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How to use ChatGPT with enterprise data

By Nick Barth

Updated on March 6, 2024

Integrating ChatGPT into your enterprise data analysis can enhance productivity, foster innovation, and streamline decision-making processes. With Deepnote, an interactive notebook platform, integrating ChatGPT for data analytics and collaborative projects becomes an accessible reality. Here's a guide on how to combine the power of ChatGPT with enterprise data in Deepnote.

Use cases for ChatGPT within Deepnote

In an enterprise setting, you can leverage ChatGPT within Deepnote for various applications:

Automating data analysis

Use ChatGPT to automate repetitive analytical processes by generating the required Python or SQL queries based on plain-English descriptions of the data insights needed.

Interactive reporting

Create interactive reports where ChatGPT assists in interpreting complex data visualizations or provides summaries of analytical findings in natural language.

Real-time collaboration

Facilitate smoother collaboration across teams with ChatGPT, where it acts as a virtual assistant within Deepnote, providing explanations, suggestions, and coding assistance on shared projects.

Enhancing data exploration

Use ChatGPT's ability to understand and generate human-like text to explore data through conversational interfaces, making complex data more accessible to cross-functional teams.

How to integrate ChatGPT in Deepnote

Here’s a step-by-step guide to integrating ChatGPT with your Deepnote environment:

1. Establish a communication channel

To interact with ChatGPT within Deepnote, set up an API that facilitates communication between the Deepnote notebook environment and ChatGPT. You might want to consider using OpenAI's GPT-3 API as the intermediary.

2. Ensure secure API integration

While you've indicated no primary security concerns, it's advisable to keep enterprise environment credentials and interactions secure. Use Deepnote's secret management feature to store API keys securely.

3. Build custom functions

Develop custom functions or utilize available Deepnote integrations that pass queries and command to ChatGPT. Capture the output and utilize it within your notebooks. These functions can enable ChatGPT to generate codes, explain data insights, or perform language translations.

4. Implement collaborative workflows

Set up workflows within Deepnote where team members can input queries to ChatGPT and share the responses. It’s imperative to maintain a structure that ensures that all team members can benefit from the integration.

5. Optimize the integration

Monitor the performance of ChatGPT in handling specific tasks. Refine and optimize the queries and integration points, so ChatGPT effectively assists with enterprise data analysis tasks.


Harnessing the strength of ChatGPT in Deepnote can revolutionize data handling in your enterprise. By following the guide above, you can improve data interaction and interpretation, make your analytical processes more efficient, and foster a collaborative environment where every team member can utilize the power of AI.

Remember that while security may not be a concern in your current setup, practicing safe API usage and access control is always recommended. This ensures that your enterprise data integration remains robust and secure in all aspects. Enjoy the synergy between ChatGPT's AI capabilities and Deepnote's collaborative data science platform!

That’s it, time to try Deepnote

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