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.

/dash/big-data-for-python/?tab=connect-any-data-pipeline#bigDataTabs

Announcing Dash Enterprise 5.2: Jupyter Notebook compatibility, AI integration, and enhanced developer experience.

Reserve your spot for the Dash Enterprise 5.2 launch event!

Dash Enterprise on Amazon EKS elevates advanced Python analytics to business users.

DASH ENTERPRISE

Install Dash Enterprise on Amazon EKS

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Dash Enterprise installs via automated scripts. Amazon Elastic Kubernetes Service (Amazon EKS) is available with an Amazon Web Services (AWS) account. 

Get started with Dash Enterprise on Amazon EKS. Access the documentation.

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Plotly’s Customer Success team will reach out to learn about your installation environment.

Together, you’ll discuss requirements around cluster configuration and memory, load balancing, network privacy, and other details that will shape your installation plan.

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Plotly’s Customer Success team will send you an installation plan tailored for your specific environment’s needs.

The plan will include your Dash Enterprise license key, as well as the scripts that provision your infrastructure and install Dash Enterprise.

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Running the scripts in your installation plan will provision your EKS cluster and install Dash Enterprise on it. You will run your scripts on an Amazon EC2 virtual machine.

The scripts complete in minutes, no Kubernetes experience required!

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

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

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

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

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

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.

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

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

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.

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.

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.

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

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

Rapidly build, deploy, and scale data apps directly from your Jupyter Notebooks with Plotly App Studio.

Dash Enterprise lets you centralize data app development under a single platform to manage and deploy Dash, Streamlit, and Django data apps.

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.

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

Learn how using Snowflake and Dash together ensures the delivery of production-grade delivery apps that use real-time machine learning and AI processes.

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.

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.

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

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

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 Microsoft Azure Kubernetes Service (AKS).

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.

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

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.

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.

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

Thanks to the flexibility of Python, Dash applications can connect to any API. Explore data applications that connect to external APIs and visualize data.

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

ChatGPT & Generative AI Dash App Examples

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 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.

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

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

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

Explore Python applications for manufacturing and research and development, ranging from laboratory data collection, IoT, real-time dashboards, and more.

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

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

Analyze URLs and website structure with Dash for better sub-folder organization, effective content distribution, and enhanced online presence.

Analyzing Website Structure With robots.txt Files and XML Sitemaps Using Dash

We explore how to choose between low-code and no-code for data app development, offering insights to streamline data into production-ready apps.

What’s Better: Low-Code or No-Code Data App Development?

Chris Parmer, Plotly Co-Founder and Chief Product Officer, reflects on the future of AI data apps and LLMs in a world of unstructured text.

Dash Club 12: Chris' Reflections on GenAI Dash Apps

Here's how Plotly's new "Ask AI" chatbot answers technical questions based on LLM models trained on over 2,000 pages of documentation.

Meet Your Personal Plotly “Ask AI” Chatbot for Easier Data App Development

Discover the benefits, challenges, and explore how AI benefits both employees and patients in the Pharmaceutical and Life Sciences industries.

How Pharma and Life Sciences Are Benefiting From AI Applications

Easily build and deploy an interactive dashboard interface for your scikit-learn models directly on the web, with Plotly Dash.

Build Python Web Apps for scikit-learn Models with Plotly Dash

Automate and streamline digital marketing workflows with by building custom digital marketing data apps and dashboards using Advertools and Dash.

Automating and Streamlining Digital Marketing Workflows with Plotly and Dash

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

Dash + GitHub Copilot = Easier and Faster Data App Building

Discover the power of leveraging Polars in lightning-fast Dash apps for visualizing and analyzing large data sets in your production environment.

How Polars Can Help You Build Fast Dash Apps for Large Datasets

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.

Creating an Interactive Web App with Matplotlib, Python, and Dash

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

Python is one of the best tools for data scientists in analyzing & developing models. Here is a list of the top 15 python tools for data scientists.

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

Performance Optimizations for Geospatial Dash Apps

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

Reflections from an Athlete — Dash feat. Strava

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

Nicole Arksey, Group Product Manager at Plotly, shares her thoughts on the upcoming Dash Enterprise 5.2 release — and what it means for data science teams.

How Dash Enterprise 5.2 Enables Data Science Teams to Influence Mission-Critical Decisions

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

Install Dash Enterprise on Amazon EKS

Install Dash Enterprise on Amazon EKS

Step 1: Discuss your requirements

Build. Deploy. Scale.