"Pentaho Data Integration (PDI) manages data at scale for rapid business innovation, ease of use, self-service automation and orchestration of your data workflows

COMPONENTS INCLUDED:
Native connectivity and bulk-loading to most common data sources, including Amazon Redshift and Snowflake
Data services to virtualize transformations without staging, making data sets immediately available to reports and applications
Process streaming data in real time.
Native Containerization to support multi-cloud deployments

KEY FEATURES:
Code-free data transformation design that empowers 15x faster productivity versus hand-coding and executes in-cluster for high performance
Template-based approach to rapidly onboard data sources into Hadoop via metadata injection feature set
Ability to seamlessly switch between execution engines, such as Spark and the Pentaho native engine, to fit data volume and transformation complexity
Support for advanced analytics models from R, Python, Scala and Weka to operationalize predictive intelligence while reducing data prep time
Robust Dataflow Orchestration of pipeline
Support both structured and unstructured data

TOP BENEFITS:
50% Faster Implementation Time - seamlessly integrate a multitude of diverse on-premises, cloud, and edge data sources with speed and efficiency using modern data integration.
3x Improve Pipeline Quality - No-code functionality versus hand-coding data pipelines using an easy drag and drop interface for on-premises and cloud Hadoop data lake integration.
50% Faster Data Delivery - Produce stellar reports with intuitive processes and seamless integration that enhances the user experience, reduce data management costs, and create business value

TOP USE CASES:
Onboard, prepare, filter data pipelines at scale combining data from both on-premises and cloud-based data sources
Cloud Data migration across hybrid cloud environments
Modernize and process large data sets in a data lake and data warehouse
Intelligent cloud automation for rapid value creation"