Edge Analytics Market Size, Share & Trends Analysis Report By Type (Descriptive Analytics, Diagnostics Analytics), By Component, By Deployment Model, By Application, By End Use Industry, By Region, And Segment Forecasts, 2023 - 2030

Report Overview

The global edge analytics market size was valued at USD 7.27 billion in 2022 and is expected to grow at a compound annual growth rate (CAGR) of around 25.3% from 2023 to 2030. The proliferation of internet of things devices such as sensors and connected devices has led to a massive influx of data being generated at the edge. The growing usage of IoT-connected devices is expected to drive market growth during the estimated period. This solution process and analyze the data closer to its source, allowing organizations to extract valuable insights and make faster decisions. Increased government activities in information and communication technology are expected to boost demand for edge analytics. Government worldwide are investing in smart city projects to improve urban infrastructure, enhance sustainability, and provide better services to citizens. The application that are enabled by this service such as real-time data processing and analysis from various sources, such as sensors, cameras, and IoT devices. Edge analytics and edge computing have reached a tipping point for government agencies as a result of the increased capacity and ubiquity of IoT devices as well as the launch of 5G networks, making it practical in an expanding number of new scenarios. 5G networks offer fast connections resulting in reduced latency for real-time decision-support and action.

Growth in internet and cloud usage offers significant opportunities for the global edge analytics industry in the future years. For instance, Federal technology leaders shared the perspective, predicting that edge solution will have the most impact on artificial intelligence & machine learning (78%), big data/analytics (58%), Cloud (50%), extended/mixed reality (32%), and distributed databases (30%).The shortage of experienced labor to install and run edge-based solutions restricts industry expansion. Increased network node efficiency is predicted to provide lucrative prospects for the advancement of the edge analytics market size throughout the forecast period.

Several production facilities are integrating and employing advanced edge analytics solutions in addition with IoT to monitor the production systems. Real-time data processing and automated resolution are features of the analytics algorithm. The beneficial information helps organizations select what steps to do next and also aids in business expansion.

Data privacy and security concerns are becoming increasingly important for businesses and consumers alike, and edge analytics helps address these concerns by keeping the need to transmit it across network. Organizations can process and analyze data locally, mitigating risks associated with data breaches and ensuring compliance with data protection regulations. The advancement of edge computing infrastructure, including edge servers, gateways, and edge devices is the significant driver for the growth of the market. The availability of powerful computing resources at the edge enables sophisticated analytics capabilities, including machine learning and artificial intelligence, to be deployed closer to the data source.

This infrastructure development facilitates the implementation of edge analytics solutions across various industries and use cases. For instance, in manufacturing, edge analytics can enable predictive maintenance by analyzing sensor data in real time, optimizing equipment performance, and reducing downtime. In retail, it can provide personalized customer experience by analyzing in-store shopper behavior and delivering targeted recommendations. The healthcare industry can benefit from edge analytics by enabling remote patient monitoring, real-time health data analysis, and timely intervention.

The COVID-19 pandemic highlighted the importance of real-time data analysis and decision-making. Organization across sectors, including healthcare, manufacturing, logistics, and retail, realized the value of processing and analyzing data at the edge to respond quickly to rapidly changing situations. Edge solution became instrumental in monitoring and managing the spread of the virus, optimizing healthcare resources, ensuring supply chain resilience, and implementing safety measures. The pandemic accelerated the adoption of telehealth and remote patient monitoring solution. It played a crucial role in the application by enabling real-time data analysis of patient vitals, symptoms and remote diagnostics. Healthcare providers leveraged analytics to monitor patients remotely, detect anomalies and provide timely interventions. These solutions reduced the need for in-person visits, minimized the risk of exposure and improved healthcare accessibility, particularly in areas with limited medical infrastructure.

Component Insights

The solutions components segment accounted for the largest market share of over 70.0% in 2022. Edge analytics solutions prioritizes acceleration and decentralization, discarding conventional approaches of gathering enormous volumes of data. Organizations across the globe have focused on increasing the efficiency and lowering the maintenance costs of analytics solutions through the effective integration of data received from connected devices and networking equipment for increased real-time event analysis. There has been increased demand for edge computing infrastructure, this includes edge servers, gateways, and edge devices equipped with processing power and storage capabilities.

These components enable data processing and analysis at the edge, supporting real-time insights and decision-making. It leverage artificial intelligence and machine learning techniques to extract valuable insights from data at the edge. The growth in the market has driven the development of edge AI and ML frameworks, libraries and algorithms. These components enable the deployment of AI and ML models directly on edge devices, facilitating real-time analytics and interference. The edge computing reduces network charges, storage costs, and traffic management system operational costs.

Type Insights

Based on type, the descriptive analytics segment dominated the market in 2022 with market share of more than 38%, whereas the prescriptive analytics segment is likely to expand at a fastest CAGR of 27.3% over the forecast period. The prescriptive analytics models are made to combine operations and data to provide a roadmap that specifies what to do and how to accomplish it correctly the first time. Prescriptive analytics are used by SideTrade to enhance the company's comprehension of clients' actual payment behavior. They are able to rank clients according to their history of on-time payments because of prescriptive analytics.

Prescriptive analytics is a more advanced analytical solution that lowers the network's analytical complexity while enhancing analytics solutions by foreseeing tasks that must be finished in advance. Prescriptive analytics uses data analytics to analyze data gathered from both historical and projected analysis and generates corrective actions to be taken for better business decisions. Several sectors, including healthcare, retail, and others, have implemented edge analytics solutions for prescriptive analytics models to enhance their company operations via cost-effective and result-oriented analytics models.

Prescriptive analytics at the edge can help address compliance and data privacy concerns by analyzing data locally; sensitive information can remain within the organization's control, reducing the need to transmit it to the cloud. This can enhance data privacy, comply with protection regulations, and build customer trust. In certain scenarios, connectivity to the cloud or centralized systems may only sometimes be available or reliable. Prescriptive analytics enables decision-making even in offline or intermittent connectivity situations by leveraging local data and processing capabilities; organizations can still receive actionable insights and make informed decisions at the edge.

Application Insights

The marketing and sales segment accounted for more than 34.0% share of the revenue share in 2022. Financial organizations, particularly conventional retail financial businesses, can use edge analytics to improve customer service, cut expenses, and assure regulatory compliance. Financial Services is a highly digitally mature business, pushed by FinTech startup's edge analytics and computing, a new type of distributed cloud, giving new and established companies various chances to boost profitability. It can help businesses monitor and analyze customer interactions and feedback in real-time; by capturing and analyzing data at the edge, businesses can identify areas for improvement, address customer pain points promptly and enhance the overall customer experience.

This feedback loop can be invaluable for marketing and sales teams to refine their strategies and increase customer satisfaction. It empowers sales teams with real-time data and insights; businesses can provide sales representatives with up-to-date information, personalized recommendations, and sales guidance by analyzing customer data, market trends, and sales performance at the edge, consequently enabling sales teams to be more effective, close deals faster, and provide better customer services.

Deployment Model Insights

In 2022, the on-cloud deployment segment held a larger revenue share of more than 50.0%. Cloud deployment is the process of deploying an application using one or more cloud-based hosting models such as software as a service, platform as a service, and infrastructure as a service. This encompasses cloud workload architecting, planning, implementation, and operation. Cloud deployment offers several benefits including quicker and easier deployment, cost savings, platform extension, increased company resilience, and others. Cloud platforms offer scalable and elastic resources, allowing organizations to handle large volumes of data generated at the edge.

Edge devices often have limited processing and storage capabilities, making it challenging to handle data-intensive analytics tasks, by leveraging the cloud, organizations can scale their computational resources as needed, ensuring efficient processing and analysis of edge data. Cloud deployment enables centralized data storage, making it easier to aggregate and access data from multiple edge devices. Edge devices typically have limited storage capacity, and sending all the data to the cloud can reduce the local storage burden. Storing data in the cloud also allows for historical analysis and long-term data retention enabling organizations to derive valuable insights over time.

End-use Insights

The energy and utility segment accounted for CAGR of more than 25.0% over the forecast period. An increase in the number of households and energy users and a rise in demand for smart grid systems is boosting the growth of the segment. Edge analytics also assists energy producers in determining how much energy can be delivered to or preserved for future use. Current systems should be constructed with cutting-edge analytics to ensure greater yields when climatic conditions change, which means utilities can absorb more sustainable energy into the grid and reduce carbon dioxide emissions while also improving clean energy.

The manufacturing sector is expected to increase significantly throughout the forecast period. Manufacturing firms are employing edge analytics to keep better track of machine performance, production output, and to be able to deal with any problem that arises in seconds rather than minutes.

Regional Insights

North America dominated the market in 2022, accounting for more than 34.0% revenue share in 2022, due to the increasing usage of edge analytics by SMEs, which is supported by government rules and regulations. Furthermore, the fast increasing edge analytics business can be the driving force behind the widespread use of edge analytics solutions in the industrial and telecommunications sectors. While both life insurance and property and liability insurance have employed cloud computing to promote agility, increase operational efficiency, attract fresh talent, and cut operating costs, insurers are increasingly viewing the cloud as a business asset.

Multinational manufacturers have actively invested in the sector to strengthen edge analytics service offerings, assure on-time and inexpensive analysis, real-time event management, and queuing up data to the appropriate quality, with the Asia Pacific region predicted to expand the quickest during the projection period. As the regional government tries to boost the market for IoT and cloud technologies, edge analytics will be employed more frequently. The country's new administration is behind the Digital India initiative, which aims to turn India into a knowledge-based society and economy.

Key Companies & Market Share Insights

Key players in the edge analytics market are offering and expanding their product portfolios by investing in product research and development and delivering competitive pricing, which embroiders market rivalry.

Gaining to the momentum of the highly growing market manufacturers/companies are expanding their reach by collaborating with local players to gain their monopoly towards customer. For instance, The Catalyst 8000 Edge series, a cornerstone of Cisco's intent-based networking portfolio, offers clients an innovative and high-performance routing architecture. The new platform, which includes built-in analytics, provides improved visibility into network or application problems and enables educated decisions to maximize user experiences. In February 2023, Amazon Web Service Inc. announced the new product availability AWS Telco Network Builder, which is fully managed service which helps the consumers to deploy, run and scale the Telco network on AWS platforms.Some of the prominent players in the global edge analytics market include:

• Amazon Web Service Inc.

• Cisco Systems Inc.

• Databricks

• Dell Statistica

• EdgeConneX

• Hewlett Packard Enterprise Development LP

• IBM Corporation

• Intel Corporation

• Microsoft

• Oracle Corporation

• PTC

• SAP HANA

Recent Development

• In September 2022, IBM and Bharti Airtel from India collaborated to launch Airtel's edge computing platform in India. This platform provided open and secured cloud services by reducing latency while addressing sovereignty and data security requirements

Edge Analytics Market Report Scope 

Global Edge Analytics Market Report Segmentation

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2018 to 2030. For this study, Grand View Research has segmented the global edge analytics market report based on type, component, deployment model, application, end-use industry, and region:

• Type Outlook (Revenue, USD Million, 2018 - 2030)

  • Descriptive Analytics

  • Diagnostic Analytics

  • Predictive Analytics

  • Prescriptive Analytics

• Component Outlook (Revenue, USD Million, 2018 - 2030)

  • Solution

  • Service

• Deployment Model Outlook (Revenue, USD Million, 2018 - 2030)

  • On-Premises

  • On-Cloud

• Application Outlook (Revenue, USD Million, 2018 - 2030)

  • Marketing & Sales

  • Operations

  • Finance

  • Human Resources

  • Others (Remote Management, Smart Grid, Hospitality, etc.)

• End-use Industry Outlook (Revenue, USD Million, 2018 - 2030)

  • IT & Telecom

  • BFSI

  • Manufacturing

  • Healthcare and Life Science

  • Retail

  • Transportation and Logistics

  • Government

  • Energy and Utilities

  • Others

• Regional Outlook (Revenue, USD Million, 2018 - 2030)

  • North America

    • U.S.

    • Canada

  • Europe

    • UK

    • Germany

    • France

    • Italy

  • Asia Pacific

    • China

    • India

    • Japan

    • South Korea

  • Latin America

    • Brazil

    • Mexico

  • Middle East and Africa

    • UAE

    • Saudi Arabia

    • South Africa