ThoughtSpot on Snowflake Interactive Analytics

The phrase “Big Data” may be out of trend, but data volumes keep climbing–and so do expectations. It’s estimated that in 2026, the global volume of data is expected to exceed 221 zettabytes. With AI tools and agents making it easier to consume, the pressure is on to deliver faster, more responsive insights on massive datasets to more users than ever.

ThoughtSpot Sync

Stop hopping between tabs and bring your data insights directly into the tools your team uses every day. In this video, we explore ThoughtSpot Sync, a powerful feature that allows you to push live visualizations and data snapshots directly to Slack, Microsoft Teams, Google Sheets, and more. Whether you need to alert a team to a specific KPI or share a detailed CSV for further analysis, ThoughtSpot Sync automates the delivery of insights so your colleagues never miss a beat—even if they haven't opened ThoughtSpot.

Preparing for Agentic AI: Top Trends in Data and AI 2026 | Feat. Rory Blundell

As we move toward a future of autonomous agents, the biggest hurdle isn't the AI's intelligence—it’s the governance. In this segment of The Data Chief, Rory Blundell, CEO of @Graviteesource , explores the critical infrastructure needed to move agents from "experimental" to "enterprise-grade." Rory explains how the agentic era is fundamentally redefining API integration and why many organizations are hitting a "maturity wall." Learn how to build the security frameworks and management layers necessary to give your agents the power to act without compromising your brand’s trust or security.

Preparing for Agentic AI: Top Trends in Data and AI 2026 | Feat. Paul Baier

In 2026, the gap between companies "testing" AI and companies "running" on AI has become a chasm. In this segment of The Data Chief, Paul Baier, CEO and Co-Founder of @GAIInsights, explains why the honeymoon phase of Generative AI is over and the era of Agentic AI has officially arrived. Paul breaks down how leading enterprises are pulling ahead by moving beyond simple chatbots to autonomous agents that can plan, reason, and execute complex workflows. If you want to know how to reshape your enterprise operating model to stay competitive, this is the field guide you’ve been looking for.

The 85% Problem: Why Your Finance Team Spends Most of Their Time Not Doing Finance

Here's a statistic that should concern every CFO: according to 2024 research from Accenture, finance teams spend 85% of their time on data triage-gathering, validating, and reconciling numbers. Only 15% of their time goes to the strategic work they were actually hired to do. If that sounds familiar, you're not alone. The reality is that most CFOs today can't confidently answer a deceptively simple question: "Where did this number come from?".

What Does a Product Analyst Do? (And How to Succeed in the Role)

A product analyst helps teams understand how users interact with a product — and turns that data into decisions that improve growth, retention, and user experience. They sit at the intersection of: Instead of guessing what users want, product analysts rely on behavioral data to guide decisions.

How to Send Shopify Orders to Snowflake with AI-ETL

Every Monday morning, e-commerce analysts face the same frustrating ritual: export CSVs from Shopify, merge them in spreadsheets, clean the data, and pray nothing breaks before the weekly revenue meeting. This manual process wastes hours weekly per analyst while delivering insights that are already days old. Meanwhile, your competitors make real-time decisions based on live data flowing automatically into their analytics platforms.

How to Build SLAs for Real-Time Dashboards with AI-ETL

Your executive dashboard shows yesterday's data while your competitors make decisions with information that's minutes old. This gap isn't just an inconvenience—it's a competitive disadvantage costing businesses millions in missed opportunities, delayed responses, and stale insights. Service Level Agreements (SLAs) for real-time dashboards solve this problem by establishing measurable commitments for data freshness, accuracy, and availability.