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What is Plotly Dash?

Industry Specialties: Serves all industries

Dash is an open-source Python library that helps data scientists create web interfaces to leverage Plotly’s data visualization and analytics applications. It provides an intuitive UI for people of all technical skills to use data science and machine learning for data analysis, thanks to components such as natural language processing for predictive modeling. It enables data analysts to translate business requirements directly into custom web development.

MIT-licensed, it can easily run on local servers and machines. Its Enterprise version is available as a Platform-as-a-Service (PaaS) and can be easily deployed on proprietary infrastructure with SSO/LDAP authentication and app designing. The community version is available for free download, while the Enterprise version comes at a price and includes authentication features, server deployment and dedicated support.
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#58

Plotly Dash is ranked #58 in the Business Analytics Tools product directory based on the latest available data collected by SelectHub. Compare the leaders with our In-Depth Report.

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Plotly Dash Benefits and Insights

Why use Plotly Dash?

Key differentiators & advantages of Plotly Dash

  • Advanced Analytics: Create, customize and deploy apps on web and mobile, with minimal code required. Connect to multiple data services that include Snowflake, Redshift, PostgreSQL, Google BigQuery and many more. 
  • App Customization: Design the app’s look and feel via CSS and default styles from a vendor-provided core style guide, or add custom features. 
  • Data Visualization: Ships with an interactive Graph component that allows easy hover, click and select actions on graphs. Create interactive applications with sliders, dropdowns and map scientific, financial and business charts in 2D and 3D through the plotly.js graphing library. 
  • App Management: Deploy, manage and share apps with all teams through a central admin portal. Leverage separate App Managers for an app’s instances on testing, UAT and production environments. 
  • Easy Authentication: Focus on operationalizing data analytics models; perform authentication through middleware that supports easy access through LDAP, OAuth, SSO and simple email authentication — no need to hard-code identity management features within the app. 
  • Optimize Performance: Perform fast numerical computations, compile Python code and identify workflow blockers. Handles incoming requests quicker through job queueing while offloading long-running queries or CPU-intensive tasks on the back end. 
  • Scalable Multitenancy: A Dash app is stateless by design — multiple teams can access and use the application at the same time. Scales easily to service a larger request load and supports Kubernetes and Docker applications. 
  • Open Source: Import and download its Core, DAQ, Bio and HTML components into Python, R and Julia-based apps. Maximize its functionality through community-contributed attributes, such as Dash Trich Components, Material UI, Pivottable, Tabulator, the Download Component and many more. 
  • Dash Enterprise App Gallery: The vendor provides a public instance of its App Manager on Azure Kubernetes that runs more than 60 apps available to all. 

Industry Expertise

Dash provides application authoring services to multiple organizations around the world. These include banks, insurance companies, pharmaceuticals, energy and transportation, airlines, sports companies, power utilities, government agencies, manufacturing, HR, retail and supply chain and many more.

Plotly Dash Reviews

Average customer reviews & user sentiment summary for Plotly Dash:

User satisfaction level icon: excellent

43 reviews

95%

of users would recommend this product

Plotly Dash has a 'excellent' User Satisfaction Rating of 95% when considering 43 user reviews from 4 recognized software review sites.

Key Features

  • Declarative Programming: Build applications based on the input data and output needed — no need to supply detailed how-to information. Plotly.js is a declarative library, shipping with over 40 chart types that include 3D charts, SVG maps, statistical graphs, maps, animations, and many more. 
  • Design Kit: Style, arrange and customize applications with its low-code Design Kit to deploy them faster. Leverage its user-friendly layouts and point-and-click theme editor to give a native look and feel to the application. 
  • Snapshot Engine: View a point-in-time image of the app and snapshots on-demand, and then share a link to these with others. Generate a print-ready, pixel-perfect PDF report to distribute via email. Draw and place comments directly on the app canvas, shareable via email. 
  • AI/ML: Securely create and run custom apps, Jupyter notebooks and Python Scripts through its browser-based IDE, Data Science Workspaces. Run code in the browser to filter and visualize data query results easily — no downloads needed. 
  • Big Data Pipelines: Run data science and analytics pipelines with integrations to Vaex, Datashader, NVIDIA RAPIDS, Snowflake, Postgres and Salesforce. Interact with and visualize more than 300 million data points in a web browser with a single GPU. 

Limitations

At the time of this review, these are the limitations according to user feedback:

  •  It lacks built-in methods to extend its API’s functionality. 
  •  It isn’t possible for two Python callback functions to update the same element. 

Suite Support

Before emailing support, access the user guide, webinars and online community forum on the vendor’s website for answers to queries and possible issue resolution. Dedicated support is only available for paid subscribers.

mail_outlineEmail: Email support through an Enterprise login.
phonePhone: Not available.
schoolTraining: Sign up for remote workshops on creating and customizing analytics and data visualization applications. Many third-party vendors offer paid training.
local_offerTickets: Raise a bug through its Github page.

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