Databricks Excel Add-in Simplifies Data Access

Databricks launches an Excel Add-in, allowing business users governed access to lakehouse data without SQL, simplifying analysis and ensuring data consistency.

Databricks logo next to Microsoft Excel logo, symbolizing the integration.
The Databricks Excel Add-in connects the lakehouse to familiar spreadsheet tools.

Databricks is streamlining data access for business users with its new Databricks Excel Add-in, now in public preview. This tool aims to bridge the gap between the company's lakehouse architecture and the ubiquitous spreadsheet software that remains central to many daily business analyses.

Traditionally, connecting Excel to the lakehouse has involved complex configurations and manual steps, often requiring IT intervention. This friction point has led to outdated data extracts and duplicated datasets, hindering efficient decision-making. The new add-in promises a simpler, governed approach.

No SQL, Just Spreadsheets

The core value proposition is enabling business users to import and analyze Databricks data directly within Excel without needing to write SQL queries or manage ODBC drivers. Built on Databricks SQL and Unity Catalog, the add-in brings live, governed lakehouse data and curated business semantics into a familiar interface.

Setup is reduced to a few clicks, drastically lowering the barrier to entry for finance, operations, and other business teams. Users can select and filter Databricks tables and Unity Catalog metric views using a point-and-click UI. This allows for the creation of native Excel pivot tables directly from governed lakehouse data.

Data teams can define business metrics once using Unity Catalog metric views, ensuring consistency across Excel and other analytics workflows. This approach replaces fragmented semantic layers and reduces the risk of data duplication and metric drift.

Users can refresh data to keep spreadsheets current and access existing Databricks Workspace queries. The add-in also offers the option to write and save SQL queries for reuse, catering to more advanced users.

This move democratizes data access for business stakeholders, ensuring they consistently work from trusted, up-to-date business semantics. It also allows data teams to enforce Unity Catalog permissions, lineage, and governance more effectively, reducing the burden of ad-hoc analysis requests.

The public preview includes core functionalities such as selecting tables and metric views, executing custom functions, manual refresh, and creating pivot tables. Future enhancements are planned, including scheduled refresh and AI integrations, further enhancing the experience for Databricks for business users.

Getting started is straightforward: the add-in is available via the Microsoft Office Marketplace or for manual download. Administrators can deploy it centrally, while individual users can install it directly in Excel across web, Windows, and macOS.

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Daniel Singer

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.