Embrace Innovation & Tame the Anarchy

Migrating from traditional analytics to modern Open Data Science (ODS) is one of the most important trends of the decade. However, although this migration is critical to the core mission of many enterprises, practicing Data Science effectively has remained a thorny challenge. 
Part of this is due to the use of older proprietary data technologies that do not provide the flexibility and power needed to channel the full potential of a Data Science team - not just Data Scientists and Developers, but business experts and other stakeholders.
Fortunately, modern technologies, by leveraging developer talent from across the world through the open source paradigm, now provide comprehensive, best-of-breed and cost effective ecosystems. Not only do these technologies meet current challenges, but they also address potential future struggles, since they can rapidly adapt in ways that proprietary Data Science technologies cannot.
In this paper, you'll learn why Open Data Science is the foundation to modernizing data analytics, and:
  • In what ways availability, interoperability, transparency and innovation are some of the most important benefits of the ODS approach
  • The best path and important considerations when moving to ODS
  • Why the Anaconda platform is the best solution for ODS
  • How you can leverage your current investment in analytics while moving to ODS


Thank you - the whitepaper will arrive in your inbox momentarily.

About the Author

Christine Doig

Christine Doig is a Senior Data Scientist at Continuum Analytics, where she worked on MEMEX, a DARPA-funded project helping stop human trafficking. She has 5+ years of experience in analytics, operations research, and machine learning in a variety of industries, including energy, manufacturing, and banking.
Christine holds a M.S. in Industrial Engineering from the Polytechnic University of Catalonia in Barcelona. She is an open source advocate and has spoken at PyData, EuroPython, SciPy, PyCon, and many other conferences.