Value appreciation through IoT
Aggregation at the edge, action at the hub
The Internet of Things
The internet permeates all areas of life. In addition to phone and web activities, modern consumer devices, home sensors, vehicle engines, medical devices, and billions of other devices provide data over the internet.
The rapid aggregation and accurate analysis of this data is crucial to making people healthy, systems secure, commerce profitable, and machines efficient. The same is true for the increasing volumes of data generated by machine and application logs, which may or may not flow over the internet in real-time.
To generate usable information from all of this data, you need secure, efficient, and reliable methods for processing and applying that data so that it works for you and not against you. But look at the landscape of tools and techniques that are applied to these problems today. Think about the speed of data volume, reliance on big hardware, complexity of design, security gaps, and cost.
Edge-Aggregation
Edge computing involves collecting and examining data as it's generated, as close to the source as possible. In edge analytics, data is preprocessed and preliminarily analyzed on IoT devices instead of being sent directly and unaltered to a central data store for later use.
„Edge aggregation and/or analytics can reduce latency within the decision-making process. Using data closer to the source can be faster, easier, and more practical than traditional methods, and much of the data generated by IoT devices isn't worth storing at all.“ (Shawn Rodgers, Quest Software).
Storing unnecessary data is costly, complex, and poses a security risk. Processing data directly means less data needs to be collected, stored, or reprocessed in bulk later. Because edge analytics can happen in real-time, some insights can be gained immediately.
The light, fast SortCLProgram in IRI CoSort is the perfect tool for filtering, masking, aggregating, segmenting, reporting, and otherwise Transforming Data on Edge devices. CoSort-generated datasets are lean, clean, and compliant, and can be easily distributed to various platforms for further use or processing, such as the IRI Voracity Data Management (Hub) Platform supporting CoSort, Hadoop, and other analytical options.
Analyze in the Hub
The IRI Workbench GUI for Voracity, built on Eclipse™, supports data processing and visualization in the same console. After setting up connections to your data stores and aggregation jobs, wherever they may be, you can further process the data with Voracity's built-in statistics and reporting features at unprecedented speed and analyze or „wrangle“ (integrate, normalize, and hand off) them for your preferred analysis and visualization tools.
IRI Voracity can aggregate device information streamed via MQTT and immediately display in the free BIRT plugin within the same Eclipse console. Voracity can also Forward processed data to open source KNIME Analytics Platform nodes in Eclipse, in real-time or in batch, for machine learning and other data science projects that improve predictive models and outcomes.
„Voracity enables a single process for the ingestion, basic analysis, and integration of IoT data into both the model development and execution environment, defined and managed from a single platform.“
Dr. Barry Devlin, 9sight Consulting
Learn more about IRI's IoT capabilities in our articles „Introduction to IoT & MQTT“ and „Aggregation on the Edge“.