You ask your agent a question. The answer is slightly off. You point out the gap. Spotter fixes it, and that fix doesn't disappear when the session ends. Your team doesn't re-explain the same thing tomorrow. The next analyst doesn't start from scratch. The correction stays, and the work gets better from here. That's what memory makes possible. Not just for you. For everyone who comes after.

Learn what Debezium is, how its CDC architecture and connectors support MySQL and SQL Server, and which of the three deployment modes fits your pipeline.

Your data integration team just asked: "Should we use MCP or REST APIs?" The answer is yes to both. With the ETL market reaching $10.24 billion in 2026 and projected to grow to $21.25 billion by 2031, understanding when to leverage each technology determines whether your AI agents can autonomously adapt to changing data needs or require manual code updates for every new integration.

Your organization invested heavily in a data warehouse, yet business users still wait days for answers to simple questions. The disconnect between where data lives and who needs it remains one of the persistent challenges in enterprise analytics. With 95% of AI pilots failing due to poor data foundations and accessibility issues, companies need a standardized way to connect AI agents to their existing data infrastructure.

The future of data analytics and AI education has just become even more accessible. The Qlik Academic Program is excited to announce a major upgrade to Qlik Product licenses available for educators and students worldwide. Participants in the program will now receive access to Premium Qlik Cloud Analytics and Premium Qlik Talend Cloud, providing an even more powerful environment for teaching, learning, and innovating with data.

The goal is not complicated to describe. The CEO opens a dashboard, asks a question about regional margin for Q2, drills through to the underlying journal entries, and gets the answer in seconds, without asking anyone. No email to the controller. No waiting until Thursday. No 'let me come back to you on that.' Every CFO who has sat through a pitch for a data platform has been shown this vision. Most of them believe it is achievable. A meaningful number have actually achieved it.

It is Monday morning. Your strongest FP&A analyst opens their laptop and starts pulling the SAP export. They clean it in Excel, cross-reference it against last month's version, and flag the columns that have shifted format again. Tuesday they pull the Dynamics export from the German entity and begin reconciling the two. Wednesday the Polish subsidiary data has not arrived. They chase the local accountant, wait, chase again.

I spend my days helping organizations modernize analytics to drive tangible business outcomes and liberate analytics teams from legacy processes. At this year’s Snowflake Summit ’26, I had the pleasure of sitting down with AJ Subbarao, Director of Business Intelligence & AI at Intuitive Surgical (ISRG).

The plan that fits your workflow is rarely the one you land on if you shop the pricing page first.

You’ve heard the pitch: AI is going to revolutionize finance. It’s going to write your variance commentary, spot anomalies before you do, answer questions about your data in plain English, and free your team from the drudgery of month-end prep so you can focus on what actually matters: strategy, decisions, and moving the business forward. It’s easy to see why you’d believe the hype.