Edge Analytics Market to Witness a Surge on Account of Exponential Growth in Real-Time Data from IoT Devices

The Edge Analytics Market is propelled by the surging demand for real-time data insights, fostering quicker decision-making and operational efficiency.

AUSTIN, TEXAS, UNITED STATES, January 31, 2024 /EINPresswire.com/ -- Based on SNS Insider’s research, the surge in IoT devices, the demand for low-latency analytics, the emphasis on real-time monitoring, and the advent of 5G technology collectively contribute to the expansion of Edge Analytics Market.

The SNS Insider report indicates that the edge analytics market, having reached a valuation of USD 7.23 billion in 2022, is projected to expand significantly, reaching USD 39.61 billion by 2030. This growth is anticipated to occur at a compound annual growth rate (CAGR) of 23.69% during the forecast period from 2023 to 2030.

Edge analytics refers to the process of analyzing data at or near the source of generation, eliminating the need for centralized data processing. This innovative approach enables real-time data insights and faster decision-making. One of the main advantages of edge analytics is its ability to process data locally, reducing latency and enhancing efficiency. It involves deploying analytics algorithms on edge devices, such as sensors or IoT devices, to analyze data locally before sending it to a centralized system. This decentralized approach not only improves response times but also reduces the burden on network bandwidth.

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Some of the Major Key Players Studied in this Report are:

➤ Oracle Corporation
➤ Cisco Systems
➤ Amazon Web Service
➤ PTC
➤ Dell Statistica
➤ EdgeConneX
➤ Hewlett Packard Enterprise Development LP
➤ Databricks
➤ IBM Corporation
➤ Intel Corporation
➤ Microsoft
➤ Analytic Edge
➤ SAP HANA
➤ AGT International Inc
➤ CGI Group Inc
➤ Others

Edge Analytics Market Analysis

The edge analytics market is experiencing robust growth driven by several key factors. Firstly, the increasing adoption of IoT devices across various industries generates vast amounts of data that can be efficiently processed at the edge. Secondly, the demand for real-time analytics and insights is pushing organizations to implement edge analytics solutions to enhance decision-making processes. Additionally, advancements in technologies such as 5G and artificial intelligence contribute to the expansion of the market, enabling faster and more sophisticated data processing capabilities. The proliferation of IoT devices generates a massive volume of data, driving the need for efficient edge analytics solutions. Continuous advancements in technologies like 5G and AI contribute to the expansion of edge analytics capabilities.

Impact of Recession

The ongoing recession has a mixed impact on the edge analytics market. On one hand, organizations may tighten their budgets, potentially delaying or scaling back investments in advanced analytics solutions. However, on the other hand, the need for operational efficiency and cost savings during economic downturns can drive increased interest in edge analytics. The ability of edge analytics to deliver real-time insights and improve overall system efficiency becomes particularly appealing to organizations aiming to streamline operations and maximize resources in challenging economic times.

Impact of Russia-Ukraine War

The Russia-Ukraine war has potential implications for the edge analytics market. Geopolitical uncertainties can disrupt supply chains and impact the global economy, influencing organizations' investment decisions. Instabilities in affected regions may lead to a heightened focus on local data processing, making edge analytics more attractive for businesses looking to mitigate risks associated with centralized systems. However, the overall impact depends on the duration and severity of the conflict, as prolonged uncertainties may lead to a cautious approach in technology investments.

Key Regional Development

The regional dynamics of the edge analytics market vary based on factors such as technological infrastructure, regulatory environment, and industry focus. Developed regions with advanced technology adoption, such as North America and Europe, are at the forefront of edge analytics implementation. The Asia-Pacific region, driven by rapid technological advancements and increasing IoT adoption, is emerging as a significant player in the market. Additionally, regulatory support and industry-specific demands contribute to the diverse regional dynamics, with each region presenting unique opportunities and challenges for the growth of the market.

Market Segmentation Analysis

Embarking on the dynamic landscape of Edge Analytics, we uncover a nuanced segmentation that mirrors the diverse applications and industries where this transformative technology thrives.

By Component:

➤ Solution: Unleashing cutting-edge technologies tailored for seamless integration into diverse business ecosystems.
➤ Services: Offering a spectrum of support services, from implementation to consulting, ensuring optimal utilization of edge analytics solutions.

By Deployment Model:

➤ On-Premises: Catering to enterprises seeking localized control and security in their edge analytics infrastructure.
➤ On-Cloud: Elevating accessibility and scalability, empowering businesses with the flexibility of cloud-based edge analytics solutions.

By Type:

➤ Descriptive Analytics: Unveiling insights into historical data, providing a comprehensive understanding of past events and trends.
➤ Predictive Analytics: Harnessing the power of data to foresee future trends, enabling proactive decision-making and risk mitigation.
➤ Prescriptive Analytics: Offering actionable insights to optimize decision-making processes, prescribing the best course of action based on data analysis.
➤ Diagnostic Analytics: Delving deep into data anomalies and patterns, identifying root causes for informed troubleshooting and optimization.

By Business Application:

➤ Marketing: Revolutionizing targeted marketing efforts through real-time insights and personalized strategies.
➤ Sales: Empowering sales teams with data-driven decision support, enhancing customer interactions and sales strategies.
➤ Operations: Optimizing operational efficiency by analyzing real-time data at the edge, minimizing delays and enhancing workflows.
➤ Finance: Redefining financial analytics, providing accurate, timely insights for prudent financial decision-making.
➤ Human Resources: Transforming HR processes through data-driven insights, from talent acquisition to employee engagement.

By Industry:

➤ Healthcare: Revolutionizing patient care and resource management through real-time analytics at the edge.
➤ Energy: Enhancing energy efficiency and grid management through edge analytics applications.
➤ Automation: Catalyzing industrial automation by providing real-time insights for streamlined processes and maintenance.
➤ Agriculture: Modernizing agriculture practices through precision farming and data-driven decision support.
➤ Manufacturing: Revolutionizing production processes with real-time analytics for quality control and efficiency.
➤ Transportation: Optimizing logistics and fleet management through edge analytics, ensuring smooth operations.
➤ Others: Exploring diverse industries harnessing the power of edge analytics for unique applications and challenges.

In navigating this segmented landscape, businesses can leverage the transformative potential of Edge Analytics strategically, unlocking unparalleled efficiency, innovation, and competitiveness.

Key Takeaways from Edge Analytics Market Study

➤ The On-premises segment is poised to assert its dominance in the market, representing a paradigm shift in the way organizations process and analyze data. On-premises solutions offer a localized approach to data analytics, allowing businesses to harness the power of edge computing within their own physical infrastructure.

➤ In the landscape of edge analytics, the Healthcare sector emerges as a dominant force, steering innovations in patient care, diagnostics, and operational efficiency. The integration of edge analytics in healthcare has the potential to revolutionize the industry by delivering real-time insights, enhancing patient outcomes, and optimizing resource utilization.

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Recent Developments Related to Edge Analytics Market

➤ Titan Torque has inked a significant new technology development contract with Steel Space Casing Drilling. The partnership is poised to usher in a new era of innovation in the drilling industry, as two industry giants join forces to push the boundaries of what is achievable in the field.

➤ Summit Casing Equipment has successfully acquired Scepter Supply. The acquisition is poised to strengthen Summit Casing Equipment's market presence and broaden its product portfolio, positioning the company as a formidable player in the industry.

Table of Contents- Major Key Points

1. Introduction

2. Research Methodology

3. Market Dynamics
3.1. Drivers
3.2. Restraints
3.3. Opportunities
3.4. Challenges

4. Impact Analysis
4.1. COVID-19 Impact Analysis
4.2. Impact of Ukraine- Russia war
4.3. Impact of Ongoing Recession on Major Economies

5. Value Chain Analysis

6. Porter’s 5 Forces Model

7. PEST Analysis

8. Edge Analytics Market Segmentation, By Component
8.1. Solution
8.2. Services

9. Edge Analytics Market Segmentation, By Deployment Model
9.1. Cloud
9.2. On-Premises

10. Edge Analytics Market Segmentation, By Type
10.1. Descriptive analytics
10.2. Predictive analytics
10.3. Prescriptive analytics
10.4. Diagnostic analytics

11. Edge Analytics Market Segmentation, By Business Application
11.1. Marketing
11.2. Sales
11.3. Operations
11.4. Finance
11.5. Human Resources

12. Edge Analytics Market Segmentation, By Industry
12.1. Healthcare
12.2. Energy
12.3. Automation
12.4. Agriculture
12.5. Manufacturing
12.6. Transportation
12.7. Others

13. Regional Analysis
13.1. Introduction
13.2. North America
13.3. Europe
13.4. Asia-Pacific
13.5. The Middle East & Africa
13.6. Latin America

14. Company Profile

15. Competitive Landscape
15.1. Competitive Benchmarking
15.2. Market Share Analysis
15.3. Recent Developments

16. USE Cases and Best Practices

17. Conclusion

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