Data Science Workbench Reviews

13 Ratings
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Score 7.4 out of 100

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Reviews (1-2 of 2)

Anonymous | TrustRadius Reviewer
September 15, 2019

Cloudera review

Score 6 out of 10
Vetted Review
Verified User
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Likelihood to Recommend

The use cases are specific to my industry, and we’re implemented for experimentation and scoring of predictive models.
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Bharadwaj (Brad) Chivukula | TrustRadius Reviewer
February 14, 2018

Exciting tool from Cloudera

Score 8 out of 10
Vetted Review
Verified User
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Likelihood to Recommend

  • 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.
Read Bharadwaj (Brad) Chivukula's full review

Data Science Workbench Scorecard Summary

Feature Scorecard Summary

Connect to Multiple Data Sources (1)
6
Extend Existing Data Sources (1)
7
Automatic Data Format Detection (1)
7
MDM Integration (1)
8
Visualization (1)
9
Interactive Data Analysis (1)
9
Interactive Data Cleaning and Enrichment (1)
8
Data Transformations (1)
8
Data Encryption (1)
8
Built-in Processors (1)
7
Multiple Model Development Languages and Tools (1)
9
Single platform for multiple model development (1)
10
Self-Service Model Delivery (1)
10
Flexible Model Publishing Options (1)
10
Security, Governance, and Cost Controls (1)
4

About Data Science Workbench

Cloudera Data Science Workbench enables secure self-service data science for the enterprise. It is a collaborative environment where developers can work with a variety of libraries and frameworks.
Categories:  Hadoop-Related,  Data Science

Data Science Workbench Technical Details

Operating Systems: Unspecified
Mobile Application:No