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Data Platform#

Data Platform is a cutting-edge, event-driven system designed for real-time data processing and analytics. It enables seamless materialization of events into a high-performance, columnar database, ensuring fast and efficient storage and retrieval. With built-in capabilities for data enrichment, machine learning, and instant access via OData and other industry-standard interfaces, this platform empowers organizations to unlock insights, automate workflows, and drive intelligent decision-making at scale.

Data Platform is also responsible for generating and giving access to Canonical Data Model (CDM) data. This data model adheres to ISA-95 standards, ensuring compatibility with industrial automation and enterprise systems by defining structured models for data exchange and process integration. It is designed to be Manufacturing Execution System (MES) agnostic, enabling seamless integration with various MES platforms without dependency on specific vendor implementations. This approach supports interoperability, scalability, and flexibility, facilitating standardized data flows across production, inventory, and quality management systems. By aligning with ISA-95, the model promotes clarity in data organization and consistency in manufacturing operations, while remaining adaptable to diverse system architectures and evolving business requirements. Furthermore, this structured and standardized data model serves as a reliable foundation for reporting, analytics, and decision-making, enabling organizations to derive actionable insights and optimize performance.

The Data Platform page group enables the creation and management of all the entities used in the Data Platform ecosystem, which provide mechanisms to ingest and digest data and to automate workflows.

Administration#

  • Data Orchestrator - a page that provides access to a dashboard to view and configure the data orchestrations currently in use by the system.

Events#

  • IoT Event Definitions - a page that allows you to define and manage IoT Event Definitions, which represent the structure of the events that can be used to ingest data into Data Platform.
  • IoT Schema - a page that allows you to define and manage IoT Schemas, which specify generic data structures that can be reused when defining IoT Events.
  • Data Platform Workflows - automation workflows applicable to Data Platform scenarios; these workflows will run in real time whenever a new event is published, and can be used for numerous purposes, from event enrichment to real time machine learning predictions.

Data#

  • Data Manager - a link to the Grafana dashboards management page, where you can use the Cubes and OData plugins to access data from the Data Manager.
  • Data Sets - a page that allows you to define and manage Data Sets, which give access to all the data in Data Platform.

Machine Learning#

  • ML Model - a page that allows you to define and manage machine learning models; these models can be trained/validated/tested with the data in Data Platform, and then deployed and used to make real-time predictions for new data, as it is produced.

Asset Management#

  • Asset Directory - a page that allows you to create Asset Directories (tree-like structures) and associate Assets (such as dashboards, properties or others).

    • Asset - a subpage that allows you to create and associate Assets (such as dashboards, properties or others).

  • Asset Browser - a page that allows you to navigate through the available Asset Directories in the system, and view the associated data.

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