Eliminate the complexity of data science on Hadoop and Spark
Code Free Machine Learning for Hadoop & Spark
Build and run predictive models in Hadoop without having to code in Spark
- Create predictive models using the RapidMiner Studio visual workflow designer
- Expand beyond MLlib to tackle a broader set of use cases including time series and text analytics
- Amazon EMR, Apache, Microsoft’s Azure HDInsight, HDP, Cloudera, and MapR and more
Harness the Power of Hadoop Clusters
Run data prep and machine learning jobs directly inside Hadoop
- RapidMiner SparkRM enables all operations and data process flows in RapidMiner Studio to run in-parallel inside Hadoop
- Jobs are automatically translated into Spark and Hive
- No additional software is required in the Hadoop cluster environment
Supports Hadoop Standards & Security
Maximize your investment in the Hadoop ecosystem
- Re-use existing SparkR, PySpark, Pig, and HiveQL code
- Reduce risk and enforce regulatory compliance with built-in Apache Sentry & Apache Ranger support
- Deploy HDFS encryption to comply with data security policies
Learn more about RapidMiner Radoop
Many data scientists and analysts don’t have a deep understanding of Hadoop, so they struggle with solving analytics problems in a distributed environment. Watch this webinar to learn best practices for extracting value from Hadoop.
Hadoop offers great promise to organizations looking to gain a competitive advantage from data science. But deploying Hadoop can be extraordinarily complex and time consuming, making it difficult to gain the insights.
This webinar shows you real world use cases for machine learning on Hadoop using RapidMiner’s new SparkRM capabilities.