Global Edge Analytics Market

Focus on Components, Mode of Deployments (On Premise, Hybrid and Others), Applications (Manufacturing, Transportation and Others), Competitive Landscape, and 20 Country's Analysis - Analysis and Forecast (2018-2025)

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Market Overview

The global edge analytics market was estimated to be $2.14 billion in 2017, and is expected to reach $13.44 billion by the end of

The Internet of Things (IoT) is bolstering the growth of many industries and is amplifying the value provided by the organizations to their customers. Smart cities, smart manufacturing, connected cars, and location-based intelligence are several ways through which IoT solutions are establishing a connected ecosystem. However, the success and evolution of this ecosystem depends upon the ability of IoT solutions to process data (generated by sensors and other devices) in real time at the network’s edge.

Although, the emergence of cloud technologies has made it possible to develop such an ecosystem, there are challenges associated such as enhanced connectivity requirements and latency issues. Pushing huge amounts of data to the cloud for computation and awaiting analytical results may tremendously increase data transmission costs and simultaneously damage valuable milliseconds required for instantaneous feedback thus damaging real time responsiveness. Billions of devices are generating data with tenacity and making sense this big data will require huge investments in the expansion of computational resources such as analytics, storage and networking software in conjunction with computing platforms. Also, the IoT implementation requires skilled staff complex integration of different devices from different manufacturers having their own set of standards. Hence, organisations utilising traditional approaches to data analytics will need to heavily invest in the expansion of IT resources to leverage the full potential of IoT.

Edge computing or Edge analytics, comes as a solution to help organizations overcome the infrastructure limitations. The technology is an evolution of cloud computing/analytics and an industrial manoeuvre to go one step ahead of democratising data analysis capabilities. It allows data processing right at the point where it is generated (for example: sensors, gateways etc.). Hence, instead of sending data to the cloud for processing and waiting for the analytical results, edge computing pushes the computation part to the edge of a network thus saving on response time as well as data transmission costs.

The global edge analytics market was estimated to be $2.14 billion in 2017, and is expected to reach $13.44 billion by the end of 2025, registering a CAGR of 22.2% during the forecast period, 2018-2025. The expected double-digit growth can be attributed to the rapid proliferation in the number of connected devices and the continuous explosion of data generated by these devices. According to Cisco, a global networking company, there will be nearly 20 billion connected devices by the end of 2020, generating zettabytes of data. An average internet user is expected to generate 1.5 GB of data every day and the video traffic will also reach nearly a petabyte every day. However, there are various factors impeding the market growth and serve as challenges for the stakeholders, such as lack of standardization of network protocols, newly introduced data privacy regulations, integration of devices and identification of edge nodes. Despite the challenges, the edge analytics ecosystem provides the stakeholders with enormous opportunities. The rising amount of capital investments into the IoT ecosystem is a key determinant of growth in the edge analytics market and will further proliferate in the upcoming years. Local governments in countries such as Australia, the U.S., India, South Korea are heavily focussed on improving the operational efficiencies of their businesses and expansion in the organizational infrastructure.

Currently, the global edge analytics market is a blend of a multitude of players from public cloud, ISVs, and networking companies and each company is entering the market from a different perspective. The current market landscape comprises of players such as: Microsoft, IBM, Google, Amazon AWS (Public cloud providers), Cisco, AT&T (networking companies), Oracle (Independent software vendors/ ISVs) and Schneider Electric, GE digital, and Siemens (industrial automation companies) among others

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Key Questions Answered in this Report:

What are the major market drivers, challenges and opportunities in the global edge analytics solutions market?

•    What are the major market drivers, challenges and opportunities in the global edge analytics solutions market?
•    What was the market value of the leading segments and sub-segments of the global edge analytics solutions market in 2017?
•    How will each segment of the global edge analytics solutions market grow during the forecast period and what will be the revenue generated by each of the segments by the end of 2025?
•    What are the influencing factors that may affect the market share of the key players?
•    How will the industry evolve during the forecast period 2018- 2025?
•    What are the key developments and strategies that are being implemented by the key players to sustain in this market?
•    What are the key application areas of the global edge analytics solutions market? How each of the application areas are employing edge computing?
•    Who are the key players in the global edge analytics solutions market and what are their contributions?
•    What is the scope for expansion by the key players of the global edge analytics solutions market in East and South-East Asia?

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Report Description

The market report is well designed to provide an all-inclusive field of vision about the market in terms of various factors influe

The global edge analytics market comprises of hardware devices, software and professional services that helps in bringing automated analytical computation at the edge of the network. In general, edge analytics is relatively a new term which aims at collecting and analyzing data at the point where it is generated such as sensors, IoT gateways, network switches and other devices. This automated computation at the edge saves time, improves latency and reduces transmission cost of sending data to the cloud servers. The technology has gained momentum with the rising prevalence of IoT connected devices. Industries, such as manufacturing, transportation, and automobile are the most prominent participants of the IoT revolution and generate tremendous amount of operational data which can be difficult and expensive to manage. By processing data at the edge of a corporate network can empower companies to decide if the data is needed to be sent to the cloud or not. This is particularly useful in environments, such as oil rigs, aircraft, CCTV cameras, connected cars, remote manufacturing where there may not be sufficient time to transmit data to a centralized location and wait for the results. Also, edge analytics could prove to be a boon for the remotely located enterprises where there is a shortage of bandwidth to transmit operational data back and forth and hence, edge can efficiently provide computation and analytics capabilities in remote locations.

An IoT gateway plays a very significant role in the deployment of edge analytics in any enterprise. This device acts as a bridge between connected devices and the centralised cloud server. Rising number of devices is consistently pushing the demand for these devices in solving data management issues. The gateway extracts all the sensor data and applies various rule-based algorithms and sends actionable commands to the connected devices in real time.

Currently, edge analytics solutions are extensively being deployed in retail, manufacturing, energy, smart cities, transportation and logistics vertical segments. Some of the major use cases of edge analytics include: retail customer behaviour analysis, remote monitoring and maintenance for energy operations, fraud detection at financial locations (ATMs), and monitoring of manufacturing & logistics equipment.

The market report is well designed to provide an all-inclusive field of vision about the market in terms of various factors influencing it such as, recent trends, technological advancements, and regulatory environment of the market. The scope of this report is centered upon conducting a detailed study of the solutions allied with the global edge analytics solutions market. The market has been segmented into ‘Mode of Deployment’, ‘Components’, ‘Application’, and ‘Region’. The report presents the reader with an opportunity to unlock comprehensive insights with respect to the market, and helps in forming well informed strategic decisions. The research uncovers some of the substantial parameters that must be taken into consideration before entering into the market.

This research report aims at answering various aspects of the global edge analytics solutions market with the help of the key factors driving the market, threats that can possibly inhibit the overall growth of the market, and the current investment opportunities that are going to shape the future trajectory of the market expansion. The study considers the growth-share matrix model for a comprehensive study of the global edge analytics solutions market and assesses the factors governing the same.

The current edge analytics solutions market landscape consists of leading players from the public cloud segment such as Microsoft, IBM, Google, and Amazon AWS. There are also some of the leading networking companies such as Cisco and AT&T entering the market with edge computing capabilities, followed by a multitude of industrial automation companies such as GE Corporation, Schneider Electric and Siemens, among others.

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Table of Contents

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1.1    What is an Edge?
1.2    Need of Edge Analytics?
1.3    Components of Edge Analytics?
1.3.1    Actuators
1.3.2    Smart Devices
1.3.3    Smart Appliances
1.3.4    IoT Smart Gateway
1.4    Field Protocols
1.5    Cloud Protocols
1.5.1    Message Queue Telemetry Transport (MQTT)
1.5.2    Advanced Message Queuing Protocol (AMQP)
1.5.3     Constrained Application Protocol (CoAP)
1.5.4    Hypertext Transfer Protocol (HTTP)
1.6    IoT Management Protocols
1.6.1    Interconnection of Heterogeneous Datalinks
1.6.2    Smart Transducer Interface
1.7    Security in IoT Protocols
1.7.1    MAC 802.15.4
1.7.2    6LoWPAN
1.7.3    RPL
1.7.4    Application Layer

2.1    Overview
2.2    Impact Analysis
2.3    Market Drivers
2.4    Market Challenges
2.5    Market Opportunities

3.1    Key Developments and Strategies
3.1.1    Product Launches
3.1.2    Partnerships and Collaborations
3.1.3    Merger & Acquisition
3.1.4    Business Expansion
3.2    Patent Analysis
3.3    Market Share Analysis by Company

4.1    Overview
4.2    On Premise
4.3    Hybrid Model

5.1    Hardware
5.2    Software
5.3    Services

6.1    Manufacturing and Construction
6.2    Transportation and Logistics
6.3    Entertainment
6.4    Automotive
6.5    Healthcare
6.6    Retail
6.7    Agriculture
6.8    Others

7.1    North America
7.1.1    U.S.
7.1.2    Canada
7.2    Europe
7.2.1    U.K.
7.2.2    Germany
7.2.3    Spain
7.2.4    France
7.2.5    Italy
7.2.6    Rest of Europe
7.3    Asia Pacific
7.3.1    India
7.3.2    China
7.3.3    South Korea
7.3.4    Singapore
7.3.5    Thailand
7.3.6    Japan
7.3.7    Malaysia
7.3.8    Rest of Asia Pacific
7.3.8.1    Australia
7.3.8.2    New Zealand
7.4    Rest of the World (RoW)
7.4.1    Kingdom of Saudi Arabia (KSA)
7.4.2    United Arab Emirates (UAE)
7.4.3    Kuwait
7.4.4    Israel
7.4.5    North Africa
7.4.6    Brazil
7.4.7    Mexico
7.4.8    Russia
7.4.9    Rest of RoW

8.1    AGT International, Inc
8.1.1    Overview
8.1.2    Product Portfolio
8.1.3    Corporate Summary
8.1.4    SWOT Analysis
8.2    Amazon Web Services
8.2.1    Overview
8.2.2    Product Portfolio
8.2.3    Corporate Summary
8.2.4    SWOT Analysis
8.3    Cisco Systems, Inc.
8.3.1    Overview
8.3.2    Product Portfolio
8.3.3    Financials
8.3.3.1    Financial Summary
8.3.4    SWOT Analysis
8.4    Dell
8.4.1    Overview
8.4.2    Product Portfolio
8.4.3    Financials
8.3.4.1    Financial Summary
8.4.4    SWOT Analysis
8.5    FogHorn Systems
8.5.1    Overview
8.5.2    Product Portfolio
8.5.3    Corporate Summary
8.5.4    SWOT Analysis
8.6    GE Corporation
8.6.1    Overview
8.6.2    Product Portfolio
8.6.3    Financials
8.6.3.1    Financial Summary
8.6.4    SWOT Analysis
8.7    Greenwave Systems
8.7.1    Overview
8.7.2    Product Portfolio
8.7.3    Corporate Summary
8.7.4    SWOT Analysis
8.8    HP Inc.
8.8.1    Overview
8.8.2    Product Portfolio
8.8.3    Financials
8.8.3.1    Financial Summary
8.8.4    SWOT Analysis
8.9    IBM Corporation
8.9.1    Overview
8.9.2    Product Mapping
8.9.3    Financials
8.9.3.1    Financial Summary
8.9.4    SWOT Analysis
8.10    Intel Corporation
8.10.1    Overview
8.10.2    Product Mapping
8.10.3    Financials
8.10.3.1    Financial Summary
8.10.4    SWOT Analysis
8.11    MachineShop Inc.
8.11.1    Overview
8.11.2    Product Mapping
8.11.3    Corporate Summary
8.11.4    SWOT Analysis
8.12    Microsoft Corporation
8.12.1    Overview
8.12.2    Product Mapping
8.12.3    Financials
8.12.3.1    Financial Summary
8.12.4    SWOT Analysis
8.13    NVIDIA Corporation
8.13.1    Overview
8.13.2    Product Mapping
8.13.3    Financials
8.13.3.1    Financial Summary
8.13.4    SWOT Analysis
8.14    Oracle Corporation
8.14.1    Overview
8.14.2    Product Mapping
8.14.3    Financials
8.14.3.1    Financial Summary
8.14.4    SWOT Analysis
8.15    PointGrab Ltd.
8.15.1    Overview
8.15.2    Product Mapping
8.15.3    Corporate Summary
8.15.4    SWOT Analysis
8.16    PTC Inc.
8.16.1    Overview
8.16.2    Product Mapping
8.16.3    Financials
8.16.3.1    Financial Summary
8.16.4    SWOT Analysis
8.17    SAP
8.17.1    Overview
8.17.2    Product Mapping
8.17.3    Financials
8.17.3.1    Financial Summary
8.17.4    SWOT Analysis
8.18    SAS
8.18.1    Overview
8.18.2    Product Mapping
8.18.3    Corporate Summary
8.18.4    SWOT Analysis
8.19    Snapshot of Key Players
8.19.1    ADLINK Technology Inc.
8.19.2    Altizon Systems
8.19.3    Mimik Technology Inc.
8.19.4    Open-Silicon, Inc
8.19.5    Zenlayer
8.19.6    Pixeom, Inc. 
8.19.7    Qwilt
8.19.8    Virtuosys

1    Country Wise Market Value, 2017 ($Million)
2    Country Wise Number of Connected Devices, 2017 ($Million)
3    Different type of Sensors used in the field of IoT
4    Different type of Sensors used in the field of IoT
5    Different type of Actuators used in the field of IoT
6    IoT Transport Layer Standards Comparison
7    New Security Mechanisms under Development/Developed to deal with resource constrained IoT devices
8    Point of Distinction (Similarities as Well as Differences) Between Edge Computing and Data Centre Computing
9    Microsoft's Cloud based Services
10    Pricing Model for Microsoft's Azure IoT Platform
11    Impact Analysis of Market Navigating Factors
12    Commercially available IoT Gateway Hardware
13    Commercially available Edge Computing Software
14    Internet Connectivity in Canada
15    Overview-AGT International, Inc
16    Overview-Amazon Web Services
17    Overview-Cisco Systems, Inc.
18    Overview-Dell
19    Overview-FogHorn Systems
20    Overview-GE Corporation
21    Overview-Greenwave Systems
22    Overview-HP Inc.
23    Overview-IBM Corporation
24    Overview-Intel Corporation
25    Overview-Machineshop Inc.
26    Overview-Microsoft Corporation
27    Overview-NVIDIA Corporation
28    Overview-Oracle Corporation
29    Overview-PointGrab Ltd.
30    Overview-PTC Inc.
31    Overview-SAP
32    Overview-SAS
33    Overview-ADLINK Technologies Inc.
34    Overview-Altizon Systems
35    Overview-Mimik Technology Inc.
36    Overview-Open-Silicon, Inc
37    Overview-Zenlayer
38    Overview-Pixeom, Inc.
39    Overview-Qwilt
40    Overview-Virtuosys

1    Rising of Connected Devices propelling the Market Growth
2    A Glimpse of Upcoming Demand for Edge Computing based on IoT Use Cases
3    Market Drivers and Market Restraints
4    Market Statistics
5    Figure: Global Edge Analytics Market Share, by Company (2016)
6    Global Edge Analytics Market (2018-2025)
7    IoT Initiatives in different regions of the World
8    Market Snapshot, Global Edge Analytics Solutions Market, 2018-2025
9    Edge Computing Architecture
10    Components of IoT Gateway within an Edge Computing Environment
11    Market Dynamics
12    Share of Key Developments and Strategies
13    Global Edge Analytics Solutions Market Share, by Company (2017)
14    Cloud Service Models (IaaS, PaaS, and SaaS)
15    Global Edge Analytics Solutions Market, by Components, 2018-2025 ($Million)
16    Global edge computing market by hardware components, 2018-2025 ($Million)
17    Global edge computing market by Software components, 2018-2025 ($Million)
18    Global edge computing market by Services components, 2018-2025 ($Million)
19    Spending on Internet of Things by Verticals in 2015 and 2020 (in $billion)
20    Global manufacturing and Construction application segment, by Value, 2018-2025 ($Million)
21    Global Transportation and Logistics application segment, by Value, 2018-2025 ($Million)
22    Global Entertainment application segment, by Value, 2018-2025 ($Million)
23    Global Automotive application segment, by Value, 2018-2025 ($Million)
24    Global Healthcare application segment, by Value, 2018-2025 ($Million)
25    Global Retail application segment, by Value, 2018-2025 ($Million)
26    Global Agriculture application segment, by Value, 2018-2025 ($Million)
27    Other application segment, by Value, 2018-2025 ($Million)
28    Global Edge Analytics Solutions Market, by Region 2018-2025 ($Million)
29    North America Edge Analytics Solutions Market, 2018-2025 ($Million)
30    North America Edge Analytics Solutions Market, by Country 2018-2025 ($Million)
31    U.S. Edge Analytics Solutions Market, 2018-2025 ($Million)
32    Canada Edge Analytics Solutions Market, 2018-2025 ($Million)
33    Europe Edge Analytics Solutions Market, 2018-2025 ($Million)
34    Europe Edge Analytics Solutions Market, by Country 2018-2025 ($Million)
35    Germany Edge Analytics Solutions Market, 2018-2025 ($Million)
36    France Edge Analytics Solutions Market, 2018-2025 ($Million)
37    Spain Edge Analytics Solutions Market, 2018-2025 ($Million)
38    Italy Edge Analytics Solutions Market, 2018-2025 ($Million)
39    U.K. Edge Analytics Solutions Market, 2018-2025 ($Million)
40    Rest of Europe Edge Analytics Solutions Market, 2018-2025 ($Million)
41    Asia Pacific Edge Analytics Solutions Market, 2018-2025 ($Million)
42    Asia Pacific Edge Analytics Solutions Market, by Country 2018-2025 ($Million)
43    India Edge Analytics Solutions Market, 2018-2025 ($Million)
44    China Edge Analytics Solutions Market, 2018-2025 ($Million)
45    Japan Edge Analytics Solutions Market, 2018-2025 ($Million)
46    South Korea Edge Analytics Solutions Market, 2018-2025 ($Million)
47    Australia Edge Analytics Solutions Market, 2018-2025 ($Million)
48    Rest of Asia Pacific Edge Analytics Solutions Market, 2018-2025 ($Million)
49    Rest of the World (RoW) Edge Analytics Solutions Market, 2018-2025 ($Million)
50    Rest of the World (RoW) Edge Analytics Solutions Market, by Country 2018-2025 ($Million)
51    Mexico Edge Analytics Solutions Market, 2018-2025 ($Million)
52    Russia Edge Analytics Solutions Market, 2018-2025 ($Million)
53    Middle East and Africa (MENA) Edge Analytics Solutions Market, 2018-2025 ($Million)
54    Brazil Edge Analytics Solutions Market, 2018-2025 ($Million)
55    Argentina Edge Analytics Solutions Market, 2018-2025 ($Million)
56    Rests of RoW Edge Analytics Solutions Market, 2018-2025 ($Million)
57    AGT International, Inc.: Product Portfolio
58    AGT International, Inc.: SWOT Analysis
59    Amazon Web Services: Product Portfolio
60    Amazon Web Services: SWOT Analysis
61    Cisco Systems, Inc.: Product Portfolio
62    Cisco Systems, Inc. : Overall Financials (2014-2016)
63    Cisco Systems, Inc. : Net Revenue by Business Segment (2014-2016)
64    Cisco Systems, Inc. : Net Revenue by Geography(2014-2016)
65    Cisco Systems, Inc.: SWOT Analysis
66    Dell: Product Portfolio
67    Dell: Overall Financials (2014-2016)
68    Dell: Net Revenue by Business Segment (2014-2016)
69    Dell: Net revenue by Region (2014-2016)
70    Dell: SWOT Analysis
71    FogHorn Systems: Product Portfolio
72    FogHorn Systems: SWOT Analysis
73    GE Corporation: Product Portfolio
74    GE Corporation: Overall Financials (2014-2016)
75    GE Corporation: Net Revenue by Business Segments (2014-2016)
76    GE Corporation: Net Revenue by Geography (2014-2016)
77    GE Corporation: Percentage of Revenues by Healthcare Sub Segments : 2016
78    GE Corporation: SWOT Analysis
79    Greenwave Systems: Product Portfolio
80    Greenwave Systems: SWOT Analysis
81    HP Inc.: Product Portfolio
82    HP Inc.: Overall Financials (2014-2016)
83    HP Inc.: Net Revenue by Business Segments (2014-2016)
84    HP Inc.: Net Revenue by Personal Systems Segment (2014-2016)
85    HP Inc.: Net Revenue by Printing Segment (2014-2016)
86    HP Inc.: Net Revenue by Region (2014-2016)
87    HP Inc.: SWOT Analysis
88    IBM Corporation: Product Portfolio
89    IBM Corporation: Overall Financials (2015-2017)
90    IBM Corporation: Net Revenue by Business Segment (2015-2017)
91    IBM Corporation: Net Revenue by Region(2015-2017)
92    IBM Corporation: SWOT Analysis
93    Intel Corporation: Product Portfolio
94    Intel Corporation: Overall Financials (2015-2017)
95    Intel Corporation: Net Revenue by Business Segment (2015-2017)
96    Intel Corporation: Net Revenue by Geography(2015-2017)
97    Intel Corporation: SWOT Analysis
98    MachineShop Inc.: Product Portfolio
99    MachineShop Inc.: SWOT Analysis
100    Microsoft Corporation: Product Portfolio
101    Microsoft Corporation: Overall Financials (2015-2017)
102    Microsoft Corporation: Net Revenue by Business Segments (2015-2017)
103    Microsoft Corporation: Net Revenue by Region (2015-2017)
104    Microsoft Corporation: SWOT Analysis
105    NVIDIA Corporation: Product Portfolio
106    NVIDIA Corporation: Overall Financials (2015-2017)
107    NVIDIA Corporation : Net Revenue by Business Segments (2015-2017)
108    NVIDIA Corporation : Net Revenue by Region (2015-2017)
109    NVIDIA Corporation: SWOT Analysis
110    Oracle Corporation: Product Portfolio
111    Oracle Corporation: Overall Financials (2014-2016)
112    Oracle Corporation: Net Revenue by Business Segments (2014-2016)
113    Oracle Corporation: Net Revenue by Geography(2014-2016)
114    Oracle Corporation: SWOT Analysis
115    PointGrab Ltd.: Product Portfolio
116    PointGrab Ltd.: SWOT Analysis
117    PTC Inc.: Product Portfolio
118    PTC Inc. : Overall Financials (2015-2017)
119    PTC Inc.: Net Revenue by Business Segments (2015-2017)
120    PTC Inc. : Net Revenue by Product Segments (2015-2017)
121    PTC Inc. : Net Revenue by Region (2015-2017)
122    PTC Inc.: SWOT Analysis
123    SAP: Product Portfolio
124    SAP: Overall Financials (2014-2016)
125    SAP: Net Revenue by Business Segment (2014-2016)
126    SAP: Revenue by Region (2014-2016)
127    SAP: Cloud Subscriptions and Support Revenue by Region (2014-2016)
128    SAP: Cloud and Software Revenue by Region (2014-2016)
129    SAP: SWOT Analysis
130    SAS: Product Portfolio
131    SAS: SWOT Analysis

Market Overview

The Internet of Things (IoT) is bolstering the growth of many industries and is amplifying the value provided by the organizations to their customers. Smart cities, smart manufacturing, connected cars, and location-based intelligence are several ways through which IoT solutions are establishing a connected ecosystem. However, the success and evolution of this ecosystem depends upon the ability of IoT solutions to process data (generated by sensors and other devices) in real time at the network’s edge.

Although, the emergence of cloud technologies has made it possible to develop such an ecosystem, there are challenges associated such as enhanced connectivity requirements and latency issues. Pushing huge amounts of data to the cloud for computation and awaiting analytical results may tremendously increase data transmission costs and simultaneously damage valuable milliseconds required for instantaneous feedback thus damaging real time responsiveness. Billions of devices are generating data with tenacity and making sense this big data will require huge investments in the expansion of computational resources such as analytics, storage and networking software in conjunction with computing platforms. Also, the IoT implementation requires skilled staff complex integration of different devices from different manufacturers having their own set of standards. Hence, organisations utilising traditional approaches to data analytics will need to heavily invest in the expansion of IT resources to leverage the full potential of IoT.

Edge computing or Edge analytics, comes as a solution to help organizations overcome the infrastructure limitations. The technology is an evolution of cloud computing/analytics and an industrial manoeuvre to go one step ahead of democratising data analysis capabilities. It allows data processing right at the point where it is generated (for example: sensors, gateways etc.). Hence, instead of sending data to the cloud for processing and waiting for the analytical results, edge computing pushes the computation part to the edge of a network thus saving on response time as well as data transmission costs.

The global edge analytics market was estimated to be $2.14 billion in 2017, and is expected to reach $13.44 billion by the end of 2025, registering a CAGR of 22.2% during the forecast period, 2018-2025. The expected double-digit growth can be attributed to the rapid proliferation in the number of connected devices and the continuous explosion of data generated by these devices. According to Cisco, a global networking company, there will be nearly 20 billion connected devices by the end of 2020, generating zettabytes of data. An average internet user is expected to generate 1.5 GB of data every day and the video traffic will also reach nearly a petabyte every day. However, there are various factors impeding the market growth and serve as challenges for the stakeholders, such as lack of standardization of network protocols, newly introduced data privacy regulations, integration of devices and identification of edge nodes. Despite the challenges, the edge analytics ecosystem provides the stakeholders with enormous opportunities. The rising amount of capital investments into the IoT ecosystem is a key determinant of growth in the edge analytics market and will further proliferate in the upcoming years. Local governments in countries such as Australia, the U.S., India, South Korea are heavily focussed on improving the operational efficiencies of their businesses and expansion in the organizational infrastructure.

Currently, the global edge analytics market is a blend of a multitude of players from public cloud, ISVs, and networking companies and each company is entering the market from a different perspective. The current market landscape comprises of players such as: Microsoft, IBM, Google, Amazon AWS (Public cloud providers), Cisco, AT&T (networking companies), Oracle (Independent software vendors/ ISVs) and Schneider Electric, GE digital, and Siemens (industrial automation companies) among others

Key Questions Answered in this Report:

•    What are the major market drivers, challenges and opportunities in the global edge analytics solutions market?
•    What was the market value of the leading segments and sub-segments of the global edge analytics solutions market in 2017?
•    How will each segment of the global edge analytics solutions market grow during the forecast period and what will be the revenue generated by each of the segments by the end of 2025?
•    What are the influencing factors that may affect the market share of the key players?
•    How will the industry evolve during the forecast period 2018- 2025?
•    What are the key developments and strategies that are being implemented by the key players to sustain in this market?
•    What are the key application areas of the global edge analytics solutions market? How each of the application areas are employing edge computing?
•    Who are the key players in the global edge analytics solutions market and what are their contributions?
•    What is the scope for expansion by the key players of the global edge analytics solutions market in East and South-East Asia?

Report Description

The global edge analytics market comprises of hardware devices, software and professional services that helps in bringing automated analytical computation at the edge of the network. In general, edge analytics is relatively a new term which aims at collecting and analyzing data at the point where it is generated such as sensors, IoT gateways, network switches and other devices. This automated computation at the edge saves time, improves latency and reduces transmission cost of sending data to the cloud servers. The technology has gained momentum with the rising prevalence of IoT connected devices. Industries, such as manufacturing, transportation, and automobile are the most prominent participants of the IoT revolution and generate tremendous amount of operational data which can be difficult and expensive to manage. By processing data at the edge of a corporate network can empower companies to decide if the data is needed to be sent to the cloud or not. This is particularly useful in environments, such as oil rigs, aircraft, CCTV cameras, connected cars, remote manufacturing where there may not be sufficient time to transmit data to a centralized location and wait for the results. Also, edge analytics could prove to be a boon for the remotely located enterprises where there is a shortage of bandwidth to transmit operational data back and forth and hence, edge can efficiently provide computation and analytics capabilities in remote locations.

An IoT gateway plays a very significant role in the deployment of edge analytics in any enterprise. This device acts as a bridge between connected devices and the centralised cloud server. Rising number of devices is consistently pushing the demand for these devices in solving data management issues. The gateway extracts all the sensor data and applies various rule-based algorithms and sends actionable commands to the connected devices in real time.

Currently, edge analytics solutions are extensively being deployed in retail, manufacturing, energy, smart cities, transportation and logistics vertical segments. Some of the major use cases of edge analytics include: retail customer behaviour analysis, remote monitoring and maintenance for energy operations, fraud detection at financial locations (ATMs), and monitoring of manufacturing & logistics equipment.

The market report is well designed to provide an all-inclusive field of vision about the market in terms of various factors influencing it such as, recent trends, technological advancements, and regulatory environment of the market. The scope of this report is centered upon conducting a detailed study of the solutions allied with the global edge analytics solutions market. The market has been segmented into ‘Mode of Deployment’, ‘Components’, ‘Application’, and ‘Region’. The report presents the reader with an opportunity to unlock comprehensive insights with respect to the market, and helps in forming well informed strategic decisions. The research uncovers some of the substantial parameters that must be taken into consideration before entering into the market.

This research report aims at answering various aspects of the global edge analytics solutions market with the help of the key factors driving the market, threats that can possibly inhibit the overall growth of the market, and the current investment opportunities that are going to shape the future trajectory of the market expansion. The study considers the growth-share matrix model for a comprehensive study of the global edge analytics solutions market and assesses the factors governing the same.

The current edge analytics solutions market landscape consists of leading players from the public cloud segment such as Microsoft, IBM, Google, and Amazon AWS. There are also some of the leading networking companies such as Cisco and AT&T entering the market with edge computing capabilities, followed by a multitude of industrial automation companies such as GE Corporation, Schneider Electric and Siemens, among others.

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Global Edge Analytics Market

Focus on Components, Mode of Deployments (On Premise, Hybrid and Others), Applications (Manufacturing, Transportation and Others), Competitive Landscape, and 20 Country's Analysis - Analysis and Forecast (2018-2025)

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