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Pentaho Data Integration

Enable users to ingest, blend, cleanse and prepare diverse data from any source. With visual tools to eliminate coding and complexity, Pentaho puts the best quality data at the fingertips of IT and the business.
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Easy to Use With the Power to Integrate All Data Types

INTUITIVE DRAG-AND-DROP DATA INTEGRATION PLUS DATA-AGNOSTIC CONNECTIVITY SPANS ALL DATA SOURCES

  • Graphical ETL designer simplifies the creation of data pipelines
  • Rich library of prebuilt components help to access, prepare and blend data
  • Powerful orchestration capabilities coordinate and combine transformations

Big Data Integration With Zero Coding Required

ACCELERATE DESIGN AND DEPLOYMENT OF BIG DATA ANALYTICS BY UP TO 15X VS. HAND-CODING TECHNIQUES

  • Eliminate manual programming and scripting with big-data integration tools
  • Seamlessly switch between execution engines, such as Apache Spark and Pentaho
  • Gain robust support for Hadoop distributions, Spark, object stores and NoSQL

ENTERPRISE PLATFORM TO ACCELERATE THE DATA PIPELINE

Manage the Analytical Data Pipeline Within a Single Platform

Increase Time Efficiency

Dynamic and reusable data integration templates enable users to create transformations on the fly.

Keep Up With Data Growth

Multithreaded data integration engine scales up and out and includes deployment to clustered and cloud environments.

Simplify Administration

Features include performance monitoring, job rollback and restart, and an operations mart to streamline usage auditing.

BROAD AND ADAPTIVE BIG DATA INTEGRATION

Support Your Teams in This Rapidly Changing Big Data Environment

Greater Flexibility

Manages and processes data in on-premises, hybrid and multicloud environments, insulated from big-data ecosystem changes.

Data-Agnostic Design

Supports Hadoop, NoSQL, object store and analytics database distributions from a variety of software providers.

Real-Time Data Ingestion

Enables real-time data ingestion from Apache Kafka using Spark streaming and IoT protocols, without any rework.

BOOST YOUR TEAM'S PRODUCTIVITY ACROSS THE DATA PIPELINE

Collaborative Data Prep and Faster Access to Analytics

Support Multiple Engines

Seamlessly switch or combine data-processing engines with in-cluster execution to increase data productivity.

Enable In-Line Analytics

Reduce the time needed to provide data models for business users, improving collaboration between business and IT.

Reduce Development Time

Use data services to virtualize transformed data, making data sets immediately available for reports and applications.

OPERATIONALIZE DATA SCIENCE

Improve Alignment Between Data Engineers and Data Scientists

Prepare and Orchestrate Model Data

Prepare and blend traditional data with big data sources, like sensors and social media, for machine learning models.

Train, Tune, and Test Models

Seamlessly train, tune and test models for languages like R and Python, using libraries like Spark MLlib and Weka.

Deploy and Operationalize Models

Analyze results by easily embedding machine and deep learning models into data pipelines without coding knowledge.
Pentaho Data Integration
Learn how PDI delivers analytics-ready data to end users faster with visual tools that reduce time and complexity.
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TDWI Report: Improving Data Prep for Business Analytics
Best practices for implementing the right strategy, processes, and technologies to solve data preparation trials.
READ THE REPORT

READ CUSTOMER STORIES FOR PENTAHO DATA INTEGRATION

To extract millions of data flows and transform them into meaningful information our customers can use to enhance energy delivery processes, you have to do a lot of work. Pentaho makes it easier.

– Dan Hopkinson, Head of Network and EMI Services, ElectraLink

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