About the Authors: Michele Chambers,  
Christine Doig & Ian Stokes-Rees

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 How Open Data Science is Eating the World

Michele Chambers
@MCanalytics

Michele Chambers, Chief Marketing Officer and VP Products at Continuum Analytics, is an entrepreneurial executive with over 25 years of industry experience. Prior to Continuum Analytics, Michele held executive leadership roles at several database and analytic companies, including Netezza, IBM, Revolution Analytics, MemSQL, and RapidMiner.

 Breaking Data 
Science Open

How Open Data Science is Eating the World

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Breaking Data Science Open

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Deliver Collaboration, Self-Service and Production Deployment with Open Data Science

Data science has burst into public attention over the past few years as perhaps the hottest and most lucrative technology field. No longer just a buzzword for advanced analytics, 

Christine Doig is a senior data scientist at Continuum Analytics, where she's worked on several projects, including MEMEX, a DARPA-funded open data science project to help stop human trafficking. She has 5+ years of experience in analytics, operations research, and machine learning in a variety of industries.

Christine Doig
@ch_doig

data science is poised to change everything about an organization: its potential customers, expansion plans, engineering and manufacturing process, how it chooses and interacts with suppliers and more.

The leading edge of this tsunami is a combination of innovative business and technology trends that promise a more intelligent future based on Open Data Science. Open Data Science is a movement that makes the open source tools of data science—data, analytics and computation—work together as a connected ecosystem.

In this book, you'll learn:

  • What Modern Data Science Teams Look Like
  • What are the Real World Open Data Science Applications in Enterprises
  • How to Navigate the Open Data Science Landscape
  • How to Bring Open Data Science to the Enterprise
  • How to Successfully Deploy Open Data Science
Ian Stokes-Rees
@ijstokes

Ian is a Computational Scientist who has had the opportunity to work on some of the biggest "Big Data" problems over the past decade. He loves Python and promotes it at every opportunity. Ian's greatest interest is in enabling communication, collaboration and discovery through numbers, narratives and interactive visualizations made possible by high performance computing infrastructure.

Ian's love of computers started with an Apple ][ and Logo at the age of 8. Two engineering degrees at the University of Waterloo (Canada) were followed by several years in the industry, developing algorithms and infrastructure for large computational problems. After a Ph.D. at Oxford (UK) working on the computing team for one the CERN particle physics experiments, Ian spent several years at Harvard University working on computational techniques for protein structure determination. Ian has been part of the engineering team at Continuum for the past 4 years

Deliver Collaboration, Self-Service and Production Deployment with Open Data Science

Data science has burst onto the public’s attention over the past few years as perhaps the hottest and most lucrative technology field. No longer just a buzzword for advanced analytical software, data science is poised to change everything about an organization: its potential customers, expansion plans, and engineering and manufacturing process and how it chooses and interacts with suppliers and more.

The leading edge of this tsunami is a combination of innovative business and technology trends that promise a more intelligent future based on the combination of open source software and cross-organizational collaboration called Open Data Science. Open Data Science is a movement that makes the open source tools of data science - data, analytics and computation - work together as a connected ecosystem.

In this book, you'll learn:

  • What Modern Data Science Teams Look Like
  • What are the Real World Open Data Science Applications in Enterprises
  • How to Navigate the Open Data Science Landscape
  • How to Bring Open Data Science to the Enterprise
  • How to Successfully Deploy Open Data Science



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