Data science technology for
a competitive edge.
a better world.
A movement that brings together millions of data science practitioners, data-driven enterprises, and the open source community.
Anaconda was built by data scientists, for data scientists. More than 20 million people use our technology to solve the toughest problems.
Tackle any challenge
Anaconda solutions are serious technology for real data science and ML applications. Anaconda is versatile - you'll be ready to solve problems you don't even know you have yet.
Own your destiny
Your business challenges change every day. Only open-source innovation can keep pace with your needs. Never be stuck waiting for a vendor to add a feature again.
Stay safe and secure
Catch vulnerabilities before they catch you. Control access to models, data, and packages. Know the who, what, when, and where of every project.
Why it matters
- Deliver on your data strategy
- Get to market faster
- Maximize flexibility and control
- Attract and keep the best talent
The modern world of data science is incredibly dynamic. Every day, new challenges surface - and so do incredible innovations. To win in this context, organizations need to give their teams the most versatile, powerful data science and machine learning technology so they can innovate fast - without sacrificing security and governance.
We call that powerful solving.
The data science
platform for all
The world's most popular open-source package distribution and management experience, optimized for commercial use and compliance with our Terms of Service.
Thousands of curated data science packages in an enterprise-grade repository. Ideal as you scale the use of Python and R across the data science discipline.
Our enterprise platform is a comprehensive foundation for any organization that wants to use data science and machine learning to make better decisions and build differentiating products.
State of Data Science: On the Path to Impact
Featuring insights from over 4,200 respondents, this year’s State of Data Science report dives into data science industry trends such as COVID-19’s impact, popular programming languages, data literacy, and bias and explainability in machine learning models.