Evolution of BI: Smarter Insights, Faster Decisions

We will dive into the practical application of Machine Learning (ML) and Natural Language Processing (NLP) within your data stack. Learn how to leverage automated insights to uncover hidden patterns, use predictive forecasting to anticipate market shifts, and deploy conversational AI that allows non-technical stakeholders to talk to their data. By integrating AI into your BI strategy, you move from reactive reporting to a proactive culture where insights are discovered in seconds and decisions are backed by predictive precision.

Key Takeaways
Utilize AI to automatically surface trends, outliers, and drivers in your data without manual slicing and dicing.

Move from historical snapshots to future-looking models using built-in ML visuals for forecasting and key influencer analysis.

Bridge the gap between insight and execution by embedding AI-driven recommendations directly into business workflows.

Utilize AI to automatically surface trends, outliers, and drivers in your data without manual slicing and dicing. Move from historical snapshots to future-looking models using built-in ML visuals for forecasting and key influencer analysis. Bridge the gap between insight and execution by embedding AI-driven recommendations directly into business workflows.