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.
This strategy seeks to decrease latency and bandwidth utilization by executing analytics locally, close to the data source, rather than sending the data to centralized servers or data centers for analysis.
- How does edge analytics provide a competitive advantage?
- How does edge analytics help with fleet management?
- Can edge analytics be used for manufacturing?
- What can edge analytics do for my business?
- HPE and edge analytics
How does edge analytics provide a competitive advantage?
Edge analytics gives companies a competitive edge by enabling them to process and analyze data locally rather than in data centers. Some important advantages are as follows:
- Real-time insights: Edge analytics allows for real-time data processing and decision-making. For instance, in the industrial sector, it can be used for predictive maintenance of machinery, in the IoT sector for real-time monitoring of smart devices, and in the retail sector for personalized customer experiences. These industries need quick insights to increase operational efficiency and reaction times.
- Reduced latency: Processing data at the network edge reduces latency by eliminating data transfer to centralized servers for analysis. Autonomous vehicles and critical infrastructure monitoring require quick data-driven responses; this is crucial.
- Optimizing bandwidth: Edge analytics decreases data sent to centralized data centers. This improvement can save bandwidth and storage costs.
- Data security and privacy: Edge processing reduces sensitive data exposure during transmission. Localizing data and reducing data breaches helps comply with data privacy laws.
- Flexible and scalable: Edge analytics supports distributed computing architectures, making horizontal scaling easy by adding edge devices. This flexibility allows corporate development and agility without overwhelming centralized infrastructure.
- Operations efficiency: Edge analytics automates operations, optimizes resource allocation, and enables predictive maintenance based on local data insights.
Edge analytics enables organizations to use real-time data to make quicker decisions, increase operational efficiencies, and provide better customer experiences, resulting in a competitive advantage in their respective sectors.
How does edge analytics help with fleet management?
Edge analytics can enhance fleet management with real-time data processing and actionable insights. Here's how it helps:
- Real-time vehicle monitoring: Vehicle edge devices can monitor vehicle performance, driver behavior, and ambient factors in real-time. This allows fleet managers to rapidly check vehicle health and condition.
- Predictive maintenance: Edge analytics can forecast when a vehicle will require maintenance by evaluating engine performance, fuel consumption, and wear and tear data. This expedites repairs, reduces downtime, and prevents costly breakdowns.
- Optimization: Edge analytics can optimize routing and dispatching using traffic, weather, and vehicle positions. This optimizes vehicle routes, lowering fuel usage and delivery times.
- Driver behavior analysis: Edge analytics can identify risky driving habits by evaluating data on driving patterns such as speed, braking, and acceleration. Fleet managers can increase safety and fuel economy with focused training or remedial measures.
- Fuel management: Real-time fuel use and monitoring of driving habits can reveal inefficiencies and opportunities for improvement. This improves fuel management and saves money.
- Compliance and reporting: Edge analytics monitors and analyzes hours of service, vehicle inspections, and emissions data to assure compliance. Data can also be used to provide accurate and timely reports.
- Customer service: Fleet managers can give precise delivery timings and updates with real-time vehicle tracking. Customer happiness and trust increase.
- Incident response: Edge analytics can notify and document car or accident incidents, speeding up response and improving incident management.
Fleet managers can enhance productivity, safety, and cost-effectiveness using edge analytics, giving them a competitive edge.
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.