Data Science-Tested, IT-Approved

Operational Best Practices for Enterprise Data Science
We know how hard you work to keep things running smoothly at your enterprise. But when it comes to enterprise data science, do you know how to give your data science team the tools they need while also keeping everything secure and stable?
We tackle the four main concerns we hear from our customers and show you best practices for managing enterprise data science. Specifically, we’ll address:
  • Scalability: Oversee a lot of users on a lot of different machines? We’ll demonstrate how to utilize your computer resources most effectively.
  • Security: Need to integrate open source tools while maintaining your existing security policies around authentication, encryption, authorization, and audit logging? We’ll help you define security mechanisms, industry standard tools, and integration methods.
  • Integration with Existing Infrastructure: Want to give your data science team a single gateway into all your storage and compute resources? We’ll go over example architectures for Spark clusters, RDBMs, and distributed storage.
  • Governance: Trying to govern the packages your data science team uses without restricting their flexibility or adding a ton of work to your plate? We’ll show you Anaconda Enterprise’s on-premise package mirror and dependency management features.

Meet Our Speakers

  • Duane Lawrence is the VP of Sales Engineering & Implementation Engineering. He is a driven team leader and manager with a passion for mapping solutions to customer needs and achieving high customer satisfaction.

    Duane came to Anaconda with 20+ years of experience delivering distributed computing and analytics solutions into the enterprise. He has worked at both startups and public companies, selling into financial services, pharmaceuticals, manufacturing, healthcare, and publishing. He also spent four years running an online marketplace for professional event planners to connect with available venues, and currently draws from his expertise to advise early-stage startups on product management and go-to-market strategies.

    Duane holds an SB in Math with Computer Science from MIT. He is based in NYC.
  • Gus Cavanaugh is a Product Marketing Manager at Anaconda, where he focuses on translating technical capabilities into user benefits. He has over five years’ experience in analytics and consulting for enterprises. Prior to joining Anaconda, he worked on projects ranging from small-scale data apps and dashboards to distributed Hadoop clusters at companies including IBM and Booz Allen Hamilton.

    Gus holds an MS in Systems Engineering from George Washington University and a BS in Business Administration from Washington & Lee University. He is a frequent speaker on analytics topics for non-technical audiences.
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