• October 7, 2015

Life on the Edge: The High Octane Fuel of High-Quality Data

Social, financial, customer, product, and supply chain. Enterprises are collecting enormous amounts of data across the market spectrum. But in many cases they’re not doing anything with it, because it’s largely indigestible. The quality is poor: It’s unstructured, noisy, aged, and growing increasingly error-prone with each passing day.

Take marketing. Effective B2B campaigns are all but impossible without robust contact databases that are accurate and have the capability to be segmented. High-performance enterprises have developed systems to apply analytics to large pools of data. Data can be captured, aggregated, and analyzed to mine hidden patterns and generate insights, triggering actionable business intelligence in real time. These processes require data refinement.

To avert Big Data paralysis, enterprises need to push intelligence out to the edge, creating cleaner, highly actionable data that can fuel business value.

Driving on the Edge

Innovations in sensor and processing technologies are driving cost savings, failure rate reductions, and value. Devices equipped with edge technologies are smarter, as data is processed in real time at the point of collection. It’s then transferred to servers or other computing devices for further processing and analytics. With intelligence at the edge, decision-makers have access to actionable information more rapidly, eliminating the time and effort required when wrestling raw data.

For example, the European Union recently launched the Flite-Wise project (Flite Instrumentation Test Wireless Sensor) to test wireless sensors on airliners. Equipped with ultra-thin batteries that can be charged wirelessly by inductive coupling, these sensors eliminate the cost, weight, complexity, and limitations of wired systems.

Wireless sensors can be placed virtually anywhere on the aircraft including on the skin, in gearboxes, and on moving engine parts. With acoustic and temperature sensor systems, the airline industry will have the capacity to detect fluctuations and anomalies predicting wear and structural fatigue.

Aligning With the Edge

Before embarking on an edge intelligence strategy, determine what problems you are trying to solve and what data can be used to formulate solutions.

  • Where and how much data should be collected?
  • How should it be processed?
  • Who will use the data?
  • How manageable are the edge end points?
  • Will data move seamlessly and securely through aggregating and analytics systems?
  • Can data be viewed and interacted with across a wide range of platforms including mobile phones, tablets, and machine dashboards?

Intelligent edge computing can be deployed across a wide variety of systems and industries. It can be embedded in power grids to make real-time decisions about how and where to distribute power. It can be deployed in manufacturing where sensors can help create smart production lines and equipment maintenance schedules to reduce costs and downtime.

With intelligence on the edge, enterprises can rapidly generate quality data, reducing the burdensome complexity of mining Big Data for value and insights.