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

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

Edge Analytics Market Growth & Trends

The global edge analytics market size is estimated to reach USD 40.71 billion by 2030, registering a CAGR of 25.3% from 2023 to 2030, according to a new report by Grand View Research, Inc. Performing data analysis and processing on the edge devices themselves, robots can quickly respond to their environment without relying heavily on a centralized system. This approach offers real-time insights, reduced latency, improved security, and optimized bandwidth. With the rise of the Internet of Things and the increasing amount of data generated at the edge, edge analytics has gained significant attention. Many industrial organizations use the Internet of Things (IoT) to monitor manufacturing machinery, pipelines, and equipment.

IoT generates and stores data that might be challenging to manage and interpret in real time. The data from IoT devices is delivered into edge analytics to be processed and understood. Analytics algorithms assist humans in determining which data is required and which is unnecessary. In many applications and industries, timely decisions are crucial for achieving operational efficiency, ensuring safety, and delivering superior customer experiences. Certain applications, such as autonomous vehicles, industrial automation, and smart cities, demand real-time analytics capabilities.

Edge analytics enable immediate processing and decision-making at the edge, minimizing latency and enabling rapid responses. Moreover, industries such as drones and robotics heavily rely on real-time decision-making capabilities. These systems must process vast amounts of sensor data and respond instantaneously to changing environments and situations. Edge analytics enable the analysis and interpretation of sensor data at the edge, allowing these autonomous systems to make quick and accurate decisions without relying on centralized processing.

The increasingly vast amount of data from connected devices around the globe is driving market expansion, real-time intelligence acting as a catalyst for the growth of edge analytics on network devices and adopting edge analytics, enhancing scalability and cost optimization. Analytical computing is performed at the device's edge rather than waiting for data to be retrieved back at a centralized storage system and then imply analytical application. Furthermore, the manufacturing industry may make substantial use of edge analytics, for example, in smart production lines, pointing out manufacturing errors, packing, and so on in real-time. The IoT connects numerous devices and sensors that generate massive volumes of data in real-time; by applying the technology, this data can be processed and analyzed at the edge, enabling rapid decision-making and reducing the need to transmit all data to a central location. For example, in smart cities, it can help monitor and manage traffic patterns, energy consumption, and public safety in real-time.

In the manufacturing sector, it enables real-time monitoring and predictive maintenance of machines and equipment; by analyzing sensor data at the edge, manufacturers can identify potential failures, optimize maintenance schedules, and minimize downtime. It also plays a crucial role in healthcare by enabling real-time patient monitoring, remote diagnostics, and personalized treatment. Edge devices can analyze patient data, including vital signs and medical history, to provide timely insights for healthcare professionals. Retailers can leverage it for real-time inventory management, customer analytics, and personalized shopping experiences; by analyzing point-of-sale data, foot traffic patterns, and customer preferences at the edge, retailers can optimize inventory levels, enhance customer satisfaction, and offer targeted promotions.

North America will attain a larger market share in the edge analytics market; predictive analytics have importance in the region and will increase the adoption of edge analytics solutions with a higher concentration of industrial and telecommunication industries. With the rising connection of IoT devices, the regional market has seen a surge in the adoption rate of edge analytics solutions across all verticals. Implementation of edge analytics to keep better track of the health of equipment and output rate and prepare the manufacturing plant to deal with any last-minute problems in production.

Various regional industries have identified the potential benefits and implemented them in specific use cases. For example, it is used in manufacturing for predictive maintenance and quality control. These industry-specific applications have contributed to the growth of the edge analytics market in the region. The region has specific regulations and standards such as data privacy laws and compliance requirements like the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). It provides a solution to address data security and privacy concerns by processing sensitive data locally, thereby complying with regulatory requirements.

Edge Analytics provides the same capability as a traditional analytics tool, with the exception of where the analytics are conducted. The key distinction is that edge analytics programmers must run on edge devices that may be limited in storage, computing power, or connection. Digitization has been the driving force behind the most recent revolutions. Companies have long struggled with how to extract relevant insights from the millions of nodes of data created each day by IoT-connected devices. The amount of linked gadgets, from a smartwatch to a smart speaker, is increasing the volume of data to be mined. Many new technologies, like as AI and Big Data, have become indispensable for gathering insights.

North America will gain a larger market share in the edge analytics market due to an increase in the need for predictive analytics, which will increase the adoption of edge analytics solutions with a higher concentration of industrial and telecommunications industries. With the rise of IoT, there has been a surge in interest in edge analytics. For many firms, streaming data from different IoT sources produces a massive data repository that is challenging to manage.

Edge Analytics Market Report Highlights

• Predictive analytics has been a major force behind analytics, and it is presently being implemented at the network's edges to deliver analytics at the edge, allowing it to achieve a CAGR of 25.8% from 2023 to 2030
• Based on deployment mode, increasing adoption of cloud technology globally is contributing to the growth of the cloud deployment segment, allowing it to lead the edge analytics market with market share of more than 50.0% in 2022
• During the forecast period, the IT and telecommunications industry is predicted to have the greatest growth rate in the edge analytics market. The telecommunications business is rapidly introducing cutting-edge analytical solutions
• North America is expected to exceed a market share of 34.0% in 2022, expanding at a CAGR of more than 22% over the forecast period owing to the technological advancements in field of robotics, artificial intelligence, predictive analysis and connected automotive among others

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