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Breaking Data Science Open by Christine Doig, Michele Chambers, Ian Stokes-Rees

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Chapter 10. Self-Service Data Science

As we discussed in the past chapter, a skills gap exists in the market for data scientists—those mythical unicorns with the ideal combination of computer science, math, and domain expertise. But even those organizations that have managed to snare data scientists can have trouble getting the assets they create to the frontline employees who need them.

Keep in mind that for every data scientist in an enterprise, there are approximately 50 to 100 frontline workers—including business analysts, salespeople, marketing managers, production managers, and customer-service representatives—who could use data science to make better business decisions.

This chapter will explain how a self-service approach can be used to empower business analysts. Equipping the maximum number of people within an organization to perform basic data science activities will allow them to work directly with data, informing their day-to-day work with contextualized intelligence that delivers game-changing business value.

Self-Service Data Science

To make data science easier to get and easier for frontline workers to use, data scientists need to shift perspectives and walk in their shoes. In other words, data scientists need to understand and have empathy for the perspective and experiences of their colleagues who are involved in other lines of business but who can also benefit from quantitative analytical information and tools.

This means contextualizing data science to the ...

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