Data science is a key discipline in a data-driven organization. Through analytics, data scientists can uncover previously unknown relationships in data to help an organization make better decisions. However, data science is often performed from local machines with limited resources and multiple datasets on a variety of databases. Moving to the cloud can help organizations provide scalable compute and storage resources to data scientists, while freeing them from the burden of setting up and managing infrastructure.
In this session, FINRA, the Financial Industry Regulatory Authority, shares best practices and lessons learned when building a self-service, curated data science platform on AWS. A project that allowed us to remove the technology middleman and empower users to choose the best compute environment for their workloads. Understand the architecture and underlying data infrastructure services to provide a secure, self-service portal to data scientists, learn how we built consensus for tooling from of our data science community, hear about the benefits of increased collaboration among the scientists due to the standardized tools, and learn how you can retain the freedom to experiment with the latest technologies while retaining information security boundaries within a virtual private cloud (VPC).
Publisher: Amazon Web Services
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