Perform real-time analysis

Real-time analytics perform processing on data ingested via a feed, analyzing each individual message as it is received. Real-time analytics are used especially for transforming data, geofencing, and incident detection. Analytics conclude with one or more outputs such as storing data in a feature layer or sending an email alert.

Examples of real-time analysis

  • As an emergency operations manager, you can track and archive the current locations of your field crews in real-time, send alerts if crew is inside a restricted zone, and calculate the distance of the field crews from their assigned base of operations.
  • As a supply chain analyst at an oil & gas company, you can connect to an Automatic Identification System (AIS) data stream to monitor your vessels, calculate expected arrival information, and understand when vessels are either inside or outside areas of interest.
  • As an environmental scientist managing a large number of sensors, you can archive observations for later processing in a big data analytic.

Components of a real-time analytic

There are four components of a real-time analytic:

  • Feeds:
    • A feed is a real-time stream of data coming into ArcGIS. Feeds typically connect to external sources of observational data such as Internet of Things (IoT) platforms, message brokers, or third-party API's. Feeds parse incoming tabular, point, polyline, or polygon data and expose it for analysis and visualization. For more information on feeds and available feed types, see What is a feed?
  • Sources:
    • A data source is used to load static or near real-time data in a big data analytic. In real-time analytics, data sources load data used in conjunction with tools that require an ancillary spatial or tabular dataset to enrich, filter, join to, or calculate distance from events. For more information on sources and available source types, see What is a data source?
    • Data sources in a real-time analytic are only utilized as a secondary dataset in applicable tools, such as Join Features, Filter by Geometry, Calculate Distance, etc.
  • Tools:
    • Tools process or analyze events coming in from feeds. There can be multiple tools in an analytic or no tools at all.
    • Tools can be connected to each other where the output of one tool represents the input of the next tool.
    • Not all tools available in big data analytics are available in real-time analytics. This is because some tools such as Find Hot Spots analyze an entire set of data at once. Real-time analytics by contrast operate on each incoming message individually.
  • Outputs:
    • An output defines what should be done with each event as it is processed by the real-time analytic.
    • There are many output options available including storing features to a new or existing feature layer, sending an email, sending messages to Kafka or RabbitMQ , and more. For additional information, see What is an output? and Fundamentals of analytic outputs.
    • The events coming from a tool or feed can be sent to multiple outputs.