5 Tips for Helping Your Data Scientists Do Their (Intended) Jobs

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Open Communication

Don't let data scientists work in the dark.

This isn't about turning on the lights in the server room; it's about making sure that data scientists don't operate in isolation. The insights provided by analytics can be fascinating and powerful for driving business strategy, but they can paradoxically also cause risk. Communications that hint at harassment, customer complaints of adverse reactions, and reports of dangerous defects can all come to light when conducting broad analysis of multiple data types. It's important for data scientists to have an open line of communication with compliance, legal, and risk management teams.

The data scientist has practically become a mythical creature in business lore. Revered, rare, and – purportedly -- supernatural in their abilities. As early as 2012, the data scientist was lauded as the "Sexiest Job of the Century." However, as Big Data has matured into a household term, businesses have begun to transition away from the hype. In many cases, ambitious analytics projects and big budgets have melted away, revealing the day-to-day -- and unforeseen -- problems of implementation.

The problem is that many of the world's data scientists find themselves not so much massaging data for insight, as simply trying to manage data to render it workable. In short, data scientists are not getting to spend much time being data scientists.

Their work is not simply about crunching numbers; it's a nuanced and multi-faceted field that combines equal parts of imagination, curiosity, and technical skill. But it has become clear that even the best data scientists need extensive support from business and IT units in order to perform their true role. In this slideshow, ZL Tech has identified some tips for making it happen.

 

Related Topics : Business Intelligence Vendors, Data Quality, Data Warehousing, Key Performance Indicators, Knowledge Management

 
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