Name: Cloudera Data Science Workbench
Rating: 6.7 (13 reviews)
Author: Cloudera

Help Desk

Web and Video Conferencing

Customer Support

Beta Testing

Continuous Integration

Development

Alumni Management

Education

Business Intelligence (BI)

Collaboration

Contract Analysis

Demand Planning

Emissions Management

Knowledge Management

Online Notary

Payment Facilitation

Enterprise

Accounting

Travel Management

Finance and Accounting

Applicant Tracking

Corporate Learning Management

HR Management

HR Service Delivery

Payroll

Talent Intelligence

Talent Management

Workforce Analytics

Workforce Management

Human Resources

AIOps

API Design

App Development

Cloud Storage

Data Center Backup

Data Center Networking

Data Center Outsourcing (Canada)

Data Integration

Data Replication

Database-as-a-Service (DBaaS)

Enterprise Printing

Fraud Detection

Integration Platform as a Service (iPaaS)

Managed Detection and Response (MDR)

Mobile Data Security

Network Performance Monitoring

Secure Access Control

Service Virtualization

Value Stream Management

Information Technology

A/B Testing

Ad Serving & Retargeting

All-in-One Marketing

Content Management

Content Marketing

Creative Management

Ecommerce Personalization

Email Marketing

Market Research

Marketing Automation

Marketing Resource Management

Social Media Analytics

Social Media Management

Survey & Forms Building

Web Analytics

Marketing

Project Management

Professional Services

Customer Onboarding

Customer Relationship Management (CRM)

Point of Sale

Predictive Sales Analytics

Sales Consulting

Sales Dialer

Sales Incentive Compensation Management

Sales Training

Sales

Virtualization Security

Security

Financial Services CRM

Hospital Management

Medical Office EMR & EHR

Revenue Cycle Management (RCM)

Shipping

eDiscovery

Vertical-Specific

Find top rated software and services based on in-depth reviews from verified users. 400+ software categories including PaaS, NoSQL, BI, HR, and more.

Jupyter Notebook

Open Source

Posit

Posit (formerly RStudio)

Amazon SageMaker

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Databricks Data Intelligence Platform

Databricks

Anaconda

Azure Machine Learning

Microsoft

Starburst Enterprise

Starburst Data

Oracle Machine Learning

Oracle

Tableau Desktop

Tableau

SAS Viya

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.

KNIME Business Hub

KNIME Community Hub  Personal Plan

KNIME Community Hub  Team Plan

KNIME Analytics Platform

Saturn Cloud

Cloudera Data Science Workbench

Data Science

Cloudera Data Science Workbench 1.4 Accelerates Everyday Workflows for Data Scientists

​With its modern, open platform and enterprise tools, Cloudera is enabling clients to build and deploy Machine Learning (ML) and Artificial Intelligence (AI) solutions at scale, efficiently and securely, anywhere they want.​

​In this CoolTalks session, we explore what we can achieve with Cloudera in terms of Machine Learning and Data Visualisation. We showcase Cloudera Machine Learning (CML), Cloudera Data Science Workbench (CDSW), and Cloudera DataViz, with a hands-on demo to show you how it all comes together.

CoolTalks 2021 - Machine Learning and Data Visualisation with Cloudera​

Demo de Cloudera Data Science Workbench con vuelos comerciales en R

Likelihood to Recommend

Support Rating

Platform Connectivity

Data Exploration

Data Preparation

Platform Data Modeling

Model Deployment

Connect to Multiple Data Sources

Extend Existing Data Sources

Automatic Data Format Detection

MDM Integration

Visualization

Interactive Data Analysis

Interactive Data Cleaning and Enrichment

Data Transformations

Data Encryption

Built-in Processors

Multiple Model Development Languages and Tools

Automated Machine Learning

Single platform for multiple model development

Self-Service Model Delivery

Flexible Model Publishing Options

Security, Governance, and Cost Controls

Cloudera presents a unified Platform for Big Data, an enterprise data hub built on Apache Hadoop™.

Cloudera offers enterprises one place to store, process and analyze data, to extend the value of existing investments while enabling fundamental new ways to derive value from data. Cloudera offers everything needed on a journey to an enterprise data hub, including software for business critical data challenges such as storage, access, management, analysis, security and search. As an educator of Hadoop professionals, Cloudera has trained over 40,000 individuals worldwide. Over 800 partners and a seasoned professional services team help deliver greater time to value. Finally, Cloudera provides proactive and predictive support to run an enterprise data hub with confidence. Leading organizations in every industry plus top public sector organizations globally run Cloudera in production.

Behind some of the top minds in Big Data, including Doug Cutting, who invented Hadoop, Cloudera enhances the storage and processing technologies originally developed by the world’s biggest Web companies. Today, Cloudera is a market leader in Hadoop with tens of thousands of nodes under management, as well as the top contributor of code to the Hadoop ecosystem. Markets include financial services, government, telecommunications, media, web, advertising, retail, energy, bioinformatics, pharma/healthcare, university research, oil and gas, gaming and more.

Cloudera

Ability to connect to a wide variety of data sources

Ability to connect to a wide variety of data sources including data lakes or data warehouses for data ingestion

Use R or Python to create custom connectors for any APIs or databases

Automatic detection of data formats and schemas

Integration with MDM and metadata dictionaries

Ability to explore data and develop insights

The product’s support and tooling for analysis and visualization of data.

Ability to analyze data interactively using Python or R Notebooks

Access to visual processors for data wrangling

Use visual tools for standard transformations

Library of processors for data quality checks

Access to multiple popular languages, tools, and packages such as R, Python, SAS, Jupyter, RStudio, etc.

Tools to help automate algorithm development

Single place to build, validate, deliver, and monitor many different models

Multiple model delivery modes to comply with existing workflows

Tools for deploying models into production

Publish models as REST APIs, hosted interactive web apps or as scheduled jobs for generating reports or running ETL tasks.

Built-in controls to mitigate compliance and audit risk with user activity tracking

Microsoft Azure

Apache Hadoop

Apache HBase

Apache Solr

GitHub

Kubernetes

Sr.Technical Manager/Delivery Manager

Cloudera Data Science Workbench 2018-02-14 10:38:55

Palo Alto Networks Next-Gen CASB

Experian Pandora, now part of Aperture Data Studio

Experian Aperture Data Studio

Experian PowerCurve

Azure Data Science Virtual Machines (DSVM)

Cloudera Data Science Workbench 2020-06-29 03:30:09

Cloudera Data Science Workbench 2019-09-13 11:03:27

TrustRadius is a technology and business research firm based in Austin, Texas. The company is known as a review platform for verified B2B technology and software reviews through a proprietary algorithm and human verification.

TrustRadius

Licensing options

Not flexible

Lacks features

Lacks some features

Quite simple

Multiple languages

Self service

Service analytics

Browser based

Self service analytics

Larger organizations

Analytics platform

Easy access

Way to keep

Home

Data Science Platforms

Data Science Workbench

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 setting.Use of data to project sales numbers, marketing etc.

One single IDE (browser based application) that makes Scala, R, Python integrated under one tool
For larger organizations/teams, it lets you be self reliant
As it sits on your cluster, it has very easy access of all the data on the HDFS
Linking with Github is a very good way to keep the code versions intact

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

As the tool itself can access all the HDFS, Spark data easily, the wait time between teams has reduced
Installation was a breeze, and ramp up time was fairly easy

Microsoft Azure Machine Learning Workbench

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 phase. It is also being used by data scientists in Analytics department for building machine learning models. On top of that, it is also used by business analyst in Big Data Monetization business units for exploration and reporting. CDSW reduces time to market from exploring, modeling, and deploying to production.

Enterprise grade security.
Self-service analytics platform.
Popular programming support.

Data Science Workbench

Overview

What is Data Science Workbench?