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Pentaho Community, pentaho data integration community edition.#Pentaho #data #integration #community #edition


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Pentaho Community

Mainz, Germany. Nov 11-12, 2017.

Pentaho data integration community edition

Pentaho data integration community edition

Pentaho Community Edition 7.1

Improve Productivity and Performance for Big Data

Pentaho data integration community edition

Pentaho data integration community edition

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Browse through the Pentaho Marketplace website.

Pentaho data integration community edition

  1. Description
  2. Main Features
  3. Marketplace

An Engagement Mechanism

  • Participate in the Pentaho Community: By using Pentaho CE, you become part of an active and engaging Community and benefit from its open source contributions.
  • Make valuable contributions: The Pentaho open source projects deliver better, faster, and more reliable products that are time-tested by the community. Developers, testers, writers, implementers, and most of all users are directly involved as a team to make high-value software contributions.

A QA Environment

  • Test it: There are no better testers than people who actually use the Pentaho CE software, reporting bugs, making suggestions, and providing direction for the projects.

An Evaluation Platform

  • Build with CE: The flexibility of Pentaho CE enables you to jump-start your development, innovate, experiment, find a solution you like, and then upgrade to Pentaho EE when you are ready for production.

Pentaho data integration community edition Pentaho data integration community edition Pentaho data integration community edition Pentaho data integration community edition Pentaho data integration community edition

Quick Links

License

The open source platform thrives on participation and cooperation. There are several communication channels available where you can get in contact with the community including blogs, forums, IRC and the Pentaho Community Mailing List.

  • Complete Spark Support: Pentaho is the only vendor to support Spark with all data integration steps in a visual drag-and-drop environment. Unlike other vendors who require users to build Spark-specific data integration logic – and often require Java development skills – with Pentaho you only need to design your logic once, regardless of execution engine.
  • Adaptive Execution on Big Data: Transitioning from one engine for big data processing to another often means users need to re-write and debug their data integration logic for each engine, which takes time. Pentaho’s adaptive execution allows users to match workloads with the most appropriate processing engine, without having to re-write any data integration logic.
  • Prepare Better Data, Faster: More visualizations throughout the data prep process allows users to spot check data for quality issues and prototype analytic data, without switching in and out of tools or waiting until the very end to discover data quality problems. Now, users can interact with heat grids, geo maps, and sunbursts, as well as drill-down into data sets for further exploration.
  • Integrate 3rd Party Visualizations: Leverage an easy to use and flexible API with full documentation to integrate visualizations from third party libraries such as D3 or FusionCharts.

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