Conversational analytics in BigQuery brings trusted agentic reasoning to everyone
Use Conversational Analytics in BigQuery to query data, run analyses, and generate reports using natural language on data in BigQuery and Lakehouse.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Where AI Capital Is Flowing: Insights From The Snowflake-Crunchbase Report
At Snowflake Summit 2026, Gene Teare from Crunchbase and Harsha Kapre, Director at Snowflake Ventures, discuss their joint report examining AI investment trends and capital formation in the data ecosystem. Learn how the market has evolved from 2021's broad exuberance to concentrated investment in AI-ready infrastructure, governance, and agentic applications. Discover what signals indicate a startup is truly enterprise-ready versus experimental, and explore the next phase of capital formation in the agentic AI economy.
Welcome to the Era of Action: A Message from Ketan Karkhanis
ThoughtSpot has been named a Leader in the 2026 Gartner Magic Quadrant for Analytics and Business Intelligence Platforms. We’re celebrating this milestone while building for tomorrow, as we shift from the Era of Reporting into the Era of Action. Hear a message from our CEO Ketan Karkhanis on what this shift means for our customers and partners, and how companies can win in this next era of AI BI.
AgentSpot Training Episode 7: Creating a Slack Bot
A Slack Bot allows your Agent to directly interact within your slack channels. In this video: Adding AgentSpot Slack App Connecting Agent to Slack Using Agent in Slack.
Synthesize the big picture and analyze trends with BigQuery's AI.AGG function
Learn to use BigQuery’s new AI.AGG function to analyze unstructured data such as logs and documents at scale.
Scaling Network Analysis for Fraud Prevention with BigQuery Graph
Data analysis at scale to identify hidden fraud and achieve transaction savings.
How AI Inference Is Reshaping Enterprise Infrastructure
Data center teams are skilled at solving familiar problems such as storage outages, missed forecasts, and late refresh cycles. These are known quantities. Teams have playbooks for them. But 2026 has brought a different kind of pressure. After years of enterprise AI investment concentrated almost entirely on model training, the industry has crossed a threshold: the workload that now defines AI infrastructure isn’t building models. It’s running them. Continuously. At scale. Every day.
ThoughtSpot June Release: Customize Your Agent
Check out what’s new in ThoughtSpot’s latest release! SpotterModel gets smarter: Build complex data models with AI formula suggestions and instant version rollbacks if you make a mistake. No stress, no lost work. Spotter Instructions: Fully customize Spotter’s persona, formatting rules, and strict guardrails. It says exactly what you want it to say—and nothing it shouldn't. Ad Hoc Analysis: Drop local files directly into Spotter for instant answers, or blend them safely with your governed enterprise data.
Collaborative BI That Drives Action: From Shared Insights to Shared Accountability
Here’s a scenario, and not an uncommon one either. A dashboard flags a margin drop on Tuesday morning. Someone from the Sales team adds a comment. Finance adds another. A colleague from Operations agrees the number looks wrong. By Friday, the issue is still open, and no one owns the fix. That is the gap in many business intelligence collaboration setups. The data was shared. The discussion happened. The decision never moved.
Agent development and AgentOps with BigQuery, ADK, and MCP
Join this session to learn about Agent Development Kit (ADK) and Model Context Protocol (MCP) integration methods that standardize how agents connect to your data while removing the need to build custom database connectors from scratch. Discover how to build agents with the ADK that accesses BigQuery for analysis, Google Maps for geospatial insights, and AlloyDB for transactions – all in a single workflow. Learn how to implement agent operations (AgentOps) for deep observability into both agent performance and cost with a single line of code.