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How to Upload CSV or Excel Files to Azure Purview

Huda QurayshiHuda Qurayshi Sep 27, 2026 870 views

Question details

The user wants to know if and how CSV or Excel data dictionaries can be uploaded into Microsoft Purview for a business glossary or data catalog.

How to Upload CSV or Excel Files to Azure Purview
Product
Azure Purview
Device & OS
not provided
Scenario
Importing local spreadsheet data into an Azure Purview data catalog or business glossary.
Observed behavior
The user is looking for the correct procedure, as the exact import method depends on the specific metadata goals and Purview configuration.
Before you start

Ensure your CSV or Excel files are properly formatted with standard headers before attempting to import them into any data catalog system.

Solution 1Recommended

Consult the Microsoft Q&A Community for Targeted Purview Support

Because the exact procedure varies based on your specific goal (glossary terms vs. metadata), posting in the official Microsoft Q&A forum is the best approach to get accurate Azure guidance.

Azure Purview supports multiple ways to handle CSV and Excel files. The correct approach changes drastically depending on whether you are bulk-importing business glossary terms, mapping catalog metadata, or simply scanning a spreadsheet as a raw data source. By consulting the official community, you can get step-by-step instructions tailored to your exact file structure and Purview environment.

1
Navigate to Microsoft Q&A

Open your web browser and go to the official Microsoft Q&A website.

2
Create a New Question

Click the button to ask a new question and ensure you add the 'Microsoft Purview' tag so that Azure data governance experts will see it.

3
Provide Your Import Goals

Clearly state in your post whether you want to import glossary terms, load catalog metadata, or scan the spreadsheet as a data source.

4
Specify Configuration Details

Include your current Purview version, your intended destination within the catalog, and a brief description of your CSV or Excel file structure.

Consult the Microsoft Q&A Community for Targeted Purview Support
Template Preparation: If you are importing glossary terms, log into the Purview Governance Portal first and download the standard .csv template to ensure your file matches the required schema.
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Prepare Your Data Dictionaries with WPS Office

Before uploading your metadata to Azure Purview, use WPS Spreadsheet to seamlessly organize, format, and save your CSV or Excel files. WPS Office is a free, lightweight suite that offers full compatibility with Microsoft formats, ensuring your data is properly structured for complex data catalog imports.

  1. 1. Download and Install: Visit the official WPS Office website to download and install the free suite.
  2. 2. Open Your Data Dictionary: Launch WPS Spreadsheet and open your existing CSV or Excel file, or start a new blank template.
  3. 3. Format and Save: Organize your column headers to match Purview's schema, remove any unsupported special characters, and save the file in .csv or .xlsx format.
100% compatible with Microsoft Excel (.xlsx) and CSV file formats.Lightweight and fast, perfect for handling large data dictionaries without lagging.Familiar spreadsheet interface that requires zero learning curve.Completely free to use for everyday data organization and formatting tasks.
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Frequently Asked Questions

Can I import a business glossary into Azure Purview using a CSV file?

Yes, Microsoft Purview allows you to bulk import business glossary terms. To do this successfully, you must use the specific CSV template provided within the Purview Governance Portal to ensure your columns map correctly.

Why is my CSV file failing to upload to Microsoft Purview?

Upload failures typically occur if the CSV file does not strictly match the required template headers, contains empty mandatory fields, or includes invalid characters that Purview's parsing engine cannot read.

Does Microsoft Purview support scanning Excel (.xlsx) files?

Yes, Purview can scan Excel files as data sources if they are stored in supported connected storage locations, such as Azure Data Lake Storage or Azure Blob Storage, allowing it to extract schema metadata automatically.