Overview
Product Information on Cloudera AI
What is Cloudera AI?
Cloudera AI Pricing
Overall experience with Cloudera AI
“CML quick review”
“Good sandbox environment for starter Data Science.”
About Company
Company Description
Cloudera focuses on enabling transformation of complex data into clear and actionable insights. It provides an enterprise data cloud for data management, catering to multiple locations from the Edge to AI. Leveraging the continuous development aspects of the open source community, Cloudera caters to the digital transformation needs of large-scale enterprises around the world.
Company Details
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Key Insights
A Snapshot of What Matters - Based on Validated User Reviews
Reviewer Insights for: Cloudera AI
Deciding Factors: Cloudera AI Vs. Market Average
Performance of Cloudera AI Across Market Features
Cloudera AI Likes & Dislikes
1) Collaborative development and quick integration with Github 2) Nice and intuitive application deployment (including Streamlit, Flask and Gradio) 3) AMPs are certainly helpful to get started quickly.
Isolation Environment for each Data Scientists on Image Docker
The platform offers a single environment which caters to diverse needs of data scientists , analysts and engineers. It provides a wide range of libraries that simplify the process of model deployment. The platform is built to handle large scale data processing and complex computations.
1) Application deployment should have feature to auto-notify when application is down or unavailable 2) Include more GenAI AMPs to dive into CML capabilities 3) Slow feature releases by Cloudera vendor
Hard to passing parameter between scripts.
Ensuring the availability of sufficient computing resources is crucial to maintain smooth operations which can be a bit challenging.
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Peer Discussions
Cloudera AI Reviews and Ratings
- Data Scientist10B+ USDHealthcare and BiotechReview Source
CML quick review
The CML platform certainly provides a lot of flexibility to developers in selecting IDEs and session profiles for model development. However, CML needs to improve on it's Model Registry, error messages and application deployment area. - MANAGEMENT CONSULTANT10B+ USDMiscellaneousReview Source
Streamline data science process and enhance collaboration
Cloudera platform has empowered our organization with robust capabilities for data science and machine learning. It provides a collaborative environment for data scientists to develop and manage mill models effectively. It has allowed us to extract meaningful insights from data and develop predictive models that drive informed business decisions. - INSTRUCTIONAL DESIGNER<50M USDHealthcare and BiotechReview Source
Empowering enterprise scale AI with unified collaboration, scalability and integration
It offers a unified environment that simplifies collaboration between data scientist and IT teams. The scalability is impressive, I was able to process and analyze massive datasets without any performance bottlenecks, which greatly enhanced the ML capabilities. Whereas it is a little tricky to navigate, documentation and support lacked clear examples and explanation, it resources requirement are high. - Data Scientist50M-1B USDRetailReview Source
Very useful tool to collaborate in data science projects
good to collaborate. When using notebooks as IDE the sessions remain active. There is no timeout if we are not using it. - BIGDATA PROGRAM MANAGER1B-10B USDRetailReview Source
The best
Very good tool to create ML and AI workflows, easy to integrate with our datalake