Plotly Dash is an Excellent Platform for Machine Learning
March 08, 2022

Plotly Dash is an Excellent Platform for Machine Learning

Anonymous | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Software Version

Open Source

Overall Satisfaction with Plotly Dash

We are using Plotly Dash Enterprise open source as a gateway to allow business users to interact with the Sentiment Analysis machine learning application built to understand and influence customer feedback received from Trustpilot, Google, and other social media platforms. Plotly Dash gives the business powerful visual representations of customer intent, emotion, and urgency.

Pros

  • Data visualisation
  • Low code dev
  • Based on python so easy to implement

Cons

  • Would be good if Dashboard Engine was included in the Enterprise VPC plan
  • Would love to see ready made fintech apps
  • Open Source
  • Generous allowance for 5 devs and unlimited business users
  • Perfect building block that brings our machine learning applications to life for the business
  • Reduce product monetization lead time
  • Real time performance monitoring
  • Deep learning to allow better marketing segmentation models
Tableau is great for basic dashboard visualisations using an ETL transfer layer from production. However, Plotly Dash is specifically designed for visualisation of machine learning applications. That's the key difference.

Do you think Plotly Dash delivers good value for the price?

Yes

Are you happy with Plotly Dash's feature set?

Yes

Did Plotly Dash live up to sales and marketing promises?

Yes

Did implementation of Plotly Dash go as expected?

Yes

Would you buy Plotly Dash again?

Yes

Plotly Dash open source components are quite powerful, fit for purpose, and easy to implement. We used a combo of bootstrap, trich, material UI, and data visualization components to allow marketing and product to interact with a wide range of sentiment and churn data analytics based on key markets, demographics, and product type.

Plotly Dash Feature Ratings

8.8
Connect to Multiple Data Sources
9
Extend Existing Data Sources
9
Automatic Data Format Detection
8
MDM Integration
9
10.0
Visualization
10
Interactive Data Analysis
10
5.0
Interactive Data Cleaning and Enrichment
1
Data Transformations
10
Data Encryption
1
Built-in Processors
8
10.0
Multiple Model Development Languages and Tools
10
Automated Machine Learning
Not Rated
Single platform for multiple model development
10
Self-Service Model Delivery
10
9.5
Flexible Model Publishing Options
9
Security, Governance, and Cost Controls
10

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