The impact of open source software on the data science revolution

March 16, 2015

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

It's hard to overstate the role of open-source software in the data science revolution. Tools like Hadoop, Spark, R, and Python are essential parts of the modern data science toolkit. These tools are likewise part of the solutions built by the Consulting Services group at Revolution Analytics. Our VP of Professional Services, Neera Talbert, shares her view on the impact of open source software in an article for Inside BigData published today. Here's Neera on the typical day of a data scientist:

Unlike a pure statistician, a data scientist is also expected to write code and understand business. Data science is a multi-disciplinary practice requiring a broad range of knowledge and insight. It’s not unusual for a data scientist to explore a fresh set of data in the morning, create a model before lunch, run a series of analytics in the afternoon and brief a team of digital marketers before heading home at night.

You can read the entire article at the link below.

Inside BigData: Open Source Software Fuels a Revolution in Data Science



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