Row Zero now integrates with Databricks Genie and Snowflake Cortex Analyst, making it possible to query warehouse data using natural language.
Row Zero users could already analyze data from Snowflake and Databricks using SQL queries and shared Data Sources. With Genie and Cortex Analyst, Row Zero users can now ask questions like:
What were total bookings by region last quarter?
Row Zero will use Genie or Cortex Analyst to translate those questions into warehouse queries and return the results directly to a spreadsheet for further analysis.
Governed answers, powered by your semantic layer
Natural language access to data is only useful if the answers are consistent and grounded in your organization's business definitions.
That's why Row Zero's integration with Genie and Cortex Analyst relies on the semantic layer configured in your data platform. Rather than generating ad hoc definitions of business metrics, queries are grounded in the governed models and logic your organization has already established.
This ensures that metrics such as bookings, revenue, customers, and pipeline remain consistent across teams and tools, even when accessed through natural language.
From questions to analysis
Most people don't start with a request for data. They start with a business problem.
They may be preparing a quarterly business review, investigating a change in performance, or trying to understand what's driving a particular trend. Answering those questions often requires both retrieving data and analyzing it. With Genie and Cortex Analyst integrated into Row Zero, users can do both from a single workflow.
When warehouse data is needed, Row Zero can use Genie or Cortex Analyst to generate the appropriate query and import the results into a connected table. From there, analysis can continue directly in the spreadsheet. Users can explore the data themselves using formulas, pivot tables, and charts, or ask the AI Agent to perform additional analysis, generate visualizations, and answer follow-up questions.
The result isn't just an answer, it's a living artifact that can be audited, edited, and shared with others.
Example: preparing a quarterly business review
Consider a sales operations manager preparing a quarterly business review.
They start by asking:
Help me prepare a quarterly business review. Analyze customer bookings for last quarter. What are trends by region? What factors drove those trends?
Row Zero determines what data is needed, uses Databricks Genie or Snowflake Cortex Analyst to query the warehouse, and imports the results into a connected table.
From there, the AI Agent performs its analysis directly in the spreadsheet, creating pivot tables, calculations, charts, and summaries that the manager can review, edit, and build upon.
Because the data, calculations, visualizations, and AI-generated outputs all live in the same place, the work remains transparent and easy to review. Team members can open the spreadsheet, validate findings, add context, and build on the analysis without recreating it elsewhere.
Getting started
Databricks Genie and Snowflake Cortex Analyst make warehouse data easier to access. Row Zero turns those answers into analyses that teams can audit, refine, and share.
Together, they combine governed warehouse access with the collaborative flexibility of a spreadsheet.
Learn how to configure Genie and Cortex Analyst in Row Zero here.
