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What is esDynamic?

Enhance your security testing process, from setting up your environment to analyzing your data processing results, with esDynamic, a tool designed to optimize your workflow, conserve valuable time, and increase the efficiency of your attack methodologies. Discover this versatile and comprehensive Python-based platform, meticulously crafted to assist you throughout every phase of your security assessments. Customize your research environment to meet your unique requirements by effortlessly adding new tools, integrating devices, and modifying data as needed. In addition, esDynamic provides an extensive library of materials on complex topics that would typically require extensive research or the expertise of a specialized team, granting you quick access to expert insights. Say goodbye to chaotic data and fragmented information; instead, adopt a cohesive workspace that promotes seamless data and insight sharing among your team, thereby enhancing collaboration and accelerating the discovery process. Additionally, strengthen and streamline your work within JupyterLab notebooks, facilitating easy sharing among team members to ensure that everyone remains aligned. This comprehensive strategy can drastically revolutionize your approach to security testing, ultimately leading to more effective outcomes. By leveraging these capabilities, you can not only improve your results but also foster a culture of continuous improvement within your security testing efforts.

What is Cloudera Data Science Workbench?

Facilitate the transition of machine learning from conceptual frameworks to real-world applications with an intuitive experience designed for your traditional platform. Cloudera Data Science Workbench (CDSW) offers a convenient environment for data scientists, enabling them to utilize Python, R, and Scala directly from their web browsers. Users can easily download and investigate the latest libraries and frameworks within adaptable project configurations that replicate the capabilities of their local setups. CDSW guarantees solid connectivity not only to CDH and HDP but also to critical systems that bolster your data science teams in their analytical tasks. In addition, Cloudera Data Science Workbench allows data scientists to manage their analytics pipelines autonomously, incorporating built-in scheduling, monitoring, and email notifications. This platform not only fosters the rapid development and prototyping of cutting-edge machine learning projects but also streamlines the deployment process into a production setting. With these workflows made more efficient, teams can prioritize delivering meaningful outcomes while enhancing their collaborative efforts. Ultimately, this shift encourages a more productive environment for innovation in data science.

Media

Media

Integrations Supported

Cloudera
Cloudera Data Platform
IBM Db2 Big SQL
JupyterLab
Python
esChecker

Integrations Supported

Cloudera
Cloudera Data Platform
IBM Db2 Big SQL
JupyterLab
Python
esChecker

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

eShard

Company Location

France

Company Website

eshard.com/esdynamic

Company Facts

Organization Name

Cloudera

Date Founded

2008

Company Location

United States

Company Website

www.cloudera.com/products/data-science-and-engineering/data-science-workbench.html

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

Software Testing

Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

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