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title: Welcome to Deepnote
description: Deepnote is a workspace for data analysis with Python, SQL, and no-code tools. It connects to over 50 data sources and includes AI assistance, code editing, and app publishing.
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---

Watch this 5-minute demo for an introduction to Deepnote.

<iframe width="720" height="405" src="https://www.youtube.com/embed/mLPUNo4O7aA?si=DwlP2Cts1pPVYvfW" title="YouTube video player" frameBorder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" allowFullScreen></iframe>

## Why data teams use Deepnote

### 1. Work in one notebook

![Deepnote_Infographics.png](../assets/docs/BVxG2tMFTzCSmgwqILlM.webp)

Deepnote's cloud environment lets team members edit notebooks together, leave comments, and review changes through version history.

Use [SQL blocks](https://deepnote.com/docs/sql-cells) with Python and R in the same notebook.

Connect the notebook to more than 50 [data sources](https://deepnote.com/integrations), including Snowflake, BigQuery, and Postgres.

No-code blocks let team members create charts and inspect data without writing Python.

### 2. Work with Deepnote AI

Deepnote AI processes notebook code, text, and variable metadata through model providers, including database schema for SQL AI. You share block outputs, which can include row-level data, only when you turn on **Provide access to block outputs**. It writes suggestions into notebook blocks, where you can inspect the code and its results. See [AI data privacy](ai-data-privacy#what-about-outputs).

![AI.png](../assets/docs/GXT55Lu8RKuMoFygbDPN.webp)

Use [Deepnote AI](https://deepnote.com/docs/deepnote-ai) to generate, explain, or correct code. Choose a model from Anthropic's Claude or OpenAI's GPT families, or use the **Automatic** option.

[AI code completion](https://deepnote.com/docs/ai-code-completion) suggests code as you type based on the notebook context.

[Deepnote Agent](https://deepnote.com/docs/deepnote-agent) can create and edit blocks, run code, inspect outputs, and use your Deepnote MCP integrations.

### 3. Publish a data app

Describe a dashboard or tool, and Deepnote Agent builds it as a [data app project](/docs/data-app-projects) backed by your notebook, or as a [Streamlit app project](/docs/streamlit-app-projects). Apps published from notebook blocks are deprecated. Browse the [Deepnote Explore gallery](https://deepnote.com/explore) for examples.

![App.png](../assets/docs/eKZQkqZ3THqjoKFjgTTF.webp)

Arrange charts and inputs in columns to control the app layout.

Choose which input, text, code, and SQL blocks your audience can see.

Add input blocks so your audience can filter and explore the data.

If you encounter any issues, please contact [help@deepnote.com](mailto:help@deepnote.com).