The Fifth Elephant 2025 Winter Edition

As AI becomes central to analytics workflows, many teams try to let LLMs query databases directly—only to find that raw tables lack the semantics AI needs. The result: hallucinated KPIs, ambiguous joins, inconsistent definitions, invalid SQL, and costly full-table scans.

This talk presents a better approach: a SQL-based metrics layer that acts as the semantic boundary between AI and data. We’ll explore why metrics—not tables—are the smallest meaningful unit of analytical reasoning, and why SQL is the ideal language for defining them. We’ll look at the which OLAP engines can be used to enable sub-second metric iteration and how the metrics layer becomes the foundation for conversational analytics.

Attendees will learn best practices for metric governance, security and access control, AI-assisted modeling, and preventing ungoverned KPI creation. We’ll introduce Rill’s metric-based semantic architecture, security policies, and MCP tools that allow AI agents to safely discover, query, and explain governed metrics—without ever exposing raw tables.

A live demo will close the session, showing how AI can reliably answer complex business questions using governed metrics with speed, determinism, and explainability.

You’ll walk away with:

• A blueprint for a SQL-based metrics layer that both AI and humans can interact with
• Best practices for governance, versioning, and KPI approval workflows
• A deeper understanding requirements of conversational analytics
• Strategies for securing data access when AI agents are in the loop
• Techniques for using AI responsibly in metric design and modeling
• A working example of how Rill’s SQYAML + MCP tooling creates safe, reliable AI workflows

Bio:

Nishant Bangarwa is the Co-Founder and Head of Engineering at Rill Data, where he leads the development of Rill’s open-source, high-performance, AI-native BI application—an alternative to legacy business intelligence tools, powered by modern analytical databases and a BI-as-Code workflow that delivers sub-second insights at scale.

Prior to Rill, Nishant worked on large-scale analytics systems at Cloudera and Metamarkets, and has contributed to several major open-source projects, including Apache Druid, Apache Calcite, and Apache Hive. His work has focused on advancing the state of the art in data infrastructure, real-time analytics, and metric-driven decision systems.

Here is a link to elevator pitch -
https://docs.google.com/presentation/d/1Krn2XGpgdrZ6Uo9B25fnfG5Tyi9hsISZd7QDE836OI0/edit?usp=sharing