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Nicole Klemp

Back in 2012, Thomas Davenport wrote in the Harvard Business Review (HBR) that Data Scientists have the “sexiest job of the 21st century.” Jump ahead five years, and data science is just as hot — if not hotter. Whether it’s big data, microdata, customer data, employee data, Data from Star Trek … we’ve got a lot of damn data, and we’re just not sure what to do with it. That’s where data science comes in.

Like the other great things we’re running short on this year: helium, avocados, bacon (see: aporkalypse), we have a high demand and low supply of data scientists. There will be four to five million jobs in the U.S. requiring data analysis skills by 2018, and a need for 1.5 million more managers and analysts with technical and analytical skills, according to the McKinsey Global Institute. Over the past few years, companies have gotten better at collecting data, but lack the people and knowledge to use that data effectively.

What exactly is data science?

When you were in school, you probably had a few different science classes: chemistry, biology, anatomy, maybe even astronomy, but data science probably wasn’t an option. (Computer Science wasn’t even an option for many of us.) But that’s all about to change — hopefully sooner rather than later. Data science is an evolutionary field, and most universities haven’t caught up in developing comprehensive data science degree programs yet. Many scholars are still arguing about what it even is, and how to define it. But we’ll go with NYU’s definition: “At its core, data science involves using automated methods to analyze massive amounts of data and to extract knowledge from them … In virtually all areas of intellectual inquiry, data science offers a powerful new approach to making discoveries. By combining aspects of statistics, computer science, applied mathematics, and visualization, data science can turn the vast amounts of data the digital age generates into new insights and new knowledge.”

Creating a data-driven culture

Whether or not they’re actually doing it, most organizations today realize the importance of making business decisions based on data. According to HBR, companies known for using data-driven decision-making are an average of five percent more productive, and six percent more profitable than their competitors.

Whether or not you have a data scientist on staff, you can empower everyone in your organization to use data to improve processes and make better decisions. Access and transparency are key to building a data-driven organization. Every minute that workers have to wait for a manager or someone in IT to pull a custom report, they’re losing productivity. To create a more productive workforce, everyone in the organization (not just business owners and managers) needs access to real-time data. Predictive analytics and interactive dashboards — with the ability to slice and dice data, and create “what-if” scenarios — allow workers to make quicker, more informed decisions. The richer the data, the easier it is for teams to look back and see what’s working well, and what isn’t.

Find out how organizations like yours are using data science to improve their businesses, and learn about the best technologies for data management in our ebook, The Productivity Prescription: How to Create a More Productive Workforce.

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