Edge Analytics and its growing popularity

What is Edge Analytics?

Edge analytics is a method of collecting, processing, and analysing data at the network's edge, such as at or near a sensor, a network switch, or another connected device. In several industries, such as retail, manufacturing, transportation, and energy, the growing popularity of connected devices, combined with the expansion of the Internet of Things (IoT), has sparked the collection of massive amounts of data at the network's edge. There are two types of analytics: descriptive and predictive. Edge analytics is real-time data analysis that takes place in-situ or on-site where data collection is taking place

Types of Edge Analytics

Descriptive analytics

• Predictive analytics

• Prescriptive analytics

• Diagnostic analytics

The growth of the edge analytics market is being driven by the prevalence of large amounts of data with the help of connected devices, real-time intelligence acting as a catalyst for the growth of edge analytics on network devices, and adopting edge analytics increasing scalability and cost optimization.

Adoption of Connected Devices is Growing at a Rapid Rate IoT device adoption is growing at a rapid pace, creating massive amounts of data and necessitating real-time data analysis.

Increased Preference for Cloud Deployment Model

Market growth is fueled by secure data networks, increased application development, and platform-based cloud services.

Lack of IT Infrastructure in Developing Countries

Latin America, the Middle East, and Africa have yet to become technologically competent hubs with robust IT infrastructure and digital content, which is projected to stifle global market growth in the foreseeable future.

Demand for Prescriptive Analytics is on the Rise

Prescriptive analytics solutions have grown in popularity in recent years as demand for greater prescriptive modelling on historical and predictive analytics outcomes has increased.

Edge Analytics is becoming more popular among businesses.

Edge analytics is becoming more popular among businesses, because to benefits like increased uptime, reliability, alarm monitoring, and active notifications.

For a deeper dive, buy a complete report:

Edge Analytics: 32.8% CAGR

Projected Revenue: 9.62 billion from 2020 to 2027

Full Report:  https://www.whipsmartmi.com/Report/Edge-Analytics-Market

Conclusion:  Big data analytics is carried out via centralised methods such as big data centres, central repositories, or Hadoop clusters. Edge analytics works on the idea that analysts acquire data directly from active devices, avoiding the need to transport the complete data to a central warehouse and therefore saving time and money. Analytic algorithms installed at the network's edge determine which data should be sent to the cloud or a central data storage repository for later use.

Published Date : July-2021

© 2021 Whipsmart. All Rights Reserved.