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AnacondaCon 2017: Python and the Emerging Practice of ‘Open Data Science’

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For its first-ever official AnacondaCon user conference, data analytics software provider Continuum Analytics emphasized the idea of “open data science,” or the use of open source tools to analyze and share data in an operational way to improve operational efficiency and improve customer service. Makes sense: Continuum’s flagship software package, Anaconda, integrates the best open source Python and R tools for data analysis.

We’re just at the beginning of an era of incorporating data science into business operations, asserted Continuum Chief Technology Officer Peter Wang, during his opening keynote. According to the company, 96 percent of data science and analytics decision makers would agree that data science is critical to the success of their business, yet 22 percent say they are not making full use of the data.

We sat down with Wang during the conference to learn more about what he means by “open data science,” as well as to discuss why Anaconda is like the “Whole Earth Catalog” for open data science, the release of the Excel plug-in Anaconda Fusion, and, finally, the growing popularity of Python for data analysis. Listen here:

Topics:

0:47: Founding of Continuum.
4:07: ‘Open Data Science,’  and the Whole Earth catalog.
6:45: Keynote talk.
10:04: Data science software in containers.
12:28: Continuum’s new Excel plug-in Fusion.
18:02: Python or R?

Keynote Highlights:

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The post AnacondaCon 2017: Python and the Emerging Practice of ‘Open Data Science’ appeared first on The New Stack.


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