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Cloudera Data Science & Engineering

Never leave your predictions to chance

Cloudera Data Science provides better access to Apache Hadoop data with familiar and performant tools that address all aspects of modern predictive analytics. Using Cloudera, your organization will be able to perform advanced data engineering, exploratory data science, and machine learning at scale. And that’s regardless of where your data lives—on-premise, across public clouds, or both. Because the right insights today lead to better business decisions tomorrow.

The flexibility and performance only we can deliver

There’s no better modern data processing solution for batch, real-time, and streaming workloads than Cloudera. By utilizing technology like Apache Spark, your advanced processing jobs can be completed significantly faster than traditional technology—giving your business fast, scalable SQL on large distributed data, as well as a flexible processing engine with a functional style programming API. You’ll also have better visibility on the data you are ingesting thanks to interactive search and SQL access on streaming data.

Learn more about Apache Spark

For all things cloud

Why wouldn’t you be doing as many workloads as possible in the cloud? Whether you’re launching multiple workloads on a multi-tenant environment or designing jobs that leverage cloud infrastructure for specific jobs like ETL and exploratory data science, Cloudera Enterprise removes compute and storage constraints to achieve a lower cost of ownership while data is persisted across the lifecycle of your environment. You’ll even cut more costs by utilizing infrastructure at it’s cheapest via spot instances on Amazon.

Data engineering and data science in the public cloud

Do what you do, better

Cloudera gives you the ability to do data science exploration over large datasets, while giving engineers the tools they need to build needed data pipelines and launch multi-tenant applications—all on a single product with reliable policy, access, and security controls to provide visibility into the entire lifecycle of data.

Learn more about the Cloudera Data Science Workbench

Say goodbye to obstacles

It’s never been easier to scale your business according to your most ambitious goals. We’ll enable your business to do exploratory data science at scale and deliver machine learning models that can take advantage of massive parallel compute and expanded data streams. With Cloudera, you have a rich programming interface and modern libraries to ensure your models are deployed and stable in production.

Watch the video: machine learning loves hadoop

Key use cases

Data processing
Choose the best fit for your workload: batch, real-time, or interactive:

  • High velocity real-time data ingest: ability to ingest data from all sources and of all types
  • Scalable, high-performance architecture
  • More data types and better data access

Machine learning
Support high-performance, ad hoc access for more users and the fastest time to insights:

  • Distributed machine learning
  • Familiar API’s
  • Integrated batch and streaming

Stream processing
Real-time and continuous processing of data streams:

  • Fault-tolerant and high-performance processing of continuous streams of data
  • Similar API and programming paradigm for batch and stream processing
  • Simplified APIs for common streaming tasks
  • Combine with MLlib for predictive analytics on streaming data

Exploratory data science
Expanding the power of statistical programing to large data sets:

  • Familiar API’s
  • Integrated batch and streaming
Analyst Report

Taneja Group Spark market adoption report


What is Data Science?