Pune, Jan. 13, 2025 (GLOBE NEWSWIRE) -- Edge Analytics Market Size Analysis:
“The Edge Analytics Market was valued at USD 10.91 Billion in 2023 and is projected to reach USD 81.57 Billion by 2032, growing at a compound annual growth rate (CAGR) of 25.10% from 2024 to 2032.”
Significant Growth in Edge Analytics Market Driven by IoT Expansion and AI Integration for Real-Time Data Processing
The Edge Analytics market is booming as the rate of Internet of Things devices increases and the necessity of real-time data processing. The number of connected IoT devices will hit 18.8 billion by the end of 2024, companies are now looking for a solution to process data locally, avoiding huge data transmission across networks to the central cloud system. In addition, 68% of IoT projects today already use AI at the edge, thereby bolstering real-time analytics, and improvements in 5G connectivity improve data transfer rates and boost market demand.
The increasing amount of data in domains such as manufacturing, health, and automobile demands efficient data processing at scale to be made timely. Edges and clouds coming together in unison present firms with flexibility as well as efficiency, combined with the guarantee of security to their data. At the same time, advancement in AI as well as ML at the edges allows for real predictive decision making in operations for greater innovation within businesses.
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Major Players Analysis Listed in this Report are:
- Amazon Web Service Inc. (AWS IoT, AWS Lambda)
- Cisco Systems Inc. (Cisco Edge Intelligence, Cisco Kinetic for Cities)
- Databricks (Databricks Unified Data Analytics Platform, Delta Lake)
- Dell Statistica (Statistica Analytics Platform, Statistica Data Miner)
- EdgeConneX (Edge Data Centers, Edge Cloud Solutions)
- Hewlett Packard Enterprise Development LP (HPE GreenLake, HPE Edgeline)
- IBM Corporation (IBM Edge Application Manager, IBM Watson IoT)
- Intel Corporation (Intel IoT Gateway, Intel NUC for Edge Analytics)
- Microsoft (Azure IoT Edge, Microsoft Power BI)
- Oracle Corporation (Oracle IoT Cloud, Oracle Autonomous Database)
- PTC (ThingWorx IoT Platform, Vuforia Augmented Reality)
- SAP HANA (SAP HANA Cloud, SAP Edge Services)
- SAS Institute Inc. (SAS Visual Analytics, SAS Viya)
- Apigee Corporation (Apigee API Platform, Apigee Edge)
- Predixion Software (Predixion Insight, Predixion Edge Analytics)
- AGT International Inc. (AGT Smart City Solutions, AGT IoT Platform)
- Foghorn Systems (Foghorn Edge AI, Foghorn Lightning)
- CGI Group Inc. (CGI Advantage, CGI IoT Platform)
- Greenwave Systems (Greenwave IoT Platform, Greenwave Edge Services)
- Equinix, Inc. (Equinix Metal, Equinix SmartKey)
- IGUAZIO (Iguazio Data Science Platform, Iguazio Enterprise AI)
Edge Analytics Market Report Scope:
| Report Attributes | Details |
| Market Size in 2023 | USD 10.91 Billion |
| Market Size by 2032 | USD 81.57 Billion |
| CAGR | CAGR of 25.10% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Key Regional Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America) |
| Key Growth Drivers | • Advancements in Edge Computing and AI Drive Growth in Edge Analytics Market • Rising Demand for Low Latency Drives Adoption of Edge Analytics in Critical Industries |
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Solution Segment Leads and Service Segment Shows Fastest Growth in Edge Analytics Market
In 2023, the Solution segment dominated the edge analytics market, accounting for around 71% of total share. This dominance is due to the increasing demand for platforms that can process data in real-time and make decisions at the edge. Key industries such as manufacturing, healthcare, and transportation are increasingly adopting edge solutions to improve operational efficiency, reduce latency, and enhance data security, with the ability to process large datasets locally, offering scalability and high performance.
The Service is expected to grow at the fastest CAGR of 26.71% from 2024 to 2032. This growth comes from the ever-increasing requirement for customized support and maintenance services so that edge analytics solutions are well deployed and optimized continuously. While businesses expand their edge infrastructure, customized consulting, integration, and managed services are very much required to have a grip over complex edge analytics environments.
Descriptive Analytics Leads While Prescriptive Analytics Shows Fastest Growth in Edge Analytics Market
In 2023, the Descriptive Analytics segment led the edge analytics market, capturing the largest revenue share of around 38%. This segment's strength lies in its ability to provide key insights into past performance, helping businesses analyze historical data to understand trends and improve decision-making. By processing data at the edge, companies can gain real-time insights into customer behavior, operational efficiency, and market trends.
The Prescriptive Analytics segment, however, is expected to grow at the fastest rate of approximately 27.88% from 2024 to 2032. Driven by the demand for actionable insights, prescriptive analytics is increasingly important as it helps businesses recommend optimal actions based on real-time data. This segment is gaining traction in industries looking to enhance decision-making and optimize operations.
Edge Analytics Market Segmentation:
By Type
- Descriptive Analytics
- Diagnostic Analytics
- Predictive Analytics
- Prescriptive Analytics
By Component
- Solution
- Service
By Deployment
- On-Premises
- Cloud
By Application
- Marketing & Sales
- Operations
- Finance
- Human Resources
- Others
By End-use Industry
- IT & Telecom
- BFSI
- Manufacturing
- Healthcare and Life Science
- Retail
- Transportation and Logistics
- Government
- Energy and Utilities
- Others
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North America Leads Edge Analytics Market While Asia Pacific Exhibits Fastest Growth Potential
In 2023, North America held the largest share of the edge analytics market with approximately 36%, driven by its advanced technological infrastructure, widespread IoT adoption, and strong investments in edge computing and AI. Industries such as healthcare, automotive, and manufacturing have leveraged these solutions to enhance efficiency, reduce latency, and enable real-time decision-making, supported by a skilled workforce and favorable regulations.
The Asia Pacific region is expected to experience the fastest growth, with a CAGR of 27.20% from 2024 to 2032. This surge is fueled by rapid industrialization, IoT device growth, and increasing investments in digital transformation, particularly in China, India, and Japan. The demand for real-time analytics in sectors like manufacturing and smart cities is driving the need for edge analytics solutions in the region.
Recent Developments in the Edge Analytics Market
- In September 2024, Belden integrated its CloudRail software with AWS IoT SiteWise Edge to improve industrial data processing, enabling efficient edge-to-cloud workflows for asset monitoring and predictive maintenance.
- • In January 2024, American Tower and IBM partnered to deliver edge cloud services, combining 5G, AI, and edge computing to boost enterprise innovation and real-time data insights.
Table of Contents – Major Key Points
1. Introduction
2. Executive Summary
3. Research Methodology
4. Market Dynamics Impact Analysis
5. Statistical Insights and Trends Reporting
6. Competitive Landscape
7. Edge Analytics Market Segmentation, By Component
8. Edge Analytics Market Segmentation, By Application
9. Edge Analytics Market Segmentation, By End-use Industry
10. Edge Analytics Market Segmentation, By Type
11. Edge Analytics Market Segmentation, By Deployment
12. Regional Analysis
13. Company Profiles
14. Use Cases and Best Practices
15. Conclusion
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