Unveiling Anaconda Enterprise–The Data Science Platform for the Entire Team

2. © 2017 Anaconda, Inc. - Confidential & Proprietary Kris Overholt Senior Product Manager Your Speaker For Today • Works with DevOps, product engineering and platform infrastructure for the Anaconda Enterprise data science platform. His areas of expertise include distributed systems, data engineering and computational science workflows. • Received his PhD in Civil Engineering from The University of Texas at Austin, and holds a BS and MS in Fire Protection Engineering. Prior to joining Anaconda, he worked at the National Institute of Standards and Technology (NIST), Southwest Research Institute and The University of Texas at Austin.

3. © 2017 Anaconda Inc- Confidential & Proprietary Unveiling Anaconda Enterprise 5 • Anaconda Enterprise 5 Overview • Anaconda Enterprise 5 Key Features • Anaconda Enterprise 5 Demonstration • Getting Started with Anaconda Enterprise 5 3

7. © 2017 Anaconda Inc- Confidential & Proprietary New Capabilities in Anaconda Enterprise • Scalable architecture for on-premises or cloud installations • Integrated data science experience, incl. JupyterLab • One-click data science deployments 7

8. © 2017 Anaconda Inc- Confidential & Proprietary Data Scientists IT/Administrators Business Analysts & Managers Anaconda Enterprise Users 8 Developers & ML Engineers • Collaborate • Reproduce • Deploy • Govern • Secure • Scale • Self-Serve • Interact • Understand • Build • Publish • Consume

9. © 2017 Anaconda Inc- Confidential & Proprietary 9 Data Science Platform Anaconda Enterprise Data Scientists IT & Admin BA & Managers On-Premises Cloud Anaconda Enterprise Overview Users Deployment Infrastructure Packages Projects Deployments ML REST APIs Dashboards Notebooks Web Apps Bokeh Apps Shiny Apps Amazon AWS Microsoft Azure Google Cloud

11. © 2017 Anaconda Inc- Confidential & Proprietary • Centralized, browser-based notebook collaboration with versioning and access control • Integrated data science environments with Jupyter Notebooks and JupyterLab • Manage and share data science projects and dependencies 11 Collaboration

12. © 2017 Anaconda Inc- Confidential & Proprietary 12 • Upload and share projects and notebooks with portable data science environments • Enterprise-grade data science reproducibility and portability with Anaconda Project • Mirror data science packages and dependencies within your organization Reproducibility

13. © 2017 Anaconda Inc- Confidential & Proprietary 13 • One-click deployment of self- service notebooks, interactive visualizations, machine learning models, REST APIs and other apps • Industry standard containerization and cluster orchestration technology Deployment

14. © 2017 Anaconda Inc- Confidential & Proprietary • On-premises data science package repository • License filtering and license audit reports • Event logging and auditing of package, project and deployment activity 14 Governance

15. © 2017 Anaconda Inc- Confidential & Proprietary 15 • Integrated with enterprise- grade identity providers: LDAP, AD, SAML, Kerberos • Secure network communications and end-to- end TLS/SSL encryption • Centralized user management portal and token-based access to deployed models and applications Security

16. © 2017 Anaconda Inc- Confidential & Proprietary 16 • Distribute Anaconda libraries across Hadoop and Spark clusters • Connect Anaconda Enterprise to Spark or Dask and perform distributed computations interactively • Scalable distributed computation resources for project editing and user- deployed data science apps Scalability

18. © 2017 Anaconda Inc- Confidential & Proprietary Example - Tensorflow / Tensorboard • Tensorflow with CPU/GPUs • Deep learning • Image classification • Neural networks • Easily deploy Tensorboard for ML development and performance monitoring 18

21. © 2017 Anaconda Inc- Confidential & Proprietary Example - R / Shiny • Supports R and Microsoft R Open (MRO) • Jupyter Notebooks with R (IRkernel) • More than 200 popular R libraries • One-click deployment of Shiny apps and REST APIs with R 21

24. © 2017 Anaconda Inc- Confidential & Proprietary 24 Key Strengths Unique Differentiators Most comprehensive data science development cycle - ML algorithm development and package management - Self-service dashboards and reports for managers Widest range of deployment options - Deployment of: - Notebooks (Python, R, Spark) - ML REST APIs - Interactive applications: Bokeh apps, Shiny apps - Web apps (Django, Flask) - Composable applications Unique continuity of experience and reproducibility - Identical experience on laptop and Anaconda: - JupyterLab, Jupyter Notebooks - Run platform data science projects on Linux, Windows, macOS Only vendor to support and indemnify Anaconda Distribution - First-class integration with Anaconda Distribution - Protect: Reduce Risk of Intrusions, Vulnerabilities & Infringement - Solve: Get Questions Answered, Guided by Experts - Deliver: Resolve Issues Quickly & Minimize Downtime

26. © 2017 Anaconda, Inc. - Confidential & Proprietary Get Started with Anaconda Enterprise Register now for a free 30-day Anaconda Enterprise 5 Test Drive https://go.anaconda.com/test-drive-anaconda-enterprise-5/ Read Deploying Secure and Scalable Data Science Projects http://go.continuum.io/wp-productionizing-deploying-secure-scalable-ds-projects/ Contact us by phone or email +1 (512) 776-1066 | sales@anaconda.com