Systems | Development | Analytics | API | Testing

Master Muze Charts - An Introductory Guide

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.

Leveraging ThoughtSpot and LLMs for Business Insights

- 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.

AI x Testing Leadership | Jaydeep Chakrabarty | Ask Me Anything

AI is not just changing how we test it's redefining how we lead. This high-impact AMA explores how testing leadership must evolve in an AI-first world. Whether you're managing a lean QA team or scaling quality across a large enterprise, the session offers frameworks and insight to help you lead, not just adapt, through transformation. What you'll take away: About Jaydeep Chakrabarty.

Ask Me Anything with Harinee Muralinath

AI tools are getting smarter, and many of them now have access to more than you realize. From test scripts to config files to internal APIs, what starts as "just a helper" can become a hidden risk. In this AMA, Harinee will share where things go wrong when tools are trusted too quickly. We’ll look at real examples, permission pitfalls, and ways to keep your systems safer. If you’re using AI in testing or automation, this session will help you ask better questions. Bring your curiosity and your concerns. Let’s talk about what your tools can do, and what they shouldn't.

BigQuery Migration Service: Validation and optimization

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.

What's the value of not going through an implementation alone?

Getting support means reaching value and impact in days instead of weeks or months. Professional services bring proven expertise that accelerates adoption and makes teams the heroes, not the ones struggling to figure everything out alone. — Mush Honda, Chief Quality Architect at Katalon Follow Katalon for more insights in our series!

AI in Action: Powering the Future of Testing | Xray Webinar

A quick overview of Xray Test Management - cutting-edge test management app for Jira. Xray is the leading Quality Assurance and Test Management app for Jira. More than 4.5 million testers, developers and QA managers trust Xray to manage 100+ million test cases each month. Xray is a mission-critical tool at over 5,000 companies in 70 countries, including 137 of the Global 500 like BMW, Samsung and Airbus.

Supercharge your LLM Using Production Data Context

Are your LLM coding agents (like Cursor or Claude Code) hallucinating fixes because they don't know what's actually happening in production? In this video, Matt from Speedscale shows you how to bridge the gap between your local IDE and live production traffic using the Model Context Protocol (MCP). Most observability tools just give you telemetry. Speedscale’s MCP server gives your agent the "inner workings" of actual API calls and payloads, so it can check its assumptions against reality. No more "vibe-coding" and hoping it works; let your agent find the 500 errors and rate limits for you.