Edge analytics, an alternative to big data analytics, provides real-time analysis of data generated on the edge of network devices, which is in an unstructured form. Edge analytics performs the automatic analytical computation of collected data in real-time, instead of sending the data back to the centralized data store or server.

Edge Analytics is increasing at significant force across the world, owing to the constant advancements of workplace performance enhancements and increase adoption of internet of things (IoT), which are driving the edge analytics market growth to the large extent. Moreover, its distinctive features like cost optimization and scalability are significantly boosting the growth of the market.

- Edge analytics help companies to get more advanced data faster by employing advanced analytics and machine learning at the point of data collection. Also, it further boosts yields, increases throughput, reduces downtime, and improves efficiency. It is gaining increasing demand owing to the emergence and the booming expansion of the Internet of Things (IoT) and the fast-paced growth in the availability of data through connected devices and via real-time intelligence.

- The manufacturing industry can make extensive use of Edge analytics, for instance, in a smart production line. Pointing out manufacturing defects or anomalies, badly printed stickers, packaging, etc., in real-time can be achieved using edge analytics. Further, by embedding computing capability in the form of complex event processing (CPE), edge devices can filter out noisy data and collect only information that is deemed useful.

- Healthcare is another domain where a massive surge in the number of connected devices can be witnessed. In the future, a hospital room on an average will have around 15 to 20 medical devices, a majority of which are expected to be networked. A large hospital can have as much as 85,000 connected medical and IoT devices, putting a significant strain on the cloud network. Edge analytics and computing can reduce this burden to a great extent.

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Key Market Trends

Retail Industry to Drive the Edge Analytics Market

- With a traditional data warehouse model, it takes significant bandwidth, time, and cost to transmit all the data to a central repository and extract the insights required to improve operations or customer interactions. Using edge analytics, retailers will be able to analyze all types of data real-time and capture fleeting opportunities to deliver hyper-relevant customer experiences and optimize operations, such as streamlining the checkout or ensuring items are in stock.

- Retail is experiencing huge data that is generating from the video camera installed in the store, in-store Wi-Fi networks, sensors, and data generated from apps. Much of the produced data is unstructured in nature, which provides valuable information. Leading retailers are utilizing edge analytics to deliver better user experience and maximize store performance. From location analytics to drive engagement to understand shopper’s pattern, retail giants Target and Walmart, among others, are using analytics at the edge of the network to draw insights from terabytes of data.

- Retailers can leverage data from a range of sensors including parking lot sensors, shopping cart tags, and store cameras. By applying smart analytics to the data, they can predict checkout wait times and preemptively alert store service managers when more registers are required to be opened, or even automatically open registers before customers get there. It also helps retailers to change their business model and reform their strategies to main competitive edge. The idea is not limited to targeting a group of audiences but offering personalized solutions for everyone with the help of behavioral targeting.

North America Holds the Largest Share in Edge Analytics Market

- The United States remains a prominent market for Edge Analytics, due to increasing acceptance of edge analytics among small and medium-scale firms, supported by government regulations and compliance. Additionally, significant growth of the edge analytics market can be attributed to the high concentration of manufacturing and telecommunication industries that majorly adopt edge analytics services. The demand for edge analytics is directly related to cloud traffic. Due to the huge increase in cloud traffic, significant growth in the market can be observed.

- North American Insurance companies are changing the way they utilize cloud computing. While both property & casualty and life insurers have employed cloud to increase agility, increase operating efficiency, attract new talent and reduce operating costs, there is an emerging trend in insurers viewing the cloud as a business asset. Cloud operations cost can be significantly reduced by using a distributed edge computing architecture, where edge devices together process a critical operation, which a cloud device cannot process on its own, thereby reducing cloud dependency.

- Also, significant growth in sensor technology can be witnessed in the region. By combining the innovations of sensor technology with reducing hardware costs, the edge-to-cloud paradigm can be established. Sensors with processing units can help take critical actions in an inconsistent cloud environment and can later synchronize with the cloud.

Competitive Landscape

The edge analytics market is extremely competing and consists of numerous significant players. In terms of market share, few of the significant players currently control the market. These important players with a noticeable share in the market are concentrating on growing their customer base across foreign countries. These businesses are leveraging strategic collaborative initiatives to enhance their market share and improve their profitability.

- May 2018 - Wood and IBM collaborated to transform the asset life cycle management. This partnership is expected to help create and offer new digital products and services that can help increase operational efficiencies for customers in the industrial and energy markets. The transformation was realized with the help of the edge analytics suite of IBM.

- Mar 2019 - FogHorn, announced that NTT Data selected its Lightning software to deliver on-premise real-time analytics and AI to their industrial clients. NTT Data offers deep expertise and IoT consulting and integration services which are utilized by FogHorn in the manufacturing, telecommunications, and energy industries.

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