"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% Less Implementation Time - onboard multiple hundreds of varied on-premises, cloud, and edge data sources efficiently and quickly with 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"