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GE Digital

Industrial Data Fabric

Turn your raw industrial data into insights with a scalable data foundations for Industrial IoT

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The opportunity and potential of industrial data

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The Industrial Internet and its network of connected machines has created a new frontier of competitiveness for data-driven decision making among industrial organizations. Data in the industrial world is growing faster than any other sector, and yet less than 3% of that data is tagged and used in a meaningful way. Every day, the monitoring and diagnostic center in Atlanta receives more than 200 billion data tags coming from 1 million sensors attached to 5,000 assets in power plants across more than 60 countries. And it's all run on Predix Platform.

Benefits of industrial data fabric

More than just gathering data

The challenge is not just gathering data from assets and systems, rather rapidly integrating, managing, and converting that data into actionable insights, leading to smarter business decisions and increased automation.

Scalable data foundation

Predix Platform's industrial data fabric is designed to connect raw data from asset with OT systems data, enterprise IT data, and any other third party data in order to create a scalable data foundation for industrial applications. It encompasses batch or streamlining ingestion, big data analytics runtime, processing, and storage of data and insights.

Managing industrial data

Industrial data is messier and faster moving that your typical enterprise data—arriving as multi-terabyte streams in different formats and from multiple sources such as equipment sensors, assets, and control systems. Industrial data is also often times captured in repositories and systems that are typically siloed, making it difficult for organizations to analyze and reuse.

Features of industrial data fabric

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Data ingestion

Predix Platform industrial data fabric supports the ingestion of virtually any streaming or batch data source. Most Industrial applications are event-centric, leverage streaming data through the Event Hub, which provides real-time data ingestion, data analysis, and workload execution.

Big data processing

Easily manage data pipelines, workload orchestration and job scheduling with native support for Spark, Hadoop, and serverless big data processing frameworks. Developers will find Insights useful when building Industrial applications that require real-time streaming data analytics at high volumes.

Flexible storage

Leverage a full range of structured and unstructured encrypted storage options, all selected and optimized for Industrial IoT solutions. Choose from Time Series for streaming sensor data, HDFS, NoSQL stores like Elastic and Cassandra, Object store, blob store or PostgresSQL for relational data.

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