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This is where the suspense of belief is important.”
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“Experience provides benefits but is not without risk if we get too complacent. “This trait captures the idea of knowing what to expect when working in any area, but also knowing that experience and intuition are imperfect,” Nimeroff says. “This skill more than anything else determines the success of a data scientist,” Rao says.Ī data scientist needs to have experience but also have the ability to suspend belief, adds Jeffry Nimeroff, CIO at Zeta Global, which provides a cloud-based marketing platform. “They need to understand the business problem or decision being made and be able to ‘model’ or ‘abstract’ what is critical to solving the problem, versus what is extraneous and can be ignored,” says Anand Rao, global artificial intelligence and innovation lead for data and analytics at consulting firm PwC. These insights help predict potential outcomes and mitigate potential threats to the business. This role is important, but the rising stars of the business are those savvy data scientists that have the ability to not only manipulate vast amounts of data with sophisticated statistical and visualization techniques, but have a solid acumen from which they can derive forward-looking insights, Boyd says.
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“In the past, the teams responsible for data were relegated to the back rooms of the IT organization, performing the critical database tasks to keep the various corporate systems fed with the data ‘fuel’ allowed corporate executives to report out on operations activities and deliver financial results,” Boyd says. | Get the latest on data analytics by signing up for CIO newsletters. | Beware the 12 myths of data analytics and sure-fire ways organizations fail at data analytics.
#INSIGHTS DATA SCIENCE HOW TO#
Learn how to use data analytics for decision-making and the secrets of highly successful data analytics teams.