Most businesses have figured out that the value of data science originates in the dynamic, exploratory activities of data scientists, equipped with their favorite tools and algorithms. However, data science teams often produce artifacts that are difficult for others in the enterprise to directly consume. Business analysts are too intimidated by the code, and software developers are sometimes ignorant of the sophisticated math and data analysis.
Anaconda can help resolve both of these issues and help data science teams easily move their work out of the exploratory sandbox and into production servers in a way that IT can feel good about. Meanwhile, other capabilities within the Anaconda platform can expose the results of analysis easily to business analysts and their spreadsheet-based workflows.
Peter Wang explores the typical problems data science teams experience when working with other teams and explains how these issues can be overcome through cohesive collaborative efforts among data scientists, business analysts, IT teams, and more.
This session is sponsored by Anaconda.
Peter Wang is the cofounder and CTO of Anaconda, where he leads the product engineering team for the Anaconda platform and open source projects including Bokeh and Blaze. Peter’s been developing commercial scientific computing and visualization software for over 15 years and has software design and development experience across a broad variety of areas, including 3-D graphics, geophysics, financial risk modeling, large data simulation and visualization, and medical imaging. As a creator of the PyData conference, he also devotes time and energy to growing the Python data community by advocating, teaching, and speaking about Python at conferences worldwide. Peter holds a BA in physics from Cornell University.
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