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Understand the Difference Between Data Science and Analytics

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It's becoming more common to see the terms analytics and data science used interchangeably. However, there is a difference that organizations have to understand, not only when hiring for their data science teams but in shaping their data initiatives.

One way to set data science apart is to consider the use of data that reflects the "Three V's" of Big Data, volume, velocity, and variety. Adam McElhinney, director of data science at predictive analytics company Uptake, joins All Analytics Radio to discuss how those Three V's set apart a data science project. McElhinney, formerly head of business analytics and marketing analytics for Enova Financial, has deep experience in business analytics, credit modeling and credit scoring, consumer finance, business development, performance optimization, strategic planning, and statistical analysis.

Tune into All Analytics Radio at 2 pm (EST) on Monday, November 23, to learn how you can take your analytics initiative to the next level by utililizing those key elements of Big Data: volume, velocity, and variety.

 

 

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