Overview
Dash Enterprise puts data and AI into action with the creation of production-grade data apps for your business. Python is the premier language of AI and data and Dash Enterprise is the leading vehicle for delivering Python-based, interactive insights and analytics to business users. The pricing in this listing reflects the base rate for Dash Enterprise with the below specifications. For private offers and other configurations, please contact Plotly at info@plotly.com .
Highlights
- Dynamic: Build sophisticated interactivity into your data apps, write back data, and create beautiful, shareable insights.
- Flexible: Customize every pixel of your data app easily, without a line of front end code. Focus on Python analytics without compromising app look-and-feel or branding.
- Production-grade: Enjoy advanced security features for data insights at scale. Reduce IT dependence with one-click deployment, automated CI/CD, embeddable data apps, and more.
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Pricing
Dimension | Description | Cost/12 months |
|---|---|---|
Custom | Dash Enterprise software | $35,000.00 |
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No refunds.
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
First Release
Additional details
Usage instructions
Product setup, configuration, and access instructions are available in detail here: https://dash.plotly.com/dash-enterprise/install-cloud-marketplace
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Vendor resources
Support
Vendor support
Email support issues for Enterprise customers are triaged immediately, with escalation and further investigation when required. After initial discussions, you can follow up by requesting a screen-share meeting for enhanced support. Our solutions support hours are between 4am to 6pm ET, Monday to Friday. Please contact info@plotly.com for support.
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Standard contract
Customer reviews
Python dashboards have transformed employment data into interactive insights for better decisions
What is our primary use case?
We use Plotly Dash Enterprise mainly for creating dashboards using Python. With Plotly's support of Python, it helps us to develop interactive dashboards according to the customer use case and the kind of applications that are required.
We have Federal Reserve Economic Data as well as Bureau of Labor Survey data sets for our economic data. We take this data on a per state basis or on a per county basis monthly to detect or determine economic government data sets, such as unemployment rate and employment rates in the manufacturing sector. We take that data using their APIs, and once we have this data in our database, we use Plotly to create dashboards with interactive visualizations that help our analytics team to make decisions and tune our machine learning model accordingly.
We have both internal and external use cases with Plotly Dash Enterprise . With our machine learning model, we develop interactive dashboards to have a picture of how things are going in terms of the employment rate and other economic data sets. Also, with our clients, who are hiring companies, we project this data to them to compare their statistics with the provided government data set. Since we are a private company, they evaluate their performance against the government provided data.
What is most valuable?
Integration with Plotly Dash Enterprise involves only the databases that we have, and interaction depends solely on the controls, meaning we have drop-downs, radio buttons, and other interface elements. We utilize multiple visualizations along with different types of charts that Plotly helps us to interact with.
The ability to develop dashboards using Python has been our great use case with Plotly Dash Enterprise. With this capability, we are able to create a GitHub repository or a central version control system that helps us manage different versions of the dashboards. If we need to improve something, we simply go back to a previous version and make immediate changes if necessary. Furthermore, we also have the ability to control how our dashboards look and design them according to our own use cases, achieving the required scalability with the help of the enterprise version.
Since we have ties with hiring companies that require high scalability, Plotly Dash Enterprise helps us achieve that. With the GitHub version control system, we have created a repository containing our dashboard code. With the help of Plotly, we integrate our dashboards with GitHub to provide us much more control over how our dashboards look and manage different versions of them simultaneously.
We use Python mainly with Plotly Dash Enterprise, which is an added use case instead of doing a drop-down and using Power BI. Coding provides us with much more ability to design custom visualizations tailored to our specific needs. Plotly Dash Enterprise helps us achieve a much more interactive and vivid form of visualization for our organization, which helps us drive better results and analytics. It also helps us derive decisions that are beneficial for our use cases and create different versions for different sets of companies that we partner with.
The main advantage we have is that we manage different forms of files or different forms of data that we have stored, including semi-structured, structured, and unstructured formats. With the help of Plotly Dash Enterprise, we tackle these challenges and create a unified data frame or dataset that helps us achieve a common goal. We are not restricted to any form of data. No matter the data format, we can handle it clearly with the help of Python libraries and scale our visualizations to another level.
What needs improvement?
The main improvement I can think of is that while creating charts, it gives you a certain format of how it could look. If you want to create something extra and go more vivid and creative with how the actual chart would look, it allows for that option but could be improved to be more artistic or aesthetically pleasing. This sort of format is missing, and I think it would be beneficial to the analytics team if it can be more interactive, with the capability of D3.js , and give us more control over how our actual dashboard would look to achieve a more aesthetic appearance. The strict format of how you can shape those charts and that extra nuance you need to keep in code to get the exact possible results are the reasons behind my rating. The rest of the features provided by Plotly are extremely good.
For how long have I used the solution?
We have been using Plotly Dash Enterprise for nearly two to three years.
What other advice do I have?
It's a great tool to incorporate in your organization to develop dashboards that help your analytics team derive better decisions and generate more business profits. It gives you much more control with Python and helps you interact with multiple file formats to easily bring them to a common platform, such as a Pandas DataFrame or PySpark DataFrame. Plotly Dash Enterprise helps you create the visualizations you want and achieve better results. I would rate this product an 8 out of 10.
Which deployment model are you using for this solution?
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
A flexible tool that offers an open-source version
What is our primary use case?
My company builds products. With the help of Plotly , the dashboards and reports my company builds are used by our clients. My company uses Plotly to present our data to clients so that they can understand and improve their performance.
My company uses Plotly as it is a very light and flexible tool. We use the free version of the solution based on our requirements. With a bit of technical skills, anyone can use Plotly. Any data analyst can use Plotly with a very small amount of training.
What needs improvement?
I believe that the price of the tool's paid services is on the premium side, so the pricing model can be considered for improvement.
For how long have I used the solution?
I have been using Plotly for nearly more than an year. My company is a customer of Plotly. I use the latest version of the solution.
What do I think about the stability of the solution?
It is a stable solution. Stability-wise, I rate the solution a seven or eight out of ten.
I have not encountered any troubles while using the product, but I feel that it has some feature limitations.
What do I think about the scalability of the solution?
It is a scalable solution. Scalability-wise, I rate the solution a nine to ten out of ten.
In my company, there are around five resources that use the product. My company's clients use the product a lot on a daily basis.
I use the product twice a week in my company before I get any call from our clients.
How are customer service and support?
My company gets a lot of support from blogs and GitHub . Everything is good with the technical support. I rate the technical support an eight or nine out of ten.
How would you rate customer service and support?
Positive
Which solution did I use previously and why did I switch?
My company has been using Power BI for many years. My company has experience with Tableau aswell.
My company switched to Plotly from Power BI since the former allowed the flexible use of certain views. Plotly's link with Python language made it here for our company to get the views that we wanted. Plotly was used to overcome certain limitations related to views, especially when it comes to the creation of custom views.
How was the initial setup?
I rate the product's initial setup phase a nine or ten on a scale of one to ten, where one is a difficult setup process, and ten is an easy setup process.
The solution is deployed on a private cloud.
The solution can be deployed in a day or two since I had to set up a lot of custom views., after which the deployment process can be managed in a few minutes.
What about the implementation team?
One of our company's in-house teams managed the product's deployment phase.
What was our ROI?
Plotly has been a good product, and it has only been a few months since my company started using it. Based on the scalability and client adaptability, my company should be able to get a fair return on investment.
What's my experience with pricing, setup cost, and licensing?
It is an open-source tool. My company hasn't explored Plotly's premium services yet, but I believe the prices are on the premium side.
I rate the product price as five or six on a scale of one to ten, where one is a low price, and ten is a high price.
What other advice do I have?
I am only in the picture when there is some decision-making process that happens with Plotly. Plotly is mainly used by the team in my company.
There is hardly any requirement for maintenance until and unless we change the views and colors or add additional views. Maybe a few hours are required every month to take care of the product's maintenance phase.
I rate the overall tool an eight out of ten.
Helps to visually present datasets
What is most valuable?
In my approach to data analysis and presentation, especially when dealing with a substantial amount of code for data processing, I find Plotly to be a valuable tool. After running the code and obtaining results, I focus on presenting these results using it acceptably.
When reviewing and interpreting data, I typically examine it in a tabular form to understand its structure. However, when explaining or presenting the findings to others, I often use visualization tools such as Plotly. These tools allow me to create visual representations of datasets.
What needs improvement?
The tool needs to improve its pie charts. Regarding Plotly, I find the online documentation somewhat challenging to navigate, especially when dealing with many parameters. Searching through thousands of parameters can be a tedious and less straightforward process. While the documentation is available online and serves its purpose, I often encounter difficulties in finding the information.
How are customer service and support?
I haven't contacted the tool's support.
What other advice do I have?
In my experience, I primarily work with R when using Plotly. However, I understand that the integration of Plotly with Python is also excellent. I'm working with a sales and marketing consultancy that has operated for 20-30 years. They are transitioning to incorporating machine learning, AI, and statistical analysis into their traditional methods. The consultancy primarily works with B2B companies, recognizing that B2B firms with a limited pool of potential customers tend to be less engaged in social media than B2C companies. The focus is on platforms like LinkedIn, Facebook, and Instagram while acknowledging that TikTok is not considered valuable for their analysis.
The consultancy actively uses large language models to analyze various aspects, such as social media engagement, and assess how companies present themselves. In statistical and analytical terms, we aim to create impactful analyses for our clients. The approach involves comparing the target company with four to six similar companies, keeping the identity of these competitors confidential. Our goal is to assist clients in understanding their position in the market and provide tailored insights using modern tools. The focus is on identifying areas of weakness and highlighting strengths to refine sales and marketing efforts.
To make this process effective, we utilize Plotly, as they offer impactful presentations. Building databases of company data and conducting analyses on various aspects like websites, social media, and other marketing presentations, we present comparative analyses of how a particular company stacks up against its competitors.
I rate the overall product a seven out of ten.
An interactive and easy-to-use solution that can be used to create dashboards
What is our primary use case?
I am using the solution for creating dashboards that can be deployed on web-based applications. It involves data analytics, graph representation, and table representation.
How has it helped my organization?
The good thing about Plotly is that it is based on Python. I know Python, so I can use it very easily. The level of interactivity that Plotly has is very useful. Users can play with the data and modify the filters of the images and tables.
What is most valuable?
The level of interactivity that the product provides is valuable to me.
What needs improvement?
The solution cannot be deployed on the website and shared with others through its own platform. We need a third-party platform to share the application that we develop. In Tableau and Power BI, we can simply share the website with others as long as we use the paid version. However, for Plotly, we need to deploy our app on a cloud-based service like AWS or other third-party websites to share with others.
For how long have I used the solution?
I have been using the solution for one year.
What do I think about the stability of the solution?
Compared to Tableau and Power BI, the product is less stable.
What do I think about the scalability of the solution?
Compared to Tableau and Power BI, the product is less scalable. Three to four people in my organization use the solution.
How are customer service and support?
I have been in touch with the support team through GitHub for some issues with my applications. My experience was very good. The team members are very good. They usually respond within two or three days. I'm happy with that. The solution has a really good community on GitHub. Most of my questions are already answered there. They usually respond within two or three days if it is something new.
How would you rate customer service and support?
Positive
How was the initial setup?
The initial setup was moderately complex the first time. I use AWS to deploy my app on the web.
What about the implementation team?
The deployment of the app does not take too much time. It depends on our level of expertise in both AWS and Plotly. If we want to deploy an app on the web, it must satisfy some criteria. As long as we maintain those criteria, it is easy to deploy on the web. It is a little bit costly to deploy the app. If we want to deploy it on the web, we must have the paid version of AWS. We cannot use a free version.
It took me almost a day to do all the setup, setting, and everything in Plotly and AWS. After that, it takes only half an hour to deploy the app on AWS. I did the deployment myself. While deploying the product, I had to change my code a little bit to maintain specific criteria. Then, I created some additional files for the application, like the asset files, the folder containing all the images, and all the things we will share. Then we need to zip everything together and go to AWS. We choose the services we wanted to use and set up our instances on AWS Connect. Finally, we upload the application onto AWS.
What's my experience with pricing, setup cost, and licensing?
I only use the free tier of the product. I haven't studied the paid version, but I don't think it will offer a lot because it's all on Python. All that it offers is a desktop version of the software. I'm not sure how useful it's going to be for those who are coding Python.
What other advice do I have?
I want to explore Tableau and Power BI. My organization did not have access to these solutions. As long as someone does not have access to the paid version of Power BI and Tableau, Plotly is the best option for them. Overall, I rate the product an eight out of ten.