Edge Analytics

What is Edge Analytics?

Edge analytics is the process of analyzing data and finding solutions at the edge, where data is collected via smart devices and IoT sensors.

How does edge analytics provide a competitive advantage?

Edge analytics provides a competitive advantage for an organization’s budget and workflow.

While creating the infrastructure to perform data analytics at the edge represents a significant cost up front, the burden of spend reduces over time. With billions of connected devices gathering data, and potentially hundreds or thousands of those in a single organization, storage for that data could be a huge capital cost, even as the cost of data storage is falling. Additionally, the greater the data load and the greater the need to analyze it at speed, the greater the cost of transfer bandwidth and computing architecture to keep the flow of information working for an organization and not against it.

Edge analytics also benefits an organization’s workflow because it facilitates real-time decision-making. Not every company requires mission-critical analysis in real-time, but as artificial intelligence (AI) and machine learning (ML) technologies evolve and become more applicable to the everyday consumer, organizations will be able to utilize collected data from the edge to modify and improve the customer experience for greater personalization and a customized, streamlined buyer journey.

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How does edge analytics help with fleet management?

Edge analytics can help with fleet management, as Internet of Things (IoT) sensors in the fleet help with safety, security, and resource allocation.

For example, automated vehicles and self-driving cars use real-time data from environmental sensors to avoid collisions, manage acceleration and deceleration, and trigger automated responses if the vehicle experiences a malfunction. That time-sensitive data is not the kind anyone would want transferred over a network to a central compute hub for analysis and then returned to the vehicle with instructions on how to respond. When safety is a concern, that analysis needs to be done on-site and immediately.

Edge analytics can also assist in upkeep and scheduled maintenance for a fleet. Before the collection of data by IoT sensors, fleet maintenance schedules would normally be coordinated at the central hub of the organization, and normally done via historical data. After 3,000 miles, a car would normally require an oil change, according to conventional wisdom. Modern IoT networks allow an organization to use real-time onboard sensors to gather data about performance, road and weather conditions, and driver behaviors to create an on-site real-time picture of how the automobile is functioning.

Can edge analytics be used for manufacturing?

Edge analytics represents a kind of modern-day industrial revolution. Just as the assembly line reduced the labor hours required to manufacture a product, edge analytics may also facilitate a leap forward in productivity as a quality control agent that requires no breaks, no time off, and no rest. Edge analytics has the potential to increase peak efficiency.

As sensors within a factory collect data, edge analytics allows that data to be organized, analyzed, and converted into actionable improvements to the manufacturing process. For instance, in a factory that produces printed circuit boards for an electronics product, sensors would not only be able to monitor the automated process of populating the circuit boards with the soldered components, but could also collect data on color codes of electrical parts, height and width data, tested solder joints, and number of components populating a circuit board. If the data returns an incorrectly placed component, a cold solder joint, or a component not seated properly in the socket or on the printed circuit board, then it could stop assembly or remove the substandard product from the production workflow.

Add to that the ability to gather data on temperature in the factory and lighting conditions that may affect the sensors’ ability to see color-coded components, for instance, and the on-site analysis of collected data can recommend real-time improvements in manufacturing time, cost, and quality control.

Sending that data off-site would not only be time-consuming and expensive, but it may also expose the data to security risks. If the manufactured product represents corporate trade secrets, intellectual property, or matters of security, then sending manufacturing data over a network opens it up to malware or theft. 

What can edge analytics do for my business?

Edge analytics makes real-time data analysis via AI and ML attainable and pragmatic. 

Your business can benefit from an ever-evolving picture of your operations, on-site, in manufacturing, B2B, or B2C environments. Edge analytics enables smoother, safer utilization of data rather than sharing time-sensitive, confidential, or proprietary information over a vulnerable network.

Additionally, the cost of cloud data storage, transfer bandwidth, and remote computing power can easily be thousands of dollars per day. Committing to an edge analytics framework—while initially expensive—can account for far less overhead and operating costs.

HPE and edge analytics

Intelligent edge refers to the analysis of data and development of solutions at the point where the data is generated. In this way, intelligent edge reduces latency, costs, and security risks, making the associated business more efficient. The three major categories of intelligent edge are operational technology edge, IoT edge, and information technology edge, with IoT edge currently being the biggest and most popular.

HPE Intelligent Edge gateways enable organizations to rapidly acquire, analyze, and take action on real-time data as it’s being collected for additional analysis at a later stage. Bringing computing and analytics close to the edge accelerates the speed of your decision-making and reduces the chance of lost opportunities or a missed red flag.

When you can control and harness data across edge to cloud, so much becomes possible, allowing you to innovate successfully at the edge. That is where data becomes insights, in real time. That is a connected edge, wisely done. Unify your data at the edge by securely and seamlessly integrating all your apps and infrastructure. Securely access your data wherever it lives, eliminating migration headaches. Go from edge to cloud with the flexibility to scale when you need.

Powered by software-defined infrastructure, HPE Hyperconverged Solutions simplify your IT environment and drive agility with a cloud-like experience—all via HPE GreenLake. Our cloud service offerings pair the flexibility of cloud with on-premises control, and they're optimized to provide you a choice in selecting the right solution for your workloads. From general-purpose and business-critical applications, across virtualized and containerized apps, and for both small- and large-scale environments, you have the freedom to determine the right architecture for your apps.