Ryan Green kicks off the new year with the latest updates across Snowflake and the AI Data Cloud. Learn about three Snowflake capabilities now generally available, including Interactive Analytics on AWS, Snowpark Connect for Apache Spark, and next-generation Snowpipe Streaming across AWS, Azure, and GCP.

- Struggling to manage large datasets in Google Sheets while trying to run high-level BI initiatives? In this video, we demonstrate how to seamlessly bridge the gap between your Google Drive and ThoughtSpot using Analyst Studio. We walk you through the entire end-to-end workflow: from connecting a Google Sheet via URL to building a data model and visualizing your insights in real-time. Learn how to automate your data pipeline so that every update in your spreadsheet—like changing a client’s industry or adding new leads—reflects instantly in your ThoughtSpot Liveboards.

Go beyond standard dashboards with Muze, the data visualization library that brings a "grammar of graphics" approach directly into ThoughtSpot. Starting in version 10.15, Muze is available as a native chart option, allowing you to build highly interactive, code-level visualizations without leaving your browser. What’s Covered: Whether you are looking to learn the technical side of custom visualizations or want to see the platform in action, we have the resources to help you succeed.

- Building a prototype is easy—but scaling reliable, secure AI is the real challenge. In this demo, we show you how to move past basic chat and into the era of Agentic AI with the ThoughtSpot MCP (Model Context Protocol) Server. The MCP Server acts as a bridge between your data and external LLMs like Claude, OpenAI, and Gemini. It doesn't just answer questions; it reasons through your data model to automatically generate governed, mission-critical Liveboards.

You’ve moved your data to Google Cloud. Now it is time to make sure it’s accurate, secure, and cost effective. This video concludes our migration series by focusing on the critical steps following data transfer from Databricks, Teradata, Snowflake, Cloudera and many other platforms. You’ve moved your data to Google Cloud. Now it is time to make sure it’s accurate, secure, and cost effective. This video concludes our migration series by focusing on the critical steps following data transfer from Databricks, Teradata, Snowflake, Cloudera and many other platforms.

Andy Steinmann of MarketAxess shares how access to Apache Kafka experts—not just software—became the turning point in MarketAxess’ shift to Confluent Cloud.