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

/solutions/healthcare-life-sciences-pharma/

NHS Foundation Trust Unlocks AI Healthcare Potential with Dash Enterprise

July 15: Witness the future of data app development with Plotly Studio. Reserve your webinar seat.

Reserve your spot for the Dash Enterprise 5.2 launch event!

Dash Enterprise is productionizing Python data apps in every industry.

DASH ENTERPRISE

Industry App Catalog

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Access these pre-built Dash apps by industry as inspiration and starter templates.

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Dash helps data scientists & quants operationalize Python models

Global Pharmaceutical Company & Dash Enterprise Customer

"The distinguishing factor between PowerBI and what Dash NLP analytic apps can do, is offer that next step up of a 'cognitive dashboard' rather than all the other standard dashboards out there."

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Dash is the fastest way to deploy Python-based apps for natural language processing (NLP).

Use NLP + Dash to extract business value from large amounts of unstructured text:

This Dash app demos Google's word2vec in ~300 lines of Python code

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Dash is the fastest way to deploy Python-based apps for computer vision.

Use computer vision + Dash for object detection in:

This Dash app demos DETR object detection in ~200 lines of Python code

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Dash is the fastest way to deploy Python-based apps for dimensionality reduction.

This Dash app demos TSNE clustering in ~300 lines of Python code

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Dash is the fastest way to deploy Python-based apps for predictive analytics and forecasting.

Use predictive analytics + Dash to put neural networks, nonlinear regressions, decision trees, SVMs, and other forecasting methods in the hands of business users.

Dash operationalizes predictive models for:

This Dash app demos Facebook’s Prophet library in ~200 lines of Python code

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Dash is the fastest way to deploy Python-based apps for voice computing.

This Dash app demos speech recognition in ~100 lines of Python code

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Deploy Flask APIs to Dash Enterprise that load trained models, accept feature values in POST requests, and respond with predicted values.

Access this Dash app and get the Python code.

This Dash app loads scenes collected from self-driving car trips, and displays both lidar sensor data and human annotated data (bounding boxes). You can choose between a basic and an advanced UI. Get the source code and read the blog post.

This Dash app shows how to build a real-time AV explorer from scratch using Dash Deck and the Lyft perception dataset. The code is easily customizable and also compatible with 3D detection models written in Python.

Given a pre-annotated video, this Dash app lets you run 2D object detection on a selected frame. You can also edit the annotations, add new bounding boxes, and export the new data table.

The release of DETR: End-to-End Object Detection with Transformers showed significant improvement in real-time object detection and panoptic segmentation (PS), while greatly simplifying the architecture. As a mean to test the model, we decided to build a simple Dash app that let you experiment and play with the model through a user interface.

This Dash app shows how Dash can be used to execute AI models like the YOLO v3 object-detection algorithm in real-time. Check out this article for full details.

This Dash app analyzes 120 million Uber trips in real-time to predict the cost of Uber trips through NYC. Read the blog post.

This Dash app displays well data from New York State. As you hover over values in the map, a time series is displayed showing production values over time. As you change the years in the range slider, the aggregate time series is updated with the sum of all production over time. The histogram chart is also selectable, serving as an alternative control for selecting a range of time.

This Dash app creates a dashboard for mineral composition evaluations from natural gas wells. By pairing geographic map of well locations with ternary diagram, this app helps geologists to find out results of gas wells with relationship to formations or rock types.

This Dash app takes a Log ASCII Standard (LAS) file as input and builds a web app to visualize drilling data.

This Dash app was published in Nature Energy by the UC Berkeley Energy Resource Group. It calculates the levelized cost of electricity (LCoE) for off-grid solar deployments in Sub-Saharan Africa.
Read the UC Berkeley announcement.

This peak load forecasting Dash app provides two helpful predictions for New York City building owners, facility managers, and residents interested in tomorrow's total electricity grid demand. The first model is a next-day hourly load curve for the NYISO. The second is a confidence interval representing the percent chance that tomorrow will be a peak load event. The Python model behind the Dash app was framed as a supervised learning problem in order to compare the performance of a Regression Tree, Random Forest Regressor, and XG Boost algorithms.

This Dash app uses pre-trained Decision Tree Classifiers to perform real-time predictions on tabular data (information about a loan applicant that was recorded by a lending firm). To read the model data, this Dash app connects to a Snowflake data warehouse.

This Dash lets you train and evaluate a L2 regression (Ridge) model for predicting the interest rates of loans based on various factors. It lets you see how well a model performs (actual vs predicted plot), as well as compare the importance of these features. To read the model data, this Dash app connects to a Snowflake data warehouse.

This Dash app performs natural language processing on a database of consumer complaints towards US financial institutions. Compare consumer complaint sentiments between Wells Fargo, Citibank, Equifax, JP Morgan and dozens of other institutions.

This Dash app uses Facebook's Prophet time series forecasting model to perform predictive analysis of regional sales. The data was collected for locations across various states and for various market segments, and the model was used to forecast future sales, which is useful for making informed decision and infer the supply needed for future months.

This Dash app simulates the efficient frontier of a set of portfolios based on the Monte Carlo method, then generates a 16 page report of the result.

This Dash app demonstrates the use of Design Kit and Snapshot Engine for generating enterprise-grade, interactive reports with Python and Dash.

This Dash app demonstrates the use of Design Kit and Snapshot Engine for triggering alerts and automatic report generation for out-of-spec process parameters.

This object-detection Dash app provides real-time visualizations about what's happening inside a complex video.

This Dash app monitors SKU product availability by product, supplier, and store region. It also allows stores to track daily distribution and future inventory predictions.

This statistical process control (SPC) Dash app simulates monitoring real-time process quality along a manufacture production line.

This Dash app allows users to annotate medical image datasets of COVID-19 patients in order to extract a lung occlusion (and train machine learning models).

This Dash app uses machine learning in order to compute the segmentation of an image, given user-provided annotations. In addition to Plotly and Dash, the app uses off-the-shelf algorithms and estimators from PyData packages, namely scikit-image and scikit-learn.

This Dash app segments an image into regions with scikit-image and computes a number of properties for these regions such as their area, their perimeter length, etc. Each region is then annotated on the image and entered in a Dash DataTable. The annotated image and the DataTable are dynamically linked together, so that interacting with one changes the displayed information in the other

This app allows you to:
Interactively move through sliced representations of the brain
See an overlay of the automatically computed over-segmentation of the brain into superpixels (regions of the brain)
Highlight one or several superpixels
See the highlighted superpixels rendered in a 3D glass brain representation
Download a file with that contains the highlighted superpixels 

Access this Dash app and get the Python code. 

To ensure adequate inventory, retailers need to continuously monitor levels of stock. Using Prophet, a procedure for forecasting time series data, this Dash app is able to process and interactively display availability levels by category, region, supplier, and product. Inventory managers can respond to the daily distribution levels and plan future inventory.

Monitoring competitors’ websites is critical to determine the best product pricing and positioning. This app uses Scrapy, a Python web-crawling framework, to mine data from multiple websites for top-rated products, price changes, and website position. Dash easily displays this information and empowers companies to optimize their market position in real-time.

The consumer decision-making process is important for retailers to understand. What will be the second choice if the first item is out of stock? This app visualizes demand transference predictions based on transactional log data, store attributes, and external sources. It adjusts for pricing, stock, and seasonality to help retailers determine and adjust to the relative level of demand of items.

Revenue protection is crucial in industries that may have fluctuating yield levels. This Dash app presents a fully interactive Sankey diagram that enables the user to view crossovers between vulnerable product ingredients, growing regions, presentation form, and consumption sites. With this information, businesses can quickly identify the percentage of predicted revenue that is protected versus unprotected before production.

Predict customer and revenue churn through survival analysis models. 

https://plotly.com/dash/industry-app-catalog/

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

Discover data applications for production with Plotly Dash. Put data and AI into action with scalable, interactive data apps for your organization.

See how Dash Enterprise simplifies app deployment with built-in services, access controls, viewer analytics, and a full-featured IDE.

Introduction to Dash Enterprise App Manager

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

 Plotly Studio is an AI-native desktop app for generating Dash data apps in minutes with no code. Join the waitlist for early access to Plotly Studio.

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

Learn how to debug, log, and deploy Dash apps using Dash 3.0. Covers Python logging, callback error handling, and reading build vs deploy logs.

We love connecting with the data community, in-person and online! Explore upcoming Plotly community events, webinars, and conferences around the world.

Plotly Community Events, Webinars, and Conferences

This video introduces Dash Enterprise as a fast and flexible environment for developing and deploying interactive Python data apps with no code.

No-code Dash app development for data scientists

Explore Dash Design Kit, a component library for creating styled, interactive Dash apps with themes, cards, modals, and layout tools.

Making Dash Apps Beautiful - Dash Design Kit

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

Easy-to-follow video tutorials and practical insights from data science experts to help you master Plotly for interactive Python data apps.

Plotly Videos | Explore, Learn, Visualize

Watch a video tutorial on how to customize the look and feel of your data apps using themes and styling tools built into Plotly Dash Enterprise. 

Exploring Themes and Styles in Dash Enterprise

Everything from geospatial analytics to finance and unstructured data workflows: Dash apps handle massive datasets and deliver high performance.

The founder of Broadband Insights shares how his team uses Plotly Dash Enterprise to build and deploy telecom analytics for broadband providers. 

Custom telecom analytics for rural regions

Discover the latest updates in Dash Enterprise, Dash Open Source, and Plotly Graphing Library — new product features, enhancements, and more

Read in-depth user stories and examples of how Plotly customers build, deploy, and scale professional data applications with Dash Enterprise.

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

 Watch a detailed walkthrough of building a production-ready retrieval-augmented generation (RAG) Python app data using Dash.

Justin Andrews from Shorelight shares how his team uses Dash Enterprise to support international student enrollment and deliver powerful analytics tools.

Data Science market needs and customer insights

Matt Brown, product manager at Plotly, breaks down the new AI chat feature built into App Studio that cuts down the time it takes to build data apps.

A smarter way to build data apps with Plotly AI

In this video, we introduce App Studio: the result of years of working with enterprise teams to streamline how Python data apps are developed and deployed. 

Build faster Python data apps with Plotly App Studio

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.

Learn how Dash Enterprise 5.6 helps teams scale data applications, manage cloud costs, and improve data access across the organization.

In this walkthrough, Nathan from Plotly demonstrates how to create an interactive data app from a Jupyter Notebook, using App Studio within Dash Enterprise.

Add interactivity to your Jupyter Notebooks and Python data apps

The keynote for Plotly’s summer launch event shares the company’s mission to make data apps accessible with better analytics, collaboration, and deployment.

This video tutorial demos the development of two Dash apps powered by the DBRX large language model. We'll share how to integrate DBRX into a Python data app.

Data apps in Python with Plotly Dash and DBRX LLM

Explore the table editor and transform library to shape and analyze data interactively before visualizing it, while still editing Python code.

Tutorial: Data shaping and transformation in App Studio for Dash Enterprise

We highlight how Plotly continues to evolve based on direct feedback from its global community of data and AI professionals.

Data and AI today — enhanced enterprise connectivity

The Kansas City Chiefs analytics team shared how they use Dash Enterprise to power real-time event operations through custom sports analytics.

How the Kansas City Chiefs use Plotly Dash Enterprise

App Portal is a centralized place to access, interact with, and act on their data through applications built on Dash Enterprise.

Quick intro to Dash Enterprise App Portal

This video introduces Dash Enterprise 5.4, focusing on App Studio and how it enables faster, more customizable development of interactive data apps.

Plotly App Studio — data apps for everyone

Meet the Plotly AI Code Assistant, your new coding co-pilot to write and edit Dash code with intelligent autocomplete faster than ever.

Take the product tour to experience Plotly Dash Enterprise, a platform for building production data apps in Python, assisted by AI.

A recap of Plotly Dash Enterpise 5.5, focused on enhancing data connectivity, improving app performance, and supporting large datasets.

Data connectors and App Studio in Dash Enterprise 5.5

Andrew Schutte, Senior Data Scientist for the Kansas City Chiefs, shares his journey from industrial engineering to leading data initiatives.

Plotly Virtual Hangout - Andrew from Kansas City Chiefs

Nathan Drezner shares updates for Dash 3.0 with new features and performance improvements perfect for all Dash developers and component creators.

Chris Parmer, Chief Product Officer and co-founder of Plotly, walks through Plotly’s journey and vision for shipping data apps.

Plotly’s story — data apps for everyone

This video introduces how Plotly AI Chat helps users explore and visualize data faster with natural language prompts, a dataset, and generative AI.

Alex Martinez from RA Capital explains how Dash has replaced static tools like spreadsheets with real-time, interactive data apps.

How RA Capital replaced spreadsheets with Plotly

Watch the video to follow along and hear from the Cox Auto team on modernizing auction operations with scalable data apps using Dash Enterprise.

How Cox Auto drives automotive operations with Dash Enterprise

Jeff Butler from CIBC talks about using Plotly Dash for financial analytics, managing credit and funding risk related to over-the-counter derivatives.

Plotly Virtual Hangout - Jeff Butler from CIBC

Watch how Cox Automotive turned to Dash Enterprise to solve a critical capacity planning problem across its 50-plus auto auction sites.

Cox Automotive on capacity planning with Dash Enterprise

A look at Dash Enterprise Design Kit, a framework to standardize the appearance of your data apps, making it simple to personalize apps without CSS.

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

Dash Enterprise | Data App Platform for Python

Austin Kiesewetter, a software engineer at Martin Engineering, shared his journey from entrepreneurship to building open source tools for the Plotly community.

Plotly Virtual Hangout - Austin at Martin Engineering

This video introduces global environmental variables and horizontal pod scaling in Dash Enterprise to improve control, customization, and scalability.

Global environment variables and horizontal pod scaling

Watch how Somerset NHS Foundation Trust (SFT) enabled AI across its operations using Plotly Dash and open source Python libraries.

Enabling AI in an NHS Acute Trust with Plotly

Get a full walkthrough of Plotly App Studio, the data app builder that’s changing how teams develop and deploy interactive data apps.

App Manager is the control center where users can configure data sources, define authentication, and access tools like App Studio and Design Kit.

Quick intro to Dash Enterprise App Manager

We demonstrate how to transform a Jupyter Notebook into a shareable Python data app using App Studio in Dash Enterprise.

Go from Jupyter Notebook to Python data app fast

Dash Enterprise and open source Dash make it possible for data teams to harness these models without needing web development expertise.

Plotly App Studio is the easiest way to transform static data science notebooks into branded, interactive data apps, with AI.

Quick intro to Dash Enterprise App Studio

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

Learn how Plotly Champions make a significant impact by developing open-source tools, offering guidance, or supporting fellow community members.

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

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

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.

Plotly’s brand guidelines outline the visual identity of our brand. Use this page as a starting point if you are creating imagery using the Plotly logo.

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.

Discover how leading businesses put data and AI to work, through production data apps. Request a custom price-quote.

Review the Dash Enterprise Terms of Use and gain a thorough understanding of Plotly's policies, to ensure compliance and effective utilization

See how Plotly Dash Enterprise compares to frameworks like Streamlit when it comes to scaling, security, and flexibility.

See how Dash Enterprise Compares to Streamlit

View the previous version of Plotly's privacy policy, including information collected, security, and third-party services.

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

Build, deploy, and scale professional data applications with airtight security, for confident, data-driven decisions across the organization.

Learn how we handle and protect your personal information during the hiring process. Our Data Privacy Notice for Candidates explains how we collect, store, and use applicant data, ensuring compliance with data protection laws to keep your information secure and confidential.

Discuss your use case with a Plotly expert. Learn how industry leaders are solving the toughest challenges with custom data apps powered by Plotly Dash Enterprise.

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

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.

Important updates to Chart Studio Cloud regarding user accounts, starting on November 8, 2024.

Sunsetting Chart Studio Cloud User Accounts

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 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?

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?

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.

Secure OAuth in Dash apps. Learn how Dash Enterprise supports pass-through authentication to APIs like Databricks, BigQuery, and more.

OAuth for Dash Enterprise: Sophisticated Data Security for Plotly Dash Apps

Chris Parmer, Plotly co-founder and author of Dash, announces the launch of Plotly Studio, an AI-native desktop app for generating data apps and visualizing data.

Announcing Plotly Cloud: a drag-and-drop way to publish, manage, and share Dash and Plotly Studio apps with your team or the world.

Plotly Cloud: The Best Way to Publish Your Dash Apps

Designed specifically for the AI era, Dash Enterprise 5.7 enables organizations to build smarter, safer data applications with efficiency.

Elevate Your Analytics: Plotly Dash Enterprise 5.7 Launch

Plotly AI is a set of AI capabilities helping data teams analyze data faster and create production-quality, interactive Python data apps with Plotly.

Explore how agentic analytics uses AI agents to monitor KPIs, generate insights, and trigger actions autonomously in modern data workflows.

Learn about the uv package manager, its definition and benefits, and how to approach issues and quirks in your Python workflows when using this tool.

uv Python Package Manager Quirks a Year Into Adoption

Understand the differences between BI and AI in analytics. See how the limitations of traditional BI tools can be overcome with AI and data apps.

AI vs BI in Analytics: What’s the Difference?

Modern data science teams trade static reports for interactive, collaborative, and highly custom data applications, commonly known as data apps.

Industry App Catalog

About Industry App Catalog

Dash helps data scientists & quants operationalize Python models

"The distinguishing factor between PowerBI and what Dash NLP analytic apps can do, is offer that next step up of a 'cognitive dashboard' rather than all the other standard dashboards out there."

NLP

AV Lidar Visualization

Lyft AV Explorer

Video Annotation

DETR Object Detection

Real-time Object Detection

Uber Price Prediction

Build. Deploy. Scale.