How conversational analytics removes the BI bottleneck

2026-04-22 · Source: Databricks · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Cloud Computing & IT Infrastructure · Depth: Intermediate, medium

Summary

Databricks' Global Head of Evangelism, Ari Kaplan, discusses the evolution of data analytics beyond traditional Business Intelligence (BI) and database solutions, focusing on the company's offerings, Genie and Lakebase. He highlights that while executives desire conversational data interaction, the breakdown occurs when insights lack a clear path to action. Genie, an AI-driven conversational analytics tool, allows non-technical users to query data in plain language, moving beyond fixed dashboards to enable real-time scenario planning and decision-making, as exemplified by Etihad Airlines. Lakebase, a modern transactional database, provides scalable data storage and management, capable of handling trillions of records and significantly reducing total cost of ownership, with some companies reporting up to 98% savings. The integration of Genie and Lakebase through Unity Catalog ensures data governance, consistent business definitions, and trust, which Kaplan identifies as the single biggest barrier to AI and data adoption among 20,000 surveyed customers.

Key takeaway

For Directors of AI/ML or VPs of Engineering evaluating modern data stacks, recognize that the competitive gap is rapidly widening. Prioritize solutions like Databricks' Genie and Lakebase that integrate conversational analytics with governed, scalable data infrastructure. This shift enables faster, data-driven operational decisions and automates complex tasks, moving beyond mere reporting to actively run the business on its data, or risk falling significantly behind competitors who are already adopting these capabilities.

Key insights

Actionable insights, not just trivia, drive business value from conversational analytics.

Principles

• Insight without action is just trivia.
• Humans remain critical for oversight and decision-making.
• Data governance builds trust in AI-driven analytics.

Method

Databricks' Genie enables conversational analytics by connecting to various data sources, including Lakebase, and applying business-specific definitions via Unity Catalog to provide governed, actionable insights.

In practice

• Use conversational analytics for real-time scenario planning.
• Implement robust data governance for consistent definitions.
• Fork database environments without data duplication for cost savings.

Topics

• Conversational Analytics
• Databricks Genie
• Databricks Lakebase
• Unity Catalog
• Data Governance

Best for: Director of AI/ML, VP of Engineering/Data, Executive

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Editorial summary, takeaway, and curation by AIssential. Original article published by Databricks.