Edge Analytics Market

Edge Analytics Market Growth Outlook (2023-2033)

The global edge analytics market is valued at US$ 7 billion in 2023 and is expected to touch US$ 62 billion by 2033, advancing at an impressive CAGR of 24.3% from 2023 to 2033 (forecast period).

Edge analytics offers real-time analysis of unstructured data produced on the edge of network devices. Instead of transmitting data back to a centralized data store or server, edge analytics conducts automatic analytical computations on acquired data in real time.

Edge analytics enables businesses to obtain more advanced data quickly by utilizing machine learning and advanced analytics at the point of data gathering. It also increases throughput, decreases downtime, and enhances efficiency.

Edge analytics is becoming increasingly popular as a result of the development and rapid growth of the Internet of Things (IoT) and the increasing availability of data via connected devices and real-time intelligence.

The retail industry is extensively using edge analytics. Traditional data warehouse models demand a significant bandwidth, money, and time to transfer all of the data to a single repository and extract the insights needed to enhance operations or customer interactions.

Retailers, using edge analytics, can evaluate all types of data in real time and seize ephemeral opportunities to create hyper-relevant consumer experiences and optimize operations, such as expediting the checkout process or ensuring items remain in stock.

Retail is dealing with massive amounts of data generated by video cameras deployed in stores, data provided by apps, in-store Wi-Fi networks, and sensors. Much of the data created is unstructured, which gives useful information. Leading retailers are leveraging cutting-edge analytics to improve user experience and increase store performance.

Major retail companies such as Walmart and Target, among others, are leveraging analytics at the network's edge to obtain insights from terabytes of data, from location analytics to boost engagement to understanding customer patterns.

Retailers can use data from a variety of sensors, such as shopping cart tags, store cameras, and parking lot sensors. By applying smart analytics to the data, they can estimate checkout wait times and notify store managers when more registers are needed or even open registers before consumers arrive.

It also assists retailers in changing their business models and reforming their strategies to gain a competitive advantage. The objective is not just to target a specific group but to provide personalized solutions for everyone via behavioral targeting.

Edge analytics is also widely used in the manufacturing and healthcare industries. Edge analytics can be used to detect production errors or anomalies, as well as poorly printed stickers, packaging, and so on, in real time. Edge devices can also filter out noisy data and capture only information considered useful by incorporating computing capabilities in the form of complex event processing (CEP).

The healthcare industry is experiencing a significant increase in the number of connected devices. A hospital room in the future will likely feature 20 to 25 medical gadgets, the bulk of which will be connected. A major hospital can have up to 80,000 connected medical and IoT devices, which puts substantial pressure on the cloud network. Edge analytics and computing can significantly lessen this burden.

Report Attributes	Details
Edge Analytics Market Size (2023)	US$ 7 Billion
Projected Market Value (2033)	US$ 62 Billion
Global Market Growth Rate (2023-2033)	24.3% CAGR
North America Market Value (2022)	US$ 2.2 Billion
Predictive Analytics Segment Growth Rate (2023-2033)	18.7% CAGR
Key Companies Profiled	AGT International Inc CGI Group Inc Analytic Edge Cisco Corporation Dell Inc Foghorn Systems Greenwave Systems, Inc Equinix, Inc HP Inc

Why is Edge Analytics Exhibiting Such High Demand?

“Edge Analytics Results in Lowest Possible Latency”

The main advantage of edge analytics is that it minimizes latency and consequently enhances overall system performance. It also allows users to respond to specific data points more rapidly, such as shutting off an overheating jet engine, without having to check in with a central procedure.

As data is processed at the edge, application developers can use local computation cycles without experiencing network latency. This enables developers to access data in real time instead of waiting for it to be uploaded to the cloud, which is useful for applications like OT management, predictive maintenance, and machine learning.

Country-wise Insights

Why is the United States the Largest Revenue Generator in North America?

“Increasing Adoption of Edge Analytics across the Country”

Demand for edge analytics in North America is increasing and this market garnered US$ 2.2 billion in 2022.

The United States is the largest revenue generator in the North American market due to the rising adoption of edge analytics among small and medium-sized businesses. Furthermore, the high concentration of telecommunication and manufacturing industries that heavily use edge analytics services is boosting the market growth in the United States. The demand for edge analytics is closely connected to cloud traffic. As a result of the massive increase in cloud traffic, the need for edge analytics is projected to grow significantly.

What is the Market Outlook for Edge Analytics in Japan & South Korea?

“Rapid Development of Networking Technology”

The Asia Pacific market is expected to grow considerably over the next ten years, owing to rising demand for high-performance computing solutions from many end-use industries and greater usage by small and medium businesses (SMEs).

Furthermore, the sales of edge analytics are growing in Japan and South Korea due to the rapid development of networking technology in these countries.

Which Aspects are Raising the Demand for Edge Analytics in Germany?

“Increasing Number of Connected Devices and Growing Demand for Advanced Real-Time Analytics”

The European market is predicted to experience significant growth during the forecast period. The demand for edge analytics is expanding in Germany due to a growth in the number of connected devices and a rise in the demand for advanced real-time analytics.

Category-wise Insights

Why is Demand for Predictive Analytics Expanding Rapidly?

“Predictive Analytics to Act as Primary Growth Driver for Edge Analytics”

The demand for predictive analytics is expected to develop at a CAGR of 18.7% during the forecast period.

Predictive analytics has been a key driver of analytics and is now being applied at network edges to give analytics at the edge (gateways, switches, routers), lowering the expense of data transfer, storage, and analysis, which is crucial during data processing on centralized analytic platforms.

Predictive analytics has been a primary growth driver for edge analytics. It uses pre-defined intelligence (algorithms) embedded in the server, which can make decisions based on previous patterns.

The traffic department heavily relies on predictive analytics to acquire real-time intelligence to reroute traffic, reduce traffic congestion, and so on. Traffic lights are equipped with sensors that have the analytic capacity to identify emergency vehicles like convoys, police cars, and ambulances.

Likewise, oil and gas industries utilize real-time predictive analytics to identify anomalies (such as acoustic sensing and rising temperatures) and alert concerned officials by transmitting messages and activating alarms to avert disaster. Such aspects are boosting the demand for predictive analytics.

Competitive Landscape

The global market for edge analytics is very competitive, with multiple major competitors. Key players in the edge analytics market are focusing on expanding their consumer base in international countries. These players are using strategic collaboration initiatives to increase their market share and profitability.

While many organizations developing edge computing technology are established industry players and global tech giants, the startups providing much of the innovation and many new products and services are critical to the edge analytics market's long-term growth.

• SliceUp, a start-up based in the United States, develops an analytics system built on an edge and cloud technology ecosystem. Edge computing systems use AI and Machine Learning to detect anomalies at the point where raw data is generated. The system can send critical and relevant information to the backend or store it in the cloud server while removing anomalous data. This assists IT departments in reducing the time, effort, and expense associated with operational security.
• Cisco collaborated with NetApp, a multinational, data-centric, cloud-led software firm, in April 2022. NetApp collaborated with Cisco to introduce FlexPod XCS, the progression of FlexPod that offers a single automated platform for data, modern apps, and hybrid cloud services. FlexPod XCS, powered by Cisco Intersight, offers companies significant new features like visibility, automation, and hybrid cloud operations in a single unified platform.
• Hewlett Packard Enterprise joined forces with Maxis, one of Malaysia's leading telecom operators, in April 2022. Through their collaboration, both firms aimed to create the country's first multi-access edge computing (MEC) solution for enterprises. MEC systems will appeal to enterprises running time-critical edge applications such as artificial intelligence, data analytics, machine learning, and automation. MEC can decrease connectivity issues and data storage expenses by improving efficiency and accuracy in real time.
• Intel Corporation acquired Granulate Cloud Solutions, an Israeli provider of real-time continuous optimization software, in March 2022. Granulate's purchase would help cloud and data center clients maximize compute workload performance while lowering infrastructure and cloud expenses.
• Equinix struck a collaboration with Nasdaq, a New York-based American stock exchange, in January 2022. Under the multi-year agreement, the companies intended to expand the Equinix NY11 data center in Carteret, New Jersey, to support Nasdaq's cloud infrastructure build-out. The collaboration was designed to get Nasdaq closer to moving its markets to the cloud. Equinox would assist Nasdaq in meeting current and future infrastructure needs while also expediting its worldwide cloud transformation.

Key Segments of Edge Analytics Industry Research

• By Component :

  • Solutions
  • Services

• By Type :

  • Predictive Analytics
  • Diagnostic Analytics
  • Prescriptive Analytics
  • Descriptive Analytics

• By End Use :

  • IT & Telecom
  • BFSI
  • Transportation & Logistics
  • Manufacturing
  • Retail & Consumer Goods
  • Energy & Utilities
  • Others

• By Region :

  • North America
  • Latin America
  • Europe
  • APAC
  • MEA