Demand for real-time data and analytics has never been higher – and for good reason. Businesses want to be able to tap into their data and generate insights that can lead to a competitive edge in their respective industry. To meet those objectives, organizations are increasingly turning to the cloud, on-premise data centers, and the edge – or are taking a hybrid approach – to house and analyze their data. 

While both cloud and edge computing are incredibly popular and powerful ways to manage data, if an organization is looking to achieve real-time data access and analysis while also improving security, edge computing holds a strong advantage. Both cloud and on-premise systems have advantages, but when it comes to real-time analysis, edge computing wins out. With edge computing, businesses gain the ability to perform automated decision-making extremely close to where the data is generated, giving businesses real-time value around the most critical data. 

Decreased Latency 

So, what makes edge computing so well-suited for analyzing data? One of the main benefits boils down to time – particularly the time spent doing the analysis. Regardless of what industry in which a business operates, success can often depend on the ability to tap into real-time analytics – or how well they reduce latency. Because edge computing does that analysis right where data is generated, there’s no time lost as the data is moved from one environment to another and then to the end-user who needs it to make decisions. 

With edge analytics, businesses can better mitigate the challenges of growing amounts of data by distributing the computational workload of analysis across each device, instead of routing everything into one data center or cloud environment. Even as the number of connected devices grows across an organization, edge analytics performed on sensors and network devices are able to cut down on the processing strain associated with enterprise data management. 

Unlocking real-time analytics at the edge gives organizations greater flexibility that is often required to kickstart a meaningful digital transformation. Overcoming the hurdles associated with scalability and latency can easily become the difference maker and affect large-scale transformation across any enterprise. 

Increased Scalability and Security

The benefits of edge computing don’t stop at reducing latency. Oftentimes, organizations struggle with localizing solutions at scale. Leaders have to take all kinds of considerations into account from the unique aspects of a local environment to varying languages and operations at each site. Edge computing brings critical customizability and scalability to an organization’s analytics strategy. The benefit of Edge Computing is that every device can analyze its own data. That’s a factor that becomes critical as both organizations and the volume of data they generate grows. 

As the amount of data being generated rises, security has become a serious concern for businesses and IT leadership. As these organizations look for ways to achieve required analytical objectives without exposing data to undue risk, edge computing presents a viable solution to boosting security. With edge solutions, there’s no need to transmit data – and the data that is needed never has to leave the device that created it. With edge computing solutions, a business can dodge a costly rip and replace of its existing control infrastructure, while also expanding the reach of cyber security teams’ ability to keep operational environments up to date with the latest patches and updates.  

Actively Monitor and Enable Predictive Analytics

By leveraging edge computing solutions, organizations can run, monitor, and control APM applications that bridge machine and factory data going to the cloud – and in doing so, they can enable deeper analytics and improved performance. With real-time active monitoring and predictive analytics, it becomes easier to forecast expected maintenance and repairs and to know when to take action or schedule maintenance before any issues arise. This improves operational resilience by running collected data through an analytics algorithm, all at the edge of a corporate network. 

Companies can then set parameters to decide what data is worth sending to a cloud or on-premises data storage. Data analytics tools can be used to identify failure modes and subsequently monitor them in real time with edge computing to ensure the right response. Building in that functionality and moving from reactive to proactive will drastically reduce downtime, save time, and cut costs.

Reduce Costs

It’s no secret that big data analytics come at a cost – and a very expensive cost, no doubt. Whether the data is processed in a public cloud or in a data center, there are costs that come from data storage, processing, and transportation. Because edge solutions rely on device hardware to perform data analytics, there’s no need for back-end processing.

For businesses that depend on cloud operations, data egress fees add up quickly. Adopting a hybrid architecture can help control those costs by managing the data that needs to be moved to and from the cloud. Take for example, a cloud-only environment – in this setting a business would take equipment data, move it to the cloud, and identify that a failure mode has been activated. Then, the organization would transfer its data to a CMMS to schedule maintenance, back to SCADA to potentially migrate operations away from that asset, and to an alert for an operations scheduling team. 

With edge computing, an organization could identify that a failure mode has been triggered and then send a message directly to the key stakeholders and send the data to the cloud, instead of from the cloud. By enabling actions like these to be taken, businesses can avoid costly downtime or even data loss that could cause serious damage and set operations back. 

Edge Computing Holds the Key to Better Analytics

The demand for real-time analytics has never been higher, no matter the industry. Organizations are prioritizing solutions that help optimize manufacturing processes and ultimately business performance. Whether it’s enhanced security, better scalability, flexibility, or reduced latency, edge computing brings a range of benefits and far more effective analytics to transform an enterprise and generate greater business value.