Reinforcing Open Data Science Foundations with conda 4.3 Release
Jun 02, 2017By Anaconda Team
At Continuum Analytics, we talk a lot about Open Data Science—this new world order of analytics that is rapidly accelerating the pace of innovation around Big Data and Data Science. It's an exciting time for anyone in the field, but, to people who are new to the space, it can also appear chaotic as old legacy approaches and solutions are disrupted by new players.
Continuum Analytics has always understood that it has a key role to play as a founding member in this new world order—providing value with a clear, organized foundation on which to build solutions in the new ecosystem. Our Enterprise customers recognize this, which is why Continuum is the go-to partner for any Enterprise deploying Python or other Open Data Science solutions into production.
This Open Data Science foundation includes critical building blocks like Anaconda which provides a pain-free way to get 100+ of the most common Python and R packages to people's desktops. Anaconda is backed up by the Anaconda Repository of another 700+ libraries essential to the work of Data Scientists and Data Engineers all over the globe. Anaconda Cloud extends the platform to enable anyone in the world to freely contribute their libraries. Community-backed (and Continuum-supported) efforts like conda-forge are rapidly expanding the breadth of capabilities being made available to the Open Data Science ecosystem and dramatically shortening delivery timeframes for new capabilities. Another critical piece is package-management with conda. Our Dev team recently announced the release of conda 4.3, with a host of new features and capabilities engineered to make conda more robust and capable than before—for example, addition of greater reliability through atomic file operations and expanding use cases provided by a new conda API.
Conda is a 100% free, open source software (BSD-3 OSS License). Continuum leverages conda and other open source software for its Enterprise platform to harnesses the power of Open Data Science in an integrated, managed and secure fashion. We refer to this approach as "Open Core.” Our Enterprise platform is free, open source software users are familiar with, packaged and delivered to meet the needs of our Enterprise customers.
So, why is the latest release of conda relevant to our commercial customers? Beyond the obvious technical advantages and benefits, the latest release illustrates the strengths of the Open Data Science ecosystem for businesses:
Reliable Technology Foundations: Continuum continues to invest in making Open Data Science a cohesive, robust ecosystem for Enterprises to build on. Read how it's making a difference at Paypal Engineering.
Simplified Change Management: This innovation can be seamlessly funneled into existing Anaconda platform deployments to get value at no incremental cost.
Innovate, but Plan for Continuity: The conda team is taking pains to address key issues while minimizing breaking changes that are so disruptive in enterprise environments. When breaking changes occur, we're creating transparent transition plans with guidance for customers to follow and allowing for sufficient lead times that customers can plan appropriately
Open Data Science is Real: Continuum (and others in the ecosystem) continues to exhibit the values of Open Data Science: Availability, Innovation, Interoperability and Transparency. Conda is an illustrative example of an open source tool that makes Data Scientists’ lives easier, becoming an indispensable part of hundreds of thousands of Data Scientists’ workflows.
Open Data Science represents a new three-way symbiotic relationship between customers, community and open core vendors that delivers the most powerful results for everyone involved. The value for businesses from the conda 4.3 release is being replicated across a thousand different tools in the ecosystem.
Is your company taking advantage of this? Tell us how is Open Data Science making a difference in your organization—we'd love to hear your success story. We're equally interested in hearing about how it can be made better. Leave a comment and let us know, or contact the Anaconda team.