Skip to main content Skip to footer

Big Data Glossary

What is Edge Analytics?

Definition of Edge Analytics

Crosser Page Break Icon

What is Edge Analytics?

Edge analytics is a method of performing data analysis and processing at the source of the data, rather than in a centralized location such as a data center or cloud. In this way, edge analytics allows for real-time analysis of data as it is generated, without the need to transmit large amounts of data over a network to a centralized location for processing.

Edge analytics is particularly useful for IoT (Internet of Things) applications, where devices such as sensors and cameras generate large amounts of data that needs to be analyzed in real-time. Edge analytics enables these devices to process the data locally, and only transmit the necessary insights or summarized data to the cloud or data center. This can help to reduce the amount of data that needs to be transmitted over the network and improve the response time of the system.

Edge analytics can also be used in other industries such as manufacturing, healthcare, and retail. It allows organizations to gain real-time insights into their operations, customer behavior, and market trends at the edge of the network, which can be used to improve decision-making, optimize processes, and increase efficiency.

Introducing Crosser

The All-in-One Platform for Modern Integration

Crosser is a hybrid-first platform that in one Low-code platform has all the capabilities that you traditionally would need several systems for.

In one easy-to-use platform:

Platform Overview

Crosser Solution for Data Mining

Explore the key features of the platform here →

Want to learn more about how Crosser could help you and your team to:

  • Build and deploy data pipelines faster
  • Save cloud cost
  • Reduce use of critical resources
  • Simplify your data stack