This topic introduces the major concepts involved in EnOS Data Asset Management.
Broadly speaking, the generation of data can be considered as a series of discrete events. When drawing these discrete events on a time axis, an event stream or data stream is formed. Stream data consists of these endless event streams.
Both offline data and stream data are normally sent as logs. Unlike traditional offline data, stream data is generated continuously by a lot of data sources. However, the size of stream data is normally smaller than that of the offline data.
The common sources of stream data can be the devices connected to a data center, the telemetry data of devices, and the log files generated by mobile or web applications.
Data ingested from different devices and sensors is of different types. EnOS Stream Processing Service supports analysis and storage of multiple types of data, including AI, DI, PI and generic types. The data types of measuring points are defined when creating device models.
Data ingested from devices or integrated from offline message channels, after being processed by the stream processing engine, can be stored in the target storage system based on the configured storage policies. According to data types and usage, data can be stored in different systems, for different storage time, and be retrieved by different methods.
EnOS provides the data subscription service to help users obtain and make use of device real-time data efficiently. With data subscription jobs running, data subscription service will push subscribed data to the users’ application automatically. The subscribed data can be device real-time data and alert data.