Systems | Development | Analytics | API | Testing

Banks and credit unions face mounting pressure to modernize operations, elevate member experiences, and keep pace with regulatory demands. Discover how banks are delivering an agile data strategy using Qlik and Snowflake and improve member service, streamline operations, and manage compliance changes. Download our joint ebook and learn:→ How to build a future-ready data architecture→ Ways to drive accuracy and faster decision-making→ How to deliver timely, personalized member experiences→ Practical strategies you can implement right away.

Most marketing teams track traffic and leads, but rarely connect the two to understand whether their content is attracting the right audience. In this walkthrough, Rick Kranz, Director of the AI Marketing Lab, demonstrates a powerful weekly growth system that cross-references website traffic, Google Search Console data, and CRM leads to identify which content truly drives ideal customer profile (ICP) engagement.

Business analytics has changed. Now, it answers back. Meet Databox AI, AI-powered analytics for teams that need answers now. Ask your data anything with Genie, your AI analyst. Don’t just see numbers—understand what changed with AI Performance Summaries. Bring your data into your favorite AI tools with Databox MCP.

In this video, Dipankar breaks down how Apache Iceberg works under the hood - starting from the limitations of Hive-style tables to why Iceberg was built in the first place. He covers: Why Hive-based tables break at scale (Netflix example) How object storage changes the problem (S3 behavior, listing, throttling) Iceberg architecture (catalog, metadata, snapshots, manifests, data files) How query planning works step by step Why Iceberg is a specification — not an execution engine.

Every company has an AI roadmap. Very few have the data infrastructure to execute it. At Hevo Data, we've spent 8 years building pipelines that are reliable, simple, and transparent so 2,000+ data teams can build without second-guessing their data. We sat down with Manish Jethani, Amit Gupta, and Scott Husband to talk about what comes next. If your data isn't AI-ready, your roadmap stays a roadmap. We've re-engineered the platform to serve as the context engine your AI vision actually runs on. Because the models are only as good as the data underneath them.