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What is Kedro?

Kedro is an essential framework that promotes clean practices in the field of data science. By incorporating software engineering principles, it significantly boosts the productivity of machine-learning projects. A Kedro project offers a well-organized framework for handling complex data workflows and machine-learning pipelines. This structured approach enables practitioners to reduce the time spent on tedious implementation duties, allowing them to focus more on tackling innovative challenges. Furthermore, Kedro standardizes the development of data science code, which enhances collaboration and problem-solving among team members. The transition from development to production is seamless, as exploratory code can be transformed into reproducible, maintainable, and modular experiments with ease. In addition, Kedro provides a suite of lightweight data connectors that streamline the processes of saving and loading data across different file formats and storage solutions, thus making data management more adaptable and user-friendly. Ultimately, this framework not only empowers data scientists to work more efficiently but also instills greater confidence in the quality and reliability of their projects, ensuring they are well-prepared for future challenges in the data landscape.

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

Amazon SageMaker
Apache Airflow
Apache Spark
Azure Databricks
Azure Machine Learning
Cloudera
Cloudera Data Platform
Dask
Docker
Gemini Enterprise Agent Platform
IBM Db2 Big SQL
Jupyter Notebook
Kubeflow
MLflow
Matplotlib
Plotly Dash
Python
pandas

Integrations Supported

Amazon SageMaker
Apache Airflow
Apache Spark
Azure Databricks
Azure Machine Learning
Cloudera
Cloudera Data Platform
Dask
Docker
Gemini Enterprise Agent Platform
IBM Db2 Big SQL
Jupyter Notebook
Kubeflow
MLflow
Matplotlib
Plotly Dash
Python
pandas

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

Kedro

Company Website

kedro.org

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

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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