Query Databricks directly in Excel—business users skip one data-request queue

Databricks posted a demo of its Excel add-in. The scenario is very concrete: on the left is a “Warm-Up Jacket” transactions table in Excel, with date, store, region, city, state, product ID, and product name laid out in columns; on the right is the Databricks Add-in for Excel toolbar, with the data-access entry point right next to the table.

This add-in is focused on how data gets in. Whether Excel can analyze it is not the point. Many teams get stuck on repeated exports, manual filtering, and waiting for the data team's schedule. The add-in pushes these steps into Excel.

The demo mentions three features.

First, generate usable filter values to narrow the data range before import. You don't have to pull the full dataset first and then delete rows in the spreadsheet.

Second, reuse existing Databricks SQL queries. Queries already written in Databricks can be used directly in Excel, reducing one copy-paste and metric-definition drift.

Third, import data with custom functions, such as DATABRICKS.SQL and DATABRICKS.Table. The data still goes through Databricks' governance path, but lands in a spreadsheet business users are familiar with.

The full demo is on YouTube, 4:59:
https://youtu.be/GKQt543lGDg

Here's a judgment: what this type of add-in really changes is the data-access workflow—from queuing to self-service. Excel itself doesn't become more powerful. The data team takes on fewer duplicate requests, and business users wait one less round. The prerequisite is that permissions and governance are in place; otherwise you're just moving the mess into a spreadsheet. Databricks is a data platform, and the add-in moves the entry point forward, which makes sense. As for the actual experience, it depends on connection configuration, query performance, and spreadsheet size. The demo video only shows the import feature and does not explore these limitations.