Analytics

Data collected from devices, normalized and persistently stored is still useless for anything apart from very simple visualization on dashboards, gauges, charts, and tables. Anything more sophisticated requires processing that may start from raw value scaling and end up with advanced failure prediction.

Years of AggreGate evolution brought numerous analytical tools to the scene. Domain-specific data mining languages, object and process modeling engine, statistical process control instruments, visually designed multi-threaded workflows, topology and graph analysis tools, machine learning modules -- all these are instruments that bring business intelligence atop of “classical” IoT bricks.

The majority of data mining and slicing operations in AggreGate are visual. Spreadsheet-like formulas and SQL-like queries are probably the most complicated things system analysts should type on their keyboards. However, scripting and even programmatic extension of the platform is here, too.

Statistical Process Control

Statistics

Seamless unified storage and management of value trends and historical events in the server database. Statistical process control module for storing values with chronologically receding precision.

Expression Language

Expression Language

Expression language for flexible alert triggering rules, event filtering, and other data processing. Interactive Expression Builder component is available.

Query Language

Query Language

Integrated SQL-based query language for data mining and batch configuration updates.

Other Languages

Other languages

Even more domain-specific languages are available as additional AggreGate modules.

Models

Models

Object and process models employing sets of business rules for making automatic control decisions upon important events.

Classes

Classes

Classes are designed to store a large number of cross-linked objects in a persistent storage facility.

Workflows

Workflows

Visually designed flow-based actions that combine server-side logic with operator interactions.

Machine Learning

Machine Learning

An instrument allowing data scientists to drill into time series streams and huge datasets to mine valuable knowledge.

Bindings

Bindings

The way to tie module’s internal elements to each other and formalized elements of the unified data model.

Unified Search

Unified Search

Unified search windows that guarantee instant access to any piece of data within AggreGate server in mere seconds.