https://store-images.s-microsoft.com/image/apps.33217.b3d2b703-2d16-408f-a6fe-48748fada5a2.42d0a46f-1b3f-4b04-9ea8-07e663b2912a.a237113f-485f-4524-9ced-ad05474ab6ba
Pentaho Data Integration Server 9.5.0.0
Hitachi Vantara
Pentaho Data Integration Server 9.5.0.0
Hitachi Vantara
Pentaho Data Integration Server 9.5.0.0
Hitachi Vantara
Pentaho Data Integration Server | Enterprise Edition from Hitachi Vantara | Pentaho DI 9.5 EE. Linux/Unix Ubuntu 20.04 LTS - 64-bit with PostgreSQL 13
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
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