What users are saying about
13 Ratings
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Score 7.5 out of 101

Likelihood to Recommend

Data Science Workbench

  • If you already have a Cloudera partnership and a cluster, having this is a no brainer.
  • It integrates well with your existing ecosystem and it immediately starts working on projects, accessing full datasets and share analysis and results.
  • With the inclusion of Kubernetes, CPU and memory across worker nodes can be managed effectively.
Bharadwaj (Brad) Chivukula profile photo

Feature Rating Comparison

Platform Connectivity

Data Science Workbench
7.0
Connect to Multiple Data Sources
Data Science Workbench
6.0
Extend Existing Data Sources
Data Science Workbench
7.0
Automatic Data Format Detection
Data Science Workbench
7.0
MDM Integration
Data Science Workbench
8.0

Data Exploration

Data Science Workbench
9.0
Visualization
Data Science Workbench
9.0
Interactive Data Analysis
Data Science Workbench
9.0

Data Preparation

Data Science Workbench
7.8
Interactive Data Cleaning and Enrichment
Data Science Workbench
8.0
Data Transformations
Data Science Workbench
8.0
Data Encryption
Data Science Workbench
8.0
Built-in Processors
Data Science Workbench
7.0

Platform Data Modeling

Data Science Workbench
9.7
Multiple Model Development Languages and Tools
Data Science Workbench
9.0
Single platform for multiple model development
Data Science Workbench
10.0
Self-Service Model Delivery
Data Science Workbench
10.0

Model Deployment

Data Science Workbench
7.0
Flexible Model Publishing Options
Data Science Workbench
10.0
Security, Governance, and Cost Controls
Data Science Workbench
4.0

Pros

Data Science Workbench

  • The ability to use multiple languages.
  • GitHub integration.
  • Scalable.
No photo available

Cons

Data Science Workbench

  • Not as great as RStudio; lacks some features when compared with it
  • It is quite simple still (because its very early in its initiative), and companies may want to wait until they see a more developed product
Bharadwaj (Brad) Chivukula profile photo

Support

Data Science Workbench

Data Science Workbench 5.0
Based on 1 answer
It is expensive and difficult to install and maintain.
No photo available

Alternatives Considered

Data Science Workbench

Both the tools have similar features and have made it pretty easy to install/deploy/use. Depending on your existing platform (Cloudera vs. Azure) you need to pick the Workbench. Another observation is that Cloudera has better support where you can get feedback on your questions pretty fast (unlike MS). As its a new product, I expect MS to be more efficient in handling customers questions.
Bharadwaj (Brad) Chivukula profile photo

Return on Investment

Data Science Workbench

  • Paid off for demonstration purposes.
No photo available

Pricing Details

Data Science Workbench

General

Free Trial
Free/Freemium Version
Premium Consulting/Integration Services
Entry-level set up fee?
No

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