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Big Data Needs Creative Types, Too Information Week, June 24

While today's data scientists must have knowledge of multiple technical and business disciplines -- including analytics, computer science, math, modeling and statistics -- it's also becoming a prerequisite to be able to showcase creative approaches to data analysis. Not surprisingly, it's often a challenge to find individuals with such a wide range of abilities, a reality that might soon transform the position of data scientist into three distinct job categories. There will be technologists to write algorithms and code; statisticians and quantitative analysts to crunch numbers; and creative thinkers who will find insights in data that their more technically inclined colleagues might miss. For companies, the challenge will be to combine these different personality types into one cohesive Big Data team.

In the Big Data world, the technologists are the people who build the systems, get data loaded and transferred and maintain the critical infrastructure of a company. The creative analysts, in turn, will mine massive volumes of data for actionable insights. Not surprisingly, these so-called "artist explorers" probably won't manage computer systems; instead, they will be completely operationally focused and a little more creative and strategic in the way they think. As a result of this transformation of the data scientist role, universities and technology companies must work together to address the "data skills gap" by giving students the tools and training to compete in a data-driven economy.

As Big Data tools grow increasingly sophisticated and automated, demand for highly trained technologists will remain high. The good news is that this projected division of labor -- technologists, quantitative analysts, and "artist explorers" -- will not reduce the need for data scientists. The six-figure salary of a career in data science will continue to attract talented people -- especially younger workers starting out on their career who are looking for something where they're going to be gainfully employed and be able to make some money. Besides, the job is fun: you can't get bored when you're doing data exploration and business intelligence because every day there's a new competitor and a new marketplace, as well as new data, algorithms, and relationships.


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