Deepnote

Deepnote is a next-generation data workspace designed for analytics and data science teams. It revolutionizes the traditional notebook experience by integrating powerful AI capabilities, real-time collaboration, and a seamless multi-language environment. Unlike legacy tools like Jupyter, Deepnote is a cloud-native platform that eliminates setup hassles and fosters teamwork. It allows users to connect to over 50 data sources, write and execute Python, SQL, and R code in the same notebook, and instantly visualize results. With its AI copilot, powered by GPT-4o, users can generate, debug, and explain code, or even perform entire analyses by simply describing their goals in natural language. This makes complex data tasks faster for experts and more accessible for beginners. Deepnote transforms static analyses into dynamic, shareable data apps and dashboards, complete with interactive inputs and scheduled updates, making it an end-to-end solution for moving from raw data to actionable insights.

How to use Deepnote

Getting started with Deepnote is straightforward and requires no local installation. 1. **Sign Up:** Create a free account on the Deepnote website. Since it's browser-based, you can start immediately. 2. **Create a Workspace:** Organize your work by creating a workspace for your team or project. You can create folders to manage different analyses. 3. **Connect Your Data:** Integrate with your data sources in seconds. Deepnote supports over 50 connectors, including Snowflake, BigQuery, PostgreSQL, Amazon S3, and you can also upload CSV files directly. 4. **Start a Notebook:** Create a new notebook. You can use a combination of code blocks (Python, SQL, R), text blocks (Markdown), and no-code chart blocks. 5. **Leverage AI:** Use the AI assistant to accelerate your workflow. Type a prompt to generate SQL queries, write Python code for analysis, create visualizations, or debug errors. The AI is context-aware of your data schema and existing code. 6. **Collaborate in Real-Time:** Invite teammates to your notebook by sharing a link. Work together simultaneously, leave comments on specific cells, and review changes with version history, just like in Google Docs. 7. **Build and Share:** Turn your notebook into an interactive data app or dashboard. Arrange your cells, hide code blocks, and add input widgets like sliders and dropdowns. Share your live, interactive report with stakeholders with a single click.

Core Features of Deepnote

• AI-Powered Workspace: Powered by GPT-4o, it offers AI code generation, completion, debugging, and automated analysis from natural language prompts.
• Collaborative Notebooks: Real-time, Google Docs-style collaboration with commenting, version history, and granular permissions.
• Multi-Language Support: Seamlessly combine Python, SQL, and R in a single notebook environment.
• Interactive Apps & Dashboards: Turn notebooks into polished, interactive data applications and dashboards with no-code UI elements.
• Extensive Integrations: Natively connect to over 50 data warehouses, databases, and file storages like Snowflake, BigQuery, Redshift, and S3.
• Scheduled Runs & APIs: Automate your workflows by scheduling notebooks to run hourly, daily, or weekly, and deploy notebooks as production-ready APIs.
• Scalable Cloud Hardware: Access powerful cloud machines, including high-memory CPUs and GPUs, on-demand without any setup.
• Enterprise-Grade Security: SOC 2 Type II, HIPAA, and GDPR compliant, with features like SSO, RBAC, and options for private deployments.

Use Cases for Deepnote

Deepnote is versatile and supports a wide range of data-related tasks: Business Intelligence: Building interactive sales reports, customer 360 dashboards, and analyzing NPS data. Data Science & Machine Learning: Developing churn prediction models, implementing lead scoring algorithms, fine-tuning LLMs like LLaMA 7B, and performing protein visualizations. Data Analytics: Conducting A/B test evaluations, analyzing AWS costs, and performing quick data explorations. ETL & Automation: Creating pipelines to sync data between services (e.g., Salesforce to Notion) and scheduling regular data processing jobs. Education & Research: Providing a zero-setup, collaborative environment for teaching data science courses and conducting research projects.

Advantages of Deepnote

Deepnote offers significant advantages over traditional tools. Its **AI-first approach** dramatically increases productivity for all users, from analysts to scientists. The **cloud-native, collaborative environment** removes friction in teamwork, eliminating environment setup and version control issues. By **unifying the entire data workflow**—from data connection and exploration to building and sharing interactive apps—it creates a single source of truth and accelerates the path to insight. Its **security and scalability** make it suitable for both small startups and large enterprises, ensuring data is protected and compute resources are always available. Finally, its **freemium model and free Education plan** make powerful data tools accessible to everyone.

Pricing and Plans

Deepnote offers a tiered pricing structure to suit different needs:

• Free Plan: Designed for individuals and small teams, it includes up to 3 editors, 5 projects, unlimited basic machines, and limited AI features.
• Pro Plan ($9/editor/month): Aimed at individual professionals, this plan offers unlimited projects, full Deepnote AI capabilities, background execution, scheduled notebooks, and more powerful machines with monthly compute credits.
• Team Plan ($39/editor/month): Built for data teams, it includes everything in Pro plus unlimited viewers, premium integrations, a 30-day revision history, and significantly more compute credits.
• Enterprise Plan (Custom Pricing): For large organizations with advanced security and support needs. It offers custom contracts, priority support, SSO, audit logs, single-tenancy deployment options, and volume discounts.
• Education Plan: 100% free for students, teachers, and researchers, providing most of the features of the Team plan.