Systems | Development | Analytics | API | Testing

GitHub Copilot: Using AI to build a custom connector with Fivetran's Connector SDK

This tutorial demonstrates how to build a Fivetran Connector SDK custom connector using VS Code and GitHub Copilot. The demo showcases the end-to-end process of creating, testing, and deploying a connector that ingests tobacco problem reports from the openFDA API. What You'll Learn Resources.

Streaming Data at Scale with Strategic Cloud Partners | Life Is But A Stream Podcast

Strategic partnerships don’t work without trust. And in the data streaming world, trust begins with transparency. In this episode, Elena Cuevas, Sr. Manager of Cloud Partner Solutions Engineering at Confluent, joins Joseph Morais to unpack what it takes to collaborate with hyperscalers like AWS, Google Cloud, and Microsoft Azure. From managing competitive overlaps to future-proofing enterprise data architectures, Elena shares her battle-tested strategies for driving alignment across complex stakeholder ecosystems.

How to Test Your Mainframe With Open Source Tools

In the past, mainframe users have been limited to expensive legacy tools, but today, it's possible to embrace agility, and security with integrating open source tools into the mainframe.Watch this how to video to see how mainframe users can also get on board to achieve superior test coverage, by testing more often, and throughout the whole development cycle.

How a CDAO goes from baseball to insurance with Don Vu - New York Life

Step inside the world of data innovation as Cindi Howson talks with Don Vu, SVP and Chief Data and Analytics Officer at New York Life. They'll reveal how a 180-year-old institution is leveraging cutting-edge AI to make experiences proactive and intelligent. Hear how New York Life utilizes their innovative "GuideMe" tool to supercharge agent and client financial planning, tackles the "last mile problem" in data operationalization, and ensures data quality is paramount for both structured and unstructured data.

Understanding AI Observability: Improve Efficiency, Security & Costs

In this video, Jason Mattis breaks down the fundamentals of AI observability, explaining its crucial role in managing and optimizing generative AI systems. Learn about the three core pillars—data monitoring, model explainability, and diagnostics—and how mastering these can help your organization ensure data privacy, maintain model accuracy, manage costs, and enhance overall AI performance.