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

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

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

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.

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

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.

Dash is the fastest way to deploy front-ends for ML backends such as PyTorch, Keras, and TensorFlow. To accelerate Dash Bio adoption among businesses, Dash Enterprise ships with dozens of Life Science templates that can be easily customized for your own data.

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

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

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

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Plotly is the easiest way to graph and share your data.

Plotly Open Source Graphing Libraries |  | Plotly

Learn how Dash, 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, Shiny, and Streamlit compare?

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

How do Dash Enterprise, RStudio Connect, Anaconda Enterprise, and Streamlit for Teams compare?

Dash apps go where Tableau and PowerBI cannot... NLP, object detection, predictive analytics, and more. With 0.5M+ downloads/month, Dash is the new standard for AI &amp; data science apps.

Use Plotly's Dash web app framework and Databricks (DB SQL, Jobs API, databricks-dash) to create at-scale, interactive, customizable data apps.

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

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.

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

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

Dash Enterprise installs via automated scripts. 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.

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.

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.

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.

Dash Enterprise ships with turnkey support for horizontally scalable Dask clusters, putting Python's most popular HPC stack in the hands of business users.

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).

The stateless design of Dash app servers enables horizontal scaling on modern infrastructure like Kubernetes with top clouds like AWS, Azure, and GCP.

Continuous integration (CI) and continuous deployment (CD) integrates naturally with Dash Enterprise's modern, git-based deployment workflow. Dash Enterprise ships with everything you need to make the most of your CI/CD platform for Dash app deployment: templates for automated QA, pre-production app review, git-based version control, and more.

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.

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

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

With Dash, access a library of AI/ML templates that work seamlessly with back ends like PyTorch, Keras, and TensorFlow. Easily operationalize Python models.

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.

Dash is the fastest way to deploy front-ends for ML backends such as PyTorch, Keras, and TensorFlow. To accelerate AI adoption among businesses, Dash Enterprise ships with dozens of ML &amp; AI templates that can be easily customized for your own data.

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.

Scale AI contributed a grant to Plotly in 2020 to speed innovation in supply chain AI for several Canadian companies, such as Hydro-Québec and Dex Clothing.

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.

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