This week, we had a chat with one of our enterprise customers about their thoughts on AI inside their Yellowfin environment. They’re currently running version 9.15 and use Yellowfin as the primary BI layer inside their app.

Every team in your company has the same problem: they need answers from data, but getting them is never fast. Marketing wants to know which campaigns are working. Sales wants to know which deals are stalling. Leadership wants to know if the business is on track. Each team asks different questions, but they all end up in the same place—waiting for someone else to pull the numbers. What if your teams could just ask questions and get answers instantly? That’s what Databox MCP enables.

The dashboard was supposed to set your data free. Instead, it became a beautiful prison. You built the perfect visualization. Metrics aligned, charts polished, filters configured. Then someone asked a follow-up question, and suddenly you were back in the queue, waiting for an analyst to build another report. Dashboards are like printed maps in the age of GPS. They show you where things are at a specific moment. But they can’t reroute when conditions change.

Determine the exact data lakehouse capabilities you’ll need for your use case, and which vendors offer them.

You've outgrown Excel for consolidation. But what comes next? Anaplan starts at $200K+ - and still assumes your data is already clean. Your data team wants to build something custom - but "three months" always becomes twelve. And every vendor says they're the answer. This guide compares every realistic consolidation path side by side. Real costs, real timelines, real trade-offs. Including when staying with Excel is still the right call.

The AI revolution in finance is no longer a question of “if” but “how fast” and “how responsibly.” While our previous posts explored AI auditability frameworks, agentic workflows that transform finance operations, and building AI native Finance teams, today’s CFOs face an equally critical challenge: successfully navigating the complex and rapidly evolving landscape of AI compliance.