The Industrial DataOps Solution for Industry 4.0

Collect and publish data over open standards and native connections—eliminating the need for custom-coded integrations. Easily configure and manage multiple connections and their respective inputs and outputs within the script-free interface. Collect data from SQL and REST source systems using dynamic requests leveraging inputs from other systems. Quickly integrate data from specialty systems and devices. Merge data from multiple systems into a complex modeled payload.

Collect and condition raw input data and then pass conditioned data to model instances or pipelines. Filter data through a deadband condition to reduce the jitter in a source sensor or measurement. Filter the data through an aggregate to buffer higher resolution data and provide statistical calculations using average, min, max, count, and delta at a slower rate to characterize the specified time period. Manipulate and transform raw input data into a usable format. Alarm on bad quality or stale data. Use the built-in transformation engine to standardize and normalize data for comparison and application mismatches. The transformation engine enables you to perform calculations, execute logic to define new “virtual property” values, and decompose complex strings at the Edge to improve data usability and reduce transmission volume. Define global JavaScript functions or load third-party JavaScript or Node packages, then use them in any expression within the Intelligence Hub.

Represent machines, products, processes, and systems with intelligent data models suited to your needs. Contextualize thousands of industrial data points by merging them with information from other systems, adding meta data, standardizing data attribute names and lists, and normalizing units of measure. Model hundreds of common assets in minutes with templatized inputs and instances and manage models through an intuitive attribute tree that enables model nesting.

Use the graphical Pipelines builder to curate complex data payloads for everything from MQTT brokers to historians to data warehouses and track the transformation of data through the pipeline. Use stages to read, filter, buffer, transform, format, and compress payloads. Read within and across Namespace hierarchies using the Smart Query stage. Use the On Change stage to enable event-based delivery and report-by-exception of any data source. Use the Switch stage to introduce conditional logic to your flow and the Model Validation stage to assess incoming data payloads against a model definition. Share data processing on-demand by calling between pipelines or securely exposing pipelines to the REST Data Server.

The REST Data Server acts as an API gateway for industrial data residing in OT systems, so any application or service with an HTTP client can securely request OT data in raw or modeled form directly from the Intelligence Hub—without requiring domain knowledge of the underlying systems. This API securely exposes the Intelligence Hub’s connections, models, instances, and pipelines as well as the underlying values. Use the REST Data Server with Callable Pipelines to gain an "Industrial Data API Builder" Connect to the REST Data Server to access the Intelligence Hub as a transactional, request-and-response interface and programmatically browse the full Industrial DataOps infrastructure.

Use the UNS client to visually discover and interrogate contents residing in any MQTT broker, negating the need for external testing clients. Simply select a connection and instantly visualize the namespace. The UNS Client can automatically detect and visualize message payloads including JSON, Sparkplug, text, and raw binary, and decode Protobuf to make payloads human readable for Sparkplug users. In addition to topic and message inspection, the UNS Client can also publish messages to topics.