Skip to main content
TrustRadius
Data Science Workbench

Data Science Workbench

Overview

What is 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.

Read more

Learn from top reviewers

The perfect analytics and data science platform for your Cloudera Data Platform

Rating: 9 out of 10
November 18, 2020
IncentivizedVetted ReviewVerified User
Cloudera Data Science Workbench (CDSW) is mainly being used by data engineers in the IT department for Big Data Analytics pipeline from ingestion until feature extraction phas...
Continue reading
Verified user
Professional
Cloudera Data Science Workbench1 year of experience

Cloudera review

Rating: 6 out of 10
September 15, 2019
IncentivizedVetted ReviewVerified User
Cloudera is being used on a 6-node Hadoop cluster used for sandbox demonstrations and development. The business problem it was selected to address was the ability to create Ma...
Continue reading
Verified user
Professional
Cloudera Data Science Workbench1 year of experience

Exciting tool from Cloudera

Rating: 8 out of 10
February 14, 2018
IncentivizedVetted ReviewVerified User
Used by the Data Science/Engineering Team as a collaboration tool.Combines all the efforts of various departments under a single IDE and provides a holistic view in the retail...
Continue reading
Bharadwaj (Brad) Chivukula
Manager - Information Technology
Sr.Technical Manager/Delivery Manager
Nisum Technologies, Inc.
Cloudera Data Science Workbench1 year of experience
Log in with LinkedIn to see content from your network
Return to navigation

Pricing

View all pricing
Data Science Workbench

Data Science Workbench

N/A
Unavailable

What is 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.

Entry-level set up fee?

  • No setup fee

Offerings

  • Free Trial
  • Free/Freemium Version
  • Premium Consulting/Integration Services

Would you like us to let the vendor know that you want pricing?

4 people also want pricing

Alternatives Pricing

Spotfire

Spotfire

$0.99
Per Hour (Starting)
What is Spotfire?

Spotfire, formerly known as TIBCO Spotfire, is a visual data science platform that combines visual analytics, data science, and data wrangling, so users can analyze data at-rest and at-scale to solve complex industry-specific problems.

KNIME Analytics Platform

KNIME Analytics Platform

Free
What is KNIME Analytics Platform?

KNIME enables users to analyze, upskill, and scale data science without any coding. The platform that lets users blend, transform, model and visualize data, deploy and monitor analytical models, and share insights organization-wide with data apps and services.

Return to navigation

Product Demos

Demo de Cloudera Data Science Workbench con vuelos comerciales en R

YouTube

CoolTalks 2021 - Machine Learning and Data Visualisation with Cloudera​

YouTube

Cloudera Data Science Workbench 1.4 Accelerates Everyday Workflows for Data Scientists

YouTube
Return to navigation

Product Details

What is 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.

Data Science Workbench Technical Details

Operating SystemsUnspecified
Mobile ApplicationNo
Return to navigation

Comparisons

View all alternatives
Return to navigation

Reviews and Ratings

(13)

Reviews

(1-1 of 1)
Companies can't remove reviews or game the system. Here's why

Cloudera review

Rating: 6 out of 10
Incentivized
September 15, 2019
Verified User
Vetted Review
Verified User
Cloudera Data Science Workbench
1 year of experience
Use Cases and Deployment Scope
Cloudera is being used on a 6-node Hadoop cluster used for sandbox demonstrations and development. The business problem it was selected to address was the ability to create Machine Learning models in an enterprise environment based on data lake architecture.
Pros and Cons
  • The ability to use multiple languages.
  • GitHub integration.
  • Scalable.
Likelihood to Recommend
The use cases are specific to my industry, and we’re implemented for experimentation and scoring of predictive models.
Data Science Workbench Feature Ratings
Platform Connectivity (4)
70%
7.0
Connect to Multiple Data Sources
60%
6.0
Extend Existing Data Sources
70%
7.0
Automatic Data Format Detection
70%
7.0
MDM Integration
80%
8.0
Data Exploration (2)
90%
9.0
Visualization
90%
9.0
Interactive Data Analysis
90%
9.0
Data Preparation (4)
77.5%
7.8
Interactive Data Cleaning and Enrichment
80%
8.0
Data Transformations
80%
8.0
Data Encryption
80%
8.0
Built-in Processors
70%
7.0
Platform Data Modeling (3)
96.66666666666666%
9.7
Multiple Model Development Languages and Tools
90%
9.0
Single platform for multiple model development
100%
10.0
Self-Service Model Delivery
100%
10.0
Model Deployment (2)
70%
7.0
Flexible Model Publishing Options
100%
10.0
Security, Governance, and Cost Controls
40%
4.0
Return on Investment
  • Paid off for demonstration purposes.
Support Rating
5
It is expensive and difficult to install and maintain.
Return to navigation