, the roles of data analysts, business intelligence analysts and business analysts are changing as new technologies hit the market.
DMway asked Dr. Eric Siegel, founder of Predictive Analytics World and the author of “Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die – Revised and Updated,” how can individuals steer the evolution of their roles in this new era of big and fast data?
Eric: Although many are flocking to take up the hands-on side — learning how to execute on the technical practices of predictive analytics — there’s still a great a need for analytics awareness and acumen on the managerial and decision-maker side. Value in the deployment of analytics can only be realized by way of an organizational process that effectively overseas and directs the hands-on technical practice, as guided by business need and pragmatics.
DMway: There are major trends upending the analyst world, including bigger and faster data, predictive analytics and automation. Can you talk to each of these trends and offer advice to analysts looking to upskill to fit the digital world?
Eric: More data means great opportunities — for the enterprise, and for you personally, taking a role in leveraging all this data. Predictive analytics is the most actionable data-driven technology, since the predictive score it outputs for each individual (customer, prospect, suspect, etc.) directly informs the action or treatment to be applied for that individual. This fundamental concept applies widely, so the breath of applications is quickly growing into so many new opportunities.
To ride this wave, you need to learn as much about the changing and growing landscape of business use cases as you do about how to execute on the core predictive analytics technology. Go to non-academic, commercially-driven conferences and read the trade publications to keep tabs on this growth. Interview line-of-business managers to hear about their pain points and identify the large-scale operations that could present the best opportunities for improved efficiency.
You chose to be on the DMway advisory board. Why DMway? What differentiates DMway from other automated predictive analytics tools?
Eric: DMway’s competitors are selling tools for data scientists — individuals with PHD’s, statisticians and machine learning experts — designed to provide direct control over every detail of the underlying algorithms. In contrast, DMway targets a different audience: more pragmatic users who want such tweaking to be determined automatically by the software product itself. By automating this way, DMway’s platform upskills every business user to better prepare for the digital world.