Plotly is based on Tioh’tia:ke, commonly known in English as Montreal Island, in Kanien’ke-há:ka, the “Place of the People of the Flint” (the Kanien’kéha).

Plotly is committed to making the tech industry more accessible to people from different cultures, as well as using and encouraging the use of our technology for anti-racist efforts. For our complete land acknowledgement and resources to learn about settlement and contribute to Indigenous activism, visit our About Us page.

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Write and execute Python code with Dash Enterprise's onboard code editor, 100% in the browser. No downloads or installation required.

DASH ENTERPRISE

Data App Workspaces

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Bring Python into your organization at massive scale with Data App Workspaces, a browser-based data science environment for corporate VPCs. Data App Workspaces are an ideal IDE to securely write and run Dash apps, Jupyter notebooks, and Python scripts.

 
With no downloads or installation required, Data App Workspaces make new team members productive from Day 1.

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A dream IDE for data science and model development

We spent a year perfecting our ideal data science IDE, building on the Eclipse Foundation's excellent Theia project. The result is a cloud IDE that is purpose built for ML model development, data science, and data visualization, without any compromises. 100% in the browser. No downloads or installation required. Data App Workspaces are an instant data science environment for your VPC.

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Our team has been using Jupyter notebooks for over a decade. The creator of Jupyter was Plotly's first advisor, and Plotly was the first corporate sponsor of nteract. We're champions for the Jupyter notebook products and community.

With Data App Workspaces, you can bring Jupyter notebooks into your corporate environment through Dash Enterprises's secure, scalable platform.

To create Dash apps within Jupyter notebooks (e.g. classic Notebook, JupyterLab, Visual Studio Code notebooks, nteract, PyCharm notebooks, etc.), please see Jupyter Dash.

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Once you've developed a model in Jupyter notebook, you can build a Dash UI for the model and deploy in to Dash Enterprise, all without leaving your Data App Workspaces. Once deployed, the rest of your company can access and run the model through your Dash app UI.

The Dash app above dynamically bins 42 million records using Python's Vaex library.

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Data App Workspaces bring Python scripting and notebooks to the enterprise environment through corporate authentication, a Secrets Manager, and easy installation on Azure, GCP, or AWS.

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Each Data App Workspaces runs in its own isolated Docker container for optimum performance, security, and customizability. Managing and scaling these Docker containers is automatic. The Docker architecture allows each Workspace to have its own notebooks, scripts, data files, and package dependencies without affecting other Workspaces or Dash apps running on Dash Enterprise.

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Data App Workspaces have a fully functional terminal where you can install new Python or R packages, run shell scripts, and launch Dash apps.

In this screen recording, the user adds Tensorflow to their Workspaces environment through the built-in terminal, then launches a Dash app.

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Data App Workspaces support first-rate autocompletion, so you can spend less time referencing documentation and debugging typos.

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Data App Workspaces already ships with dozens of plugins to optimize your development experience, and we're adding more each month. Plugins already enabled include:

Viewing CSV or Excel files in an editable table

Most VSCode plugins will work with Data App Workspaces. Get in touch if there is a plugin that you'd like to see!

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Workspaces run on servers in your corporate network enabling data scientists access to network-secured data stores and APIs. Run multiple Dash Enterprise platforms in different networks to give finer grained control to networked data stores without compromising security and without expanding network access to individual laptops.

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Data science packages, database drivers, and production-grade Dash apps run best on Linux. Data App Workspaces run in secure, isolated Linux-based containers that is accessible in an IDE in the web browser. This means that you can continue to run Windows on your workstation while writing code on a Linux operating system via your browser.

With deployed Dash Applications running the same operating system as Workspaces, you'll spend less time reconciling the differences between production and development.

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Every developer has struggled with reconciling the differences between a development environment and their production environment. Subtle differences between networking, operating systems, Python packages, database drivers, virtual environments, CPU & memory and more cause a myriad of difficult-to-debug issues when bringing your application into production. Further, many data scientists's development environments differ from one another causing friction when sharing apps and projects among a team.

In Data App Workspaces, the Docker-based development environment is run on the same network and inside identical Docker containers as deployed applications. All of the Dash Enterprise features like Job Queues, Onboard Redis and Postgres Databases, PDF Reporting, and Low-Code packages are available. You'll never run into issues where an app works in development but fails in production.

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Creating a Jupyter notebook in Data App Workspaces

Watch how a Jupyter notebook with Plotly Express charts in created in Data App Workspaces.

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Creating a Dash app in Data App Workspaces

Watch how a Dash app is created & deployed in Data App Workspaces.

Write and execute data science code within secure Docker containers.

Develop data science, AI, and ML algorithms in Jupyter notebooks.

Develop & deploy Dash apps from start to finish, entirely on Dash Enterprise.

Upskill Python beginners quickly by not requiring a desktop IDE.

Sign up for a live demo to learn more about our Dash Enterprise offering.

JOIN THE THOUSANDS OF INNOVATORS THAT ARE ALREADY BUILDING WITH DASH ENTERPRISE.

Workspaces is an onboard code editor from Dash Enterprise. Easily write and execute code for data apps. No additional downloads or installation needed.

Combined with Python, Plotly Dash delivers interactive, customizable data apps. Explore examples in a wide range of industries and advanced analytic needs.

Access a curated selection of user stories, white papers, and how-to guides from data science experts and industry leaders. Start your data app journey today.

Data science and analytics best practices, trends, success stories, and expert-curated tutorials for modern data teams and leaders.

Plotly Professional Services are experts in delivering future-proof data apps. From custom development to workshops, they can support your analytics needs.

Consulting, Training & Open-Source Development

Plotly Customer Success empowers Dash Enterprise customers to drive insight and decision-making with data. The award-winning team offers support, enablement sessions, technical account management, and more.

Dash is a framework for building data apps in Python. Dash Enterprise simplifies the development and deployment process in a secure, scalable environment.

Plotly: The front end for ML and data science models

Find answers to common questions you may have about Dash Enterprise, including migration, installation, deployment, and licensing.

Headquartered in Montreal with a remote-first team, Plotly is dedicated to ensuring that every organization uses Dash Enterprise to build data applications.

As a category-defining leader in enabling data-driven decisions, Plotly is frequently featured in the news. Explore recent articles, podcasts, and blog posts.

Deploy front-ends for machine learning back-ends like PyTorch, Keras, and TensorFlow with custom Life Sciences templates in Dash Enterprise.

Compare Dash Enterprise, RStudio Connect, Anaconda Enterprise, and Streamlit for Teams as deployment platforms. See differences in authentication and licensing.

Dash Enterprise vs RStudio, Anaconda, Streamlit

Dash is the solution for operationalizing your AI/ML initiatives, with GPT-3, Hugging Face Transformers, UMAP, and YOLOv3. Check out latest Dash-AI projects.

Learn how Dash, Posit (Shiny), and Streamlit compare as low-code UI layers for data apps. See the differences in architecture, deployment, user experience, and more.

How do Dash, Posit (Shiny), and Streamlit compare?

Have a question about Plotly or want to know how to get started with Dash Enterprise? Fill out this form, and a member of the our team will get in touch soon.

Compare Dash Enterprise, Tableau, Power BI, and Einstein Analytics. See the differences in deployment process, ease of use, security, support, and more.

Dash Enterprise for Python vs Common BI Software

Learn how low-code UI layers like Dash, Posit (Shiny), Streamlit, and Bokeh compare in web protocol, architecture, user experience, licensing, deployment, and more.

How do Dash, Shiny, Streamlit, and Bokeh compare?

Compare the differences between Dash Open Source and Dash Enterprise. Start deploying unlimited Dash apps for unlimited end-users. Request a custom price-quote.

Plotly's company culture focuses on autonomy, trust, and data. Join the remote-first team pioneering analytic innovation and leading the data app industry.

Have a question about Plotly or want to know how to get started with Dash? Share feedback in this form, and a member of the our team will get in touch soon.

Go from data exploration to actionable insight faster. Schedule a demo to learn how Dash Enterprise enables powerful, customizable, interactive data apps.

Please see more details on Plotly's privacy policy, including information collected, security, retention, international visitors, and third-party services.

Use Plotly’s Dash web app framework with Databricks (Python SQL connector, Jobs API,  CLI, databricks-connect-v2) for at-scale production data apps.

Python is one of the best tools for data scientists in analyzing & developing models. Here are some resources to help you say goodbye to Excel, and hello to Dash.

As a Python-based framework, Dash offers integration with ChatGPT and large language models (LLMs). Learn how you can take part in the future of AI-enabled apps.

After installing Dash Enterprise in one of the below environments, you will be asked for a license key to activate the software and begin deploying Dash apps.

Learn how Dash Enterprise installs via automated scripts and get started with Dash Enterprise on Google Kubernetes Engine (GKE).

Learn how to adapt your Dash app with Dask to use Coiled in the back end. Using the integration can enable scaling across parallel computing clusters.

Dash Enterprise seamlessly integrates CI/CD for streamlined app deployment. Git-based workflow, automated QA, version control, and more included.

Dash Enterprise is the fastest way to deploy front-ends for machine learning back-ends with dozens of easily customizable ML and AI templates.

Dash Enterprise supports turnkey connections to popular backends in Python – Vaex, Dask, Datashader, RAPIDS, Databricks (PySpark), Snowflake, and Postgres.

With Persistent Filesystems, simplify your data science workflow and avoid network delays. Large data can be uploaded, updated, and cached in Dash Enterprise.

Connect Dash directly to Snowfake, a data warehouse offered by Amazon Web Services. Dash offers an ideal frontend to interact with real-time AI/ML processes.

Dash Enterprise installs via automated scripts. Get started with Dash Enterprise on Microsoft Azure Kubernetes Service (AKS).

Deploy, manage, and share data apps. | With the App Manager from Dash Enterprise, ensure a standard, well-documented, and reproducible workflow.

Easily style and customize data apps with Design Kit, a low-code framework from Dash Enterprise. Production ready — no JavaScript, HTML, or CSS required.

Dash Enterprise installs via automated scripts. Get started with Dash Enterprise on Amazon Elastic Kubernetes Service (Amazon EKS).

Provide data app end users with a powerful, drag-and-drop UI. Dashboard Engine from Dash Enterprise is Python ETL meeds BI — no callbacks or layout required.

Dash Enterprise Job Queue makes background jobs seamless and scalable in Python. Easily offload CPU-intensive tasks and improve data app performance.

Dash Enterprise Embedding Middleware enables seamless embedding without the use of iframes. It also offers single sign-on for easy authentication that scales.

Create, annotate, archive, and share views of your Dash apps. With only a few lines of code, Snapshot Engine schedules tasks and auto-generates reports.

Access a GUI for easy and secure authentication. With App Manager from Dash Enterprise, choose from LDAP, AD, PingFederate, Okta, SAML, SSO, and more.

Leverage Plotly's library of recorded webinars to learn data analytics tips, industry best practices, and application use cases from data analytics experts.

Learn how Université de Sherbrooke uses Plotly to develop new analytical tools to explore and visualize genetic structures at the school's CoBIUS Lab.

Plotly & Université de Sherbrooke to develop genomic visualization

Plotly receives the Canadian SME award for Top Place to Work and Business of the Year for driving product innovation and employee professional development.

Canadian SME National Business Awards selects Plotly

Dash DAQ provides Python users the means to create interactive virtual control panels on their computers that interface with common lab instruments.

Dash Enterprise 5.0 is built on Kubernetes architecture, providing low-code capabilities for data scientists and drag-and-drop custom views for business users.

Explore examples of Python in bioinformatics in a variety of applications, ranging from genomics, public health, clinical trials, 3D images, and more.

Bioinformatics & Life Sciences Dash App Examples

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Data visualization and dashboards is what Plotly and Dash is known for. Explore several of these Python applications for data visualization and dashboards.

Data Visualization & Dashboards Dash App Examples

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Explore examples of Python and Dash in finance ranging from quantitative analysis, machine learning, portfolio optimization, and NLP.

Explore Dash applications that incorporate ChatGPT and generative AI in Python.

ChatGPT & Generative AI Dash App Examples

Explore Python applications for science and engineering, including finite element method, contract for difference, physics modeling, and simulations, and more.

Interested in Plotly and Dash for geospatial projects and use cases? Explore these Dash data applications that take advantage of the flexibility of Python.

Explore Python and Dash applications for machine learning projects, ranging in a variety of use cases from SHAP explainability, segmentation, and more.

Explore detailed and practical examples of Python in predictive analytics and forecasting to go beyond common BI limitations.

Explore Dash data applications that run interactive image processing, computer vision, video analysis, and audio engineering with the power of Python.

Explore Python and data science Dash applications for business-related use cases, ranging from customer segmentation, retail demand forecasting, and more.

Explore examples of Python and data science applications in the energy and utilities industry, including electricity, oil and gas, renewables, and more.

Explore Python data applications for natural language processing (NLP). The following Plotly and Dash applications examples will speak for themselves.

Data analytics and data scientists meet sports fans with Dash. Explore Dash data applications that convey sports analytics using the flexibility of Python.

Learn how Plotly prioritizes data security as the premier platform for developing, scaling, and deploying Python-based data apps.

By leveraging these best practices and the provided code, you can harness the power of Sankey Diagrams to gain insights from data. Learn more in this Plotly article.

Dive into the world of data science in finance, where analytics and insights reshape the future of financial decision-making and innovation.

Plotly is now SOC2 Type I and Type II compliant. Learn how this helps protect customer assets and data sources when using Plotly products.

Enhanced Security and Reliability: Plotly Is SOC 2 Type II Compliant

Learn how to accelerate data app creation using GitHub Copilot with Dash Open Source and Dash Enterprise Solutions, for streamlined development.

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Plotly Professional Services team shares how to effectively visualize geospatial datasets in data apps, specifically for vector, polygon data.

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Discover how Anna Riley, Plotly Professional Services team member and athlete, visualized her Strava data in just two weeks with Dash.

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In this blog post from Plotly Community Manager, Adam Schroeder, learn how to leverage Matplotlib's robust plots with Dash's intuitive API to create dynamic and immersive data visualizations.

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In this blog post from Plotly's CPO and the Creator of Dash, Chris Parmer, learn how Partial Property Updates offers substantial data app performance improvements.

Partial Property Updates: Extending Full-Stack Development with Python

Excel is a complicated tool with a lot of functions that aren’t always intuitive. We’ve got a few ways Python can improve Excel functions. Learn more in this article.

Generating Excel reports can be tedious & time-consuming, but there’s a solution. Automating your reports using Python. Learn more.

How to Automate Excel Reports Using Python | Plotly

Data App Workspaces

About Data App Workspaces

A dream IDE for data science and model development

Creating a Jupyter notebook in Data App Workspaces

Creating a Dash app in Data App Workspaces

Bring Python into your Enterprise.

Write Code

Develop Algorithms

Deploy Dash Apps

Upskill Quickly

JOIN THE THOUSANDS OF INNOVATORS THAT ARE ALREADY BUILDING WITH DASH ENTERPRISE.