The Scenario
You are a data analyst at a 200-person e-commerce company. It is Thursday afternoon and the ops director just messaged you in Teams: "Can you pull sales by region for Q1 and drop it in the shared workbook before the 4 PM planning call?"
You have Databricks access. But the SQL editor is in another browser tab, the table name is never quite what you remember, and once you run the query you still have to download the CSV, open it in Excel, fix the headers, and share the file.
The bad version of this afternoon:
- You open the Databricks SQL editor
- You search the catalog for the right table name, which is not what you thought
- You write the query, run it, fix a syntax error, run it again
- You download the result as a CSV
- You open it in Excel, reformat the date columns, add a totals row
- You upload the file to SharePoint and send the link
- The 4 PM call already started.
The fast version is one prompt in the workbook you are already looking at.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook that can call your Databricks SQL warehouse directly, so you never have to leave the workbook.
Open the SheetXAI sidebar and type:
Run this SQL on my Databricks warehouse: SELECT region, SUM(revenue) AS total_revenue, COUNT(order_id) AS order_count FROM sales.orders WHERE order_date >= '2026-01-01' AND order_date < '2026-04-01' GROUP BY region ORDER BY total_revenue DESC — and write the results into the Revenue tab of this workbook starting at row 2, with headers Region, Total Revenue, and Order Count in row 1.
SheetXAI calls your Databricks SQL warehouse, runs the query, and writes the result set into the Revenue tab. The ops director gets a link to a populated workbook.
What You Get
The Revenue tab, populated with the query results:
- Row 1 — clean headers: Region, Total Revenue, Order Count
- Rows 2 onward — one row per region, sorted by revenue descending
- Results directly from the warehouse — no intermediate CSV download
The query runs against live warehouse data. If revenue numbers updated this morning, the workbook reflects that.
What If the Data Is Not Quite Ready
Most real queries are more specific than a clean aggregate. SheetXAI handles filtering, reshaping, and cleanup in the same prompt.
When the region names in the warehouse use internal codes
The warehouse stores "R-WEST" and "R-EAST" but the ops team's workbook templates always say "West Region" and "East Region."
Run this SQL on my Databricks warehouse: SELECT region, SUM(revenue) AS total_revenue FROM sales.orders WHERE order_date >= '2026-01-01' GROUP BY region — write the results into the Revenue tab. Then replace "R-WEST" with "West Region," "R-EAST" with "East Region," and "R-CENTRAL" with "Central Region" in column A before displaying.
When the ops director wants only regions above a revenue threshold
They want the planning call focused on meaningful markets, not the tail.
Run the Q1 sales-by-region query on my Databricks warehouse. Only include regions where total revenue exceeds $500,000. Write the filtered results into the Revenue tab with headers in row 1 and a note in cell D1 saying how many regions were excluded.
When the query needs a join to a second table for context
The ops team also wants the top product category per region, which lives in a different Databricks table.
Run this SQL on my Databricks warehouse: SELECT o.region, SUM(o.revenue) AS total_revenue, p.top_category FROM sales.orders o JOIN analytics.region_summary p ON o.region = p.region WHERE o.order_date >= '2026-01-01' GROUP BY o.region, p.top_category ORDER BY total_revenue DESC — write the result into the Revenue tab with headers Region, Total Revenue, and Top Category.
When you want the query result plus a short written analysis in one operation
The ops director did not just want the numbers. She wanted a summary paragraph explaining which regions grew versus Q4.
Run this SQL on my Databricks warehouse for Q1 2026: SELECT region, SUM(revenue) AS q1_2026 FROM sales.orders WHERE order_date >= '2026-01-01' AND order_date < '2026-04-01' GROUP BY region. Also run the same query for Q4 2025 (order_date >= '2025-10-01' AND order_date < '2026-01-01'). Write both result sets side by side in the Revenue tab with Q1 and Q4 columns. Then write a three-sentence analysis in cell E1 identifying which regions grew, which declined, and the biggest change.
The pattern: instead of downloading a CSV and then thinking about the numbers separately, you ask for the query and the analysis in the same prompt.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook, then ask it to run a SQL query against your Databricks warehouse and populate the workbook with results. The Databricks integration is included in every plan. For more Databricks workflows, see how to export a Unity Catalog table inventory to Excel or the Databricks in Excel overview.