awesome-data-definitions offers a large set of over 17,000 data definitions. These definitions help organize and standardize data across different industries. Whether you work in finance, healthcare, or data governance, the definitions guide you to keep data clear and consistent. This can improve how teams manage data models, create databases, or set up logical and physical data frameworks.
The collection is open source, meaning anyone can use or study it. It focuses on enterprise needs, so the definitions fit large, structured data systems. You do not need to know coding or complex technical terms to use these data definitions.
To run the collection on Windows, make sure your computer meets these basics:
- Windows 10 or later (64-bit preferred)
- At least 4 GB of RAM
- 1 GB free disk space
- Internet access to download files and updates
- Recommended screen resolution: 1280 x 800 or higher
No special software is needed beyond what Windows usually provides. The collection comes ready to use after download.
Follow these steps to download and run the awesome-data-definitions collection on your Windows machine.
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Open this link in your web browser:
GitHub Repository - awesome-data-definitions -
On the repository page, look for the green Code button near the top right.
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Click Code, then choose Download ZIP from the dropdown. This downloads the entire collection as a ZIP file.
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Once downloaded, open the file using Windows File Explorer.
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Right-click the ZIP file and select Extract All.... Choose a folder where you want the data definitions saved.
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After extraction, open the folder. Inside, you will find organized files and folders containing categorized data definitions.
The files may include text or spreadsheet formats, making it easy to browse through the definitions. You can open them with default Windows apps like Notepad or Excel.
Here is how to work with the definitions on your computer without technical skills:
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Open folders by double-clicking in File Explorer.
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Look for files with names related to your field (for example, “finance-data.csv” or “healthcare-terms.txt”).
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Double-click files to open them in the default app.
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You can read or search the text, copy definitions, or print them as needed.
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For easy navigation, some files include tables listing key terms, their meanings, and related fields.
These definitions help you understand common terms and organize data according to industry standards.
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Press
Ctrl + Fin the open file to open the search box. -
Type the word you are looking for.
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The app will jump to the term if it exists in the file.
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Highlight the text with your mouse.
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Press
Ctrl + Cto copy. -
Open your document or notes, then press
Ctrl + Vto paste.
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Open the file.
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Press
Ctrl + Pto open the print window. -
Select your printer and print only the pages you need.
If you have trouble opening or finding files:
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Make sure you extracted the ZIP file completely. Sometimes, files inside a ZIP cannot be opened directly.
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Use apps like Microsoft Excel or WordPad for spreadsheet or text files.
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If files seem corrupted, download the ZIP file again from the link.
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Ensure you have sufficient disk space on your computer.
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If links in the definitions do not open, check your internet connection.
The data definitions may be updated over time. To get the latest version:
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Visit the GitHub page again:
Update Link -
Download the newest ZIP file following the same steps as above.
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Replace the old folder with the new files on your computer.
Keeping the collection updated helps stay current with industry standards and new terms.
This collection is useful for data architects and engineers who want to build or improve databases and models. While this guide avoids technical details, here are some ways experts use the definitions:
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Importing terms into data modeling tools to standardize names.
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Matching definitions to company data for better data governance.
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Creating logical and physical data models using the provided terms.
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Mapping finance and healthcare data fields to the definitions for clarity.
If you are curious, explore the files and talk with your data team for deeper use.
