Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022

機械学習の世界市場予測(~2022年)

◆タイトル:Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022
◆商品コード:MAM-TC5578
◆調査・発行会社:MarketsandMarkets
◆発行日:2017年9月14日
◆ページ数:162
◆レポート形式:PDF / 英語
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【レポートの概要】

MarketsandMarketsが発行した当調査レポートでは、機械学習の世界市場について調査・分析し、エグゼクティブサマリー、市場インサイト、市場概観/市場動向、産業動向、産業別分析、地域別分析、機械学習の世界市場規模及び予測、市場動向、競争状況、関連企業分析などの情報をお届けいたします。

The machine learning market is projected to grow at a CAGR of 44.1% during the forecast periodThe machine learning market is expected to grow from USD 1.41 billion in 2017 to USD 8.81 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1%. The proliferation of large and multidimensional data sets, rising focus towards solving real-time problems from data along with rising demand for sophisticated algorithm platform and tool is driving the adoption of machine learning across the globe.
The major issue in front of most of the organizations while incorporating machine learning in their business process is the lack of skilled employees including analytical talent, and the demand for those who can monitor analytical content is even greater.

Professional service segment is expected to have a larger market share during the forecast period
The service segment in the machine learning market includes professional and managed services. Majority of the companies do not have the expertise to successfully manage infrastructure, and hence, they outsource these services to third-party partners to maintain the level of security and safety. The growth of the professional services segment is mainly governed by the complexity of operations and increasing deployment of machine learning solutions.
Large enterprises segment is expected to have a larger market size during the forecast period
The organization size segment in the machine learning market includes Small and Medium-Sized Enterprises (SMEs) and large enterprises. Emergence in the demand for cloud computing, cloud storage, IoT connected devices, and excessive use of smartphones are some of the prime reasons why large enterprises have turned toward machine learning for processing data. In large enterprises, machine learning has a huge potential for the big data technology in allowing precise decision-making for superior performance.

Asia Pacific (APAC) is expected to witness the highest growth rate during the forecast period
APAC is estimated to grow at the highest CAGR during the forecast period. Factors, such as continual growth in the mobile network, increasing the complexity of business, rise in demand for intelligent business processes, and exponential growth in data generation throughout the industry verticals are driving the machine learning market in the APAC region. The North American region is expected to have the largest market share during the forecast period. The major growth drivers for this region are the large-scale investments in implementing machine learning services due to the growth in demand for processed data. Moreover, recently the region also witnessed the widespread adoption of cloud-based machine learning platform among large enterprises and SMEs across multiple verticals.
In the process of determining and verifying the market size for several segments and subsegments gathered through secondary research, extensive primary interviews were conducted with the key people.
• By Company Type – Tier 1 – 18%, Tier 2 – 48%, and Tier 3 – 34%
• By Designation – C-level – 22%, Director-level – 43%, and Others – 35%
• By Region –North America – 42%, EMEA (Europe, Middle East and Africa) – 32%, and APAC (Asia Pacific) – 26%

The major machine learning vendors are Microsoft Corporation (Washington, US), IBM Corporation (New York, US), SAP SE (Walldorf, Germany), SAS Institute Inc. (North Carolina, US), Google, Inc. (California, US), Amazon Web Services Inc. (Washington, US), Baidu, Inc. (Beijing, China), BigML, Inc. (Oregon, US), Fair Isaac Corporation (FICO) (California, US), Hewlett Packard Enterprise Development LP (HPE) (California, US), Intel Corporation (California, US), KNIME.com AG (Zurich, Switzerland), RapidMiner, Inc. (Massachusetts, US), Angoss Software Corporation (Toronto, Canada), H2O.ai (California, US), Alpine Data (California, US), Domino Data Lab, Inc. (California, US), Dataiku (Paris, France), Luminoso Technologies, Inc. (Massachusetts, US), TrademarkVision (Pennsylvania, US), Fractal Analytics Inc. (New Jersey, US), TIBCO Software Inc. (California, US), Teradata (Ohio, US), Dell Inc. (Texas, US), and Oracle Corporation (California, US).
Research Coverage
The machine learning market has been segmented on the basis of verticals, deployment modes, organization sizes, services, and region. The machine learning is segmented on the basis of verticals into Banking, Financial Services, and Insurance (BFSI), energy and utilities, healthcare and life sciences, retail, telecommunication, manufacturing, government and defense, and others (transportation, agriculture, media and entertainment, and education). The verticals are further segmented on the basis of application areas, applications of machine learning in BFSI includes fraud and risk management, investment prediction, sales and marketing campaign management, customer segmentation, digital assistance, and others (compliance management and credit underwriting). Applications of machine learning in healthcare and life sciences includes disease identification and diagnosis, image analytics, drug discovery/manufacturing, personalized treatment, and others (clinical trial research and epidemic outbreak prediction). Applications of machine learning in retail includes inventory planning, upsell and cross channel marketing, segmentation and targeting, recommendation engines, and others (customer ROI and lifetime value and customization management). Applications of machine learning in telecommunication includes customer analytics, network optimization, network security, and others (digital assistance/contact centers analytics and marketing campaign analytics). Applications of machine learning in government and defense includes threat intelligence, autonomous defense system, and others (sustainability and operational analytics). Applications of machine learning in manufacturing includes predictive maintenance, demand forecasting, revenue estimation, supply chain management, and others (root cause analysis and telematics). Applications of machine learning in energy and utilities includes power/energy usage analytics, seismic data processing, smart grid management, carbon emission, and others (customer specific pricing and renewable energy management).
The services offered in the machine learning market include professional and managed services. The deployment modes in the machine learning market include the cloud and on-premises. The organization sizes are segmented into Small and Medium-Sized Enterprises (SMEs) and large enterprises. Finally, on the basis of regions, the machine learning market is segmented into North America, Europe, APAC, Middle East and Africa (MEA), and Latin America.
The report will help the market leaders and new entrants in the machine learning market in the following ways:
1. The report segments the market into various subsegments, hence it covers the market comprehensively. The report provides the closest approximations of the revenue numbers for the overall market and the subsegments. The market numbers are further split across different verticals and regions.
2. The report helps in understanding the overall growth of the market. It provides information on the key market drivers, restraints, challenges, and opportunities.
3. The report helps in understanding the competitors better and gaining more insights to strengthen the organization’s position in the market. The study also presents the positioning of the key players based on their product offerings and business strategies.

【レポートの目次】

TABLE OF CONTENTS

1 INTRODUCTION 16
1.1 OBJECTIVES OF THE STUDY 16
1.2 MARKET DEFINITION 16
1.3 MARKET SCOPE 17
1.4 YEARS CONSIDERED FOR THE STUDY 18
1.5 CURRENCY 18
1.6 STAKEHOLDERS 19

2 RESEARCH METHODOLOGY 20
2.1 RESEARCH DATA 20
2.1.1 SECONDARY DATA 21
2.1.2 PRIMARY DATA 21
2.1.2.1 Breakdown of primaries 21
2.1.2.2 Key industry insights 22
2.2 MARKET SIZE ESTIMATION 23
2.2.1 BOTTOM-UP APPROACH 24
2.2.2 TOP-DOWN APPROACH 25
2.3 MICROQUADRANT RESEARCH METHODOLOGY 25
2.3.1 VENDOR INCLUSION CRITERIA 26
2.4 RESEARCH ASSUMPTIONS 26
2.5 LIMITATIONS 27

3 EXECUTIVE SUMMARY 28

4 PREMIUM INSIGHTS 36
4.1 ATTRACTIVE MARKET OPPORTUNITIES IN THE MACHINE LEARNING MARKET 36
4.2 MACHINE LEARNING MARKET: TOP 3 VERTICALS 36
4.3 LIFECYCLE ANALYSIS, BY REGION, 2017–2022 37

5 MARKET OVERVIEW AND INDUSTRY TRENDS 39
5.1 INTRODUCTION 39
5.2 MARKET DYNAMICS 39
5.2.1 DRIVERS 40
5.2.1.1 Technological advancements 40
5.2.1.2 Proliferation in data generation 40
5.2.2 RESTRAINTS 40
5.2.2.1 Lack of skilled employees 40
5.2.3 OPPORTUNITIES 41
5.2.3.1 Increasing demand for intelligent business processes 41
5.2.3.2 Increasing adoption in modern applications 41
5.2.4 CHALLENGES 41
5.2.4.1 Sensitive data security 41
5.2.4.2 Ethical implications of the algorithms deployed 42
5.3 INDUSTRY TRENDS 42
5.3.1 MACHINE LEARNING: USE CASES 42
5.3.1.1 Introduction 42
5.3.1.2 USE CASE #1: Deliver analytics solution 42
5.3.1.3 USE CASE #2: Improve cross-selling capabilities 43
5.3.1.4 USE CASE #3: Increase revenue and decrease customer incompetence 43
5.3.1.5 USE CASE #4: Market basket analysis 44
5.4 MACHINE LEARNING PROCESS 44
5.5 REGULATORY IMPLICATIONS 45
5.5.1 INTRODUCTION 45
5.5.2 SARBANES-OXLEY ACT OF 2002 45
5.5.3 GENERAL DATA PROTECTION REGULATION 46
5.5.4 BASEL 46

6 MACHINE LEARNING MARKET ANALYSIS, BY VERTICAL 47
6.1 INTRODUCTION 48
6.1.1 MACHINE LEARNING APPLICATION IN BANKING, FINANCIAL SERVICES, AND INSURANCE 49
6.1.1.1 Fraud and risk management 50
6.1.1.2 Customer segmentation 50
6.1.1.3 Sales and marketing campaign management 50
6.1.1.4 Investment prediction 51
6.1.1.5 Digital assistance 51
6.1.1.6 Others 51
6.1.2 MACHINE LEARNING APPLICATION IN HEALTHCARE AND LIFE SCIENCES 51
6.1.2.1 Disease identification and diagnosis 52
6.1.2.2 Image analytics 53
6.1.2.3 Personalized treatment 53
6.1.2.4 Drug discovery/manufacturing 53
6.1.2.5 Others 53
6.1.3 MACHINE LEARNING APPLICATION IN RETAIL 53
6.1.3.1 Inventory planning 55
6.1.3.2 Recommendation engines 55
6.1.3.3 Upsells and cross channel marketing 55
6.1.3.4 Segmentation and targeting 55
6.1.3.5 Others 55

6.1.4 MACHINE LEARNING APPLICATION IN TELECOMMUNICATION 56
6.1.4.1 Customer analytics 57
6.1.4.2 Network security 57
6.1.4.3 Network optimization 58
6.1.4.4 Others 58
6.1.5 MACHINE LEARNING APPLICATION IN GOVERNMENT AND DEFENSE 58
6.1.5.1 Autonomous defense system 60
6.1.5.2 Threat intelligence 60
6.1.5.3 Others 60
6.1.6 MACHINE LEARNING APPLICATION IN MANUFACTURING 61
6.1.6.1 Predictive maintenance 62
6.1.6.2 Revenue estimation 62
6.1.6.3 Demand forecasting 62
6.1.6.4 Supply chain management 63
6.1.6.5 Others 63
6.1.7 MACHINE LEARNING APPLICATION IN ENERGY AND UTILITIES 63
6.1.7.1 Power/energy usage analytics 65
6.1.7.2 Seismic data processing 65
6.1.7.3 Carbon emission 65
6.1.7.4 Smart grid management 65
6.1.7.5 Others 65
6.1.8 OTHER APPLICATIONS 66

7 MACHINE LEARNING MARKET ANALYSIS, BY DEPLOYMENT MODE 67
7.1 INTRODUCTION 68
7.2 CLOUD 69
7.3 ON-PREMISES 69

8 MACHINE LEARNING MARKET ANALYSIS, BY ORGANIZATION SIZE 70
8.1 INTRODUCTION 71
8.2 LARGE ENTERPRISES 72
8.3 SMALL AND MEDIUM-SIZED ENTERPRISES 72

9 MACHINE LEARNING MARKET ANALYSIS, BY SERVICE 73
9.1 INTRODUCTION 74
9.2 PROFESSIONAL SERVICES 75
9.3 MANAGED SERVICES 75

10 GEOGRAPHIC ANALYSIS 76
10.1 INTRODUCTION 77
10.2 NORTH AMERICA 79
10.2.1 BY VERTICAL 81
10.2.1.1 Machine learning application trends in BFSI 82
10.2.1.2 Machine learning application trends in healthcare and life sciences 83
10.2.1.3 Machine learning application trends in retail 84
10.2.1.4 Machine learning application trends in telecommunication 84
10.2.1.5 Machine learning application trends in government and defense 85
10.2.1.6 Machine learning application trends in manufacturing 85
10.2.1.7 Machine learning application trends in energy and utilities 86
10.2.2 BY ORGANIZATION SIZE 86
10.2.3 BY DEPLOYMENT MODE 86
10.2.4 BY SERVICE 87
10.3 EUROPE 87
10.3.1 BY VERTICAL 88
10.3.1.1 Machine learning application trends in BFSI 89
10.3.1.2 Machine learning application trends in healthcare and life sciences 89
10.3.1.3 Machine learning application trends in retail 90
10.3.1.4 Machine learning application trends in telecommunication 90
10.3.1.5 Machine learning application trends in government and defense 91
10.3.1.6 Machine learning application trends in manufacturing 91
10.3.1.7 Machine learning application trends in energy and utilities 92
10.3.2 BY ORGANIZATION SIZE 92
10.3.3 BY DEPLOYMENT MODE 93
10.3.4 BY SERVICE 93
10.4 ASIA PACIFIC 94
10.4.1 BY VERTICAL 95
10.4.1.1 Machine learning application trends in BFSI 96
10.4.1.2 Machine learning application trends in healthcare and life sciences 96
10.4.1.3 Machine learning application trends in retail 97
10.4.1.4 Machine learning application trends in telecommunication 97
10.4.1.5 Machine learning application trends in government and defense 98
10.4.1.6 Machine learning application trends in manufacturing 98
10.4.1.7 Machine learning application trends in energy and utilities 99
10.4.2 BY ORGANIZATION SIZE 99
10.4.3 BY DEPLOYMENT MODE 100
10.4.4 BY SERVICE 100

10.5 MIDDLE EAST AND AFRICA 101
10.5.1 BY VERTICAL 101
10.5.1.1 Machine learning application trends in BFSI 102
10.5.1.2 Machine learning application trends in healthcare and life sciences 103
10.5.1.3 Machine learning application trends in retail 103
10.5.1.4 Machine learning application trends in telecommunication 104
10.5.1.5 Machine learning application trends in government and defense 104
10.5.1.6 Machine learning application trends in manufacturing 105
10.5.1.7 Machine learning application trends in energy and utilities 105
10.5.2 BY ORGANIZATION SIZE 106
10.5.3 BY DEPLOYMENT MODE 106
10.5.4 BY SERVICE 106
10.6 LATIN AMERICA 107
10.6.1 BY VERTICAL 107
10.6.1.1 Machine learning application trends in BFSI 108
10.6.1.2 Machine learning application trends in healthcare and life sciences 109
10.6.1.3 Machine learning application trends in retail 109
10.6.1.4 Machine learning application trends in telecommunication 110
10.6.1.5 Machine learning application trends in government and defense 110
10.6.1.6 Machine learning application trends in manufacturing 110
10.6.1.7 Machine learning application trends in energy and utilities 111
10.6.2 BY ORGANIZATION SIZE 111
10.6.3 BY DEPLOYMENT MODE 112
10.6.4 BY SERVICE 112

11 COMPETITIVE LANDSCAPE 113
11.1 MARKET RANKING FOR THE MACHINE LEARNING MARKET, 2017 113

12 COMPANY PROFILES 114
(Business Overview, Strength of product portfolio, Business strategy excellence, Recent developments)*

12.1 INTERNATIONAL BUSINESS MACHINES CORPORATION 114
12.2 MICROSOFT CORPORATION 117
12.3 SAP SE 120
12.4 SAS INSTITUTE INC. 124
12.5 AMAZON WEB SERVICES, INC. 127
12.6 BIGML, INC. 130
12.7 GOOGLE INC. 133
12.8 FAIR ISAAC CORPORATION 136
12.9 BAIDU, INC. 139
12.10 HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP 142
12.11 INTEL CORPORATION 145
12.12 H2O.AI 148
*Details on Overview, Strength of product portfolio, Business strategy excellence, Recent developments might not be captured in case of unlisted companies.

13 APPENDIX 151
13.1 DISCUSSION GUIDE 151
13.2 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 156
13.3 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE 158
13.4 AVAILABLE CUSTOMIZATIONS 159
13.5 RELATED REPORTS 159
13.6 AUTHOR DETAILS 160

LIST OF TABLES

TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2014–2016 18
TABLE 2 EVALUATION CRITERIA 25
TABLE 3 GLOBAL MACHINE LEARNING MARKET SIZE AND GROWTH RATE,
2015–2022 (USD MILLION, Y-O-Y %) 29
TABLE 4 MACHINE LEARNING MARKET SIZE, BY VERTICAL, 2015–2022 (USD MILLION) 48
TABLE 5 BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 50
TABLE 6 HEALTHCARE AND LIFE SCIENCES MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 52
TABLE 7 RETAIL MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 54
TABLE 8 TELECOMMUNICATION MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 57
TABLE 9 GOVERNMENT AND DEFENSE MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 59
TABLE 10 MANUFACTURING MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 62
TABLE 11 ENERGY AND UTILITIES MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 64
TABLE 12 MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE,
2015–2022 (USD MILLION) 68
TABLE 13 MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE,
2015–2022 (USD MILLION) 71
TABLE 14 MACHINE LEARNING MARKET SIZE, BY SERVICE, 2015–2022 (USD MILLION) 74
TABLE 15 MACHINE LEARNING MARKET SIZE, BY REGION, 2015–2022 (USD MILLION) 78
TABLE 16 NORTH AMERICA: MACHINE LEARNING MARKET SIZE, BY VERTICAL,
2015–2022 (USD MILLION) 81
TABLE 17 NORTH AMERICA: BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 82
TABLE 18 NORTH AMERICA: HEALTHCARE AND LIFE SCIENCES MARKET SIZE,
BY APPLICATION, 2015–2022 (USD MILLION) 83
TABLE 19 NORTH AMERICA: RETAIL MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 84
TABLE 20 NORTH AMERICA: TELECOMMUNICATION MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 84
TABLE 21 NORTH AMERICA: GOVERNMENT AND DEFENSE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 85
TABLE 22 NORTH AMERICA: MANUFACTURING MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 85
TABLE 23 NORTH AMERICA: ENERGY AND UTILITIES MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 86
TABLE 24 NORTH AMERICA: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 86
TABLE 25 NORTH AMERICA: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015–2022 (USD MILLION) 87
TABLE 26 NORTH AMERICA: MACHINE LEARNING MARKET SIZE, BY SERVICE,
2015–2022 (USD MILLION) 87
TABLE 27 EUROPE: MACHINE LEARNING MARKET SIZE, BY VERTICAL,
2015–2022 (USD MILLION) 88
TABLE 28 EUROPE: BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET SIZE,
BY APPLICATION, 2015–2022 (USD MILLION) 89
TABLE 29 EUROPE: HEALTHCARE AND LIFE SCIENCES MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 90
TABLE 30 EUROPE: RETAIL MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 90
TABLE 31 EUROPE: TELECOMMUNICATION MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 91
TABLE 32 EUROPE: GOVERNMENT AND DEFENSE MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 91
TABLE 33 EUROPE: MANUFACTURING MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 92
TABLE 34 EUROPE: ENERGY AND UTILITIES MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 92
TABLE 35 EUROPE: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE,
2015–2022 (USD MILLION) 93
TABLE 36 EUROPE: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE,
2015–2022 (USD MILLION) 93
TABLE 37 EUROPE: MACHINE LEARNING MARKET SIZE, BY SERVICE,
2015–2022 (USD MILLION) 93
TABLE 38 ASIA PACIFIC: MACHINE LEARNING MARKET SIZE, BY VERTICAL,
2015–2022 (USD MILLION) 95
TABLE 39 ASIA PACIFIC: BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET SIZE,
BY APPLICATION, 2015–2022 (USD MILLION) 96
TABLE 40 ASIA PACIFIC: HEALTHCARE AND LIFE SCIENCES MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 97
TABLE 41 ASIA PACIFIC: MACHINE LEARNING MARKET SIZE IN RETAIL, BY APPLICATION, 2015–2022 (USD MILLION) 97
TABLE 42 ASIA PACIFIC: TELECOMMUNICATION MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 98
TABLE 43 ASIA PACIFIC: GOVERNMENT AND DEFENSE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 98
TABLE 44 ASIA PACIFIC: MANUFACTURING MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 99
TABLE 45 ASIA PACIFIC: ENERGY AND UTILITIES MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 99
TABLE 46 ASIA PACIFIC: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE,
2015–2022 (USD MILLION) 100
TABLE 47 ASIA PACIFIC: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE,
2015–2022 (USD MILLION) 100
TABLE 48 ASIA PACIFIC: MACHINE LEARNING MARKET SIZE, BY SERVICE,
2015–2022 (USD MILLION) 100
TABLE 49 MIDDLE EAST AND AFRICA: MACHINE LEARNING MARKET SIZE, BY VERTICAL, 2015–2022 (USD MILLION) 102
TABLE 50 MIDDLE EAST AND AFRICA: BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 102
TABLE 51 MIDDLE EAST AND AFRICA: HEALTHCARE AND LIFE SCIENCES MARKET SIZE,
BY APPLICATION, 2015–2022 (USD MILLION) 103
TABLE 52 MIDDLE EAST AND AFRICA: RETAIL MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 103
TABLE 53 MIDDLE EAST AND AFRICA: TELECOMMUNICATION MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 104
TABLE 54 MIDDLE EAST AND AFRICA: GOVERNMENT AND DEFENSE MARKET SIZE,
BY APPLICATION, 2015–2022 (USD MILLION) 104
TABLE 55 MIDDLE EAST AND AFRICA: MANUFACTURING MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 105
TABLE 56 MIDDLE EAST AND AFRICA: ENERGY AND UTILITIES MARKET SIZE,
BY APPLICATION, 2015–2022 (USD MILLION) 105
TABLE 57 MIDDLE EAST AND AFRICA: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 106
TABLE 58 MIDDLE EAST AND AFRICA: MACHINE LEARNING MARKET SIZE,
BY DEPLOYMENT MODE, 2015–2022 (USD MILLION) 106
TABLE 59 MIDDLE EAST AND AFRICA: MACHINE LEARNING MARKET SIZE, BY SERVICE, 2015–2022 (USD MILLION) 106
TABLE 60 LATIN AMERICA: MACHINE LEARNING MARKET SIZE, BY VERTICAL,
2015–2022 (USD MILLION) 108
TABLE 61 LATIN AMERICA: BANKING, FINANCIAL SERVICES, AND INSURANCE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 108
TABLE 62 LATIN AMERICA: HEALTHCARE AND LIFE SCIENCES MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 109
TABLE 63 LATIN AMERICA: RETAIL MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 109
TABLE 64 LATIN AMERICA: TELECOMMUNICATION MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 110
TABLE 65 LATIN AMERICA: GOVERNMENT AND DEFENSE MARKET SIZE, BY APPLICATION, 2015–2022 (USD MILLION) 110
TABLE 66 LATIN AMERICA: MANUFACTURING MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 111
TABLE 67 LATIN AMERICA: ENERGY AND UTILITIES MARKET SIZE, BY APPLICATION,
2015–2022 (USD MILLION) 111
TABLE 68 LATIN AMERICA: MACHINE LEARNING MARKET SIZE, BY ORGANIZATION SIZE, 2015–2022 (USD MILLION) 112
TABLE 69 LATIN AMERICA: MACHINE LEARNING MARKET SIZE, BY DEPLOYMENT MODE, 2015–2022 (USD MILLION) 112
TABLE 70 LATIN AMERICA: MACHINE LEARNING MARKET SIZE, BY SERVICE,
2015–2022 (USD MILLION) 112
TABLE 71 MARKET RANKING FOR THE MACHINE LEARNING MARKET, 2017 113


LIST OF FIGURES

FIGURE 1 GLOBAL MACHINE LEARNING MARKET: MARKET SEGMENTATION 17
FIGURE 2 GLOBAL MACHINE LEARNING MARKET: RESEARCH DESIGN 20
FIGURE 3 BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY SIZE, DESIGNATION,
AND REGION 21
FIGURE 4 DATA TRIANGULATION 23
FIGURE 5 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH 24
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH 25
FIGURE 7 MACHINE LEARNING MARKET SNAPSHOT (2017), BY VERTICAL 29
FIGURE 8 MACHINE LEARNING MARKET SNAPSHOT (2017), BY BANKING,
FINANCIAL SERVICES, AND INSURANCE APPLICATION 30
FIGURE 9 MACHINE LEARNING MARKET SNAPSHOT (2017), BY HEALTHCARE
AND LIFE SCIENCES APPLICATION 30
FIGURE 10 MACHINE LEARNING MARKET SNAPSHOT (2017), BY RETAIL APPLICATION 31
FIGURE 11 MACHINE LEARNING MARKET SNAPSHOT (2017), BY TELECOMMUNICATION APPLICATION 31
FIGURE 12 MACHINE LEARNING MARKET SNAPSHOT (2017), BY GOVERNMENT
AND DEFENSE APPLICATION 32
FIGURE 13 MACHINE LEARNING MARKET SNAPSHOT (2017), BY MANUFACTURING APPLICATION 32
FIGURE 14 MACHINE LEARNING MARKET SNAPSHOT (2017), BY ENERGY AND UTILITIES APPLICATION 33
FIGURE 15 MACHINE LEARNING MARKET SNAPSHOT (2017), BY SERVICE 33
FIGURE 16 MACHINE LEARNING MARKET SNAPSHOT (2017), BY ORGANIZATION SIZE 34
FIGURE 17 MACHINE LEARNING MARKET SNAPSHOT (2017), BY DEPLOYMENT MODE 34
FIGURE 18 MACHINE LEARNING MARKET SNAPSHOT, BY REGION 35
FIGURE 19 PROLIFERATION IN DATA GENERATION IS ONE OF THE MAJOR FACTORS DRIVING THE OVERALL GROWTH OF THE MACHINE LEARNING MARKET DURING THE FORECAST PERIOD 36
FIGURE 20 HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED TO GROW
AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 36
FIGURE 21 ASIA PACIFIC IS EXPECTED TO EXHIBIT THE HIGHEST GROWTH POTENTIAL DURING THE FORECAST PERIOD 37
FIGURE 22 MARKET INVESTMENT SCENARIO: ASIA PACIFIC IS EXPECTED TO BE
THE BEST MARKET FOR INVESTMENT IN THE NEXT 5 YEARS 38
FIGURE 23 MACHINE LEARNING MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES,
AND CHALLENGES 39
FIGURE 24 MACHINE LEARNING PROCESS 45
FIGURE 25 HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED TO EXHIBIT THE HIGHEST CAGR DURING THE FORECAST PERIOD 48
FIGURE 26 FRAUD AND RISK MANAGEMENT APPLICATION IS EXPECTED TO HOLD
THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 49
FIGURE 27 DISEASE IDENTIFICATION AND DIAGNOSIS APPLICATION IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 52
FIGURE 28 INVENTORY PLANNING APPLICATION IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 54
FIGURE 29 CUSTOMER ANALYTICS APPLICATION IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 56
FIGURE 30 THREAT INTELLIGENCE APPLICATION IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 59
FIGURE 31 PREDICTIVE MAINTENANCE APPLICATION IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 61
FIGURE 32 POWER/ENERGY USAGE ANALYTICS APPLICATION IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING THE FORECAST PERIOD 64
FIGURE 33 CLOUD DEPLOYMENT MODE IS EXPECTED TO EXHIBIT A HIGHER CAGR DURING THE FORECAST PERIOD 68
FIGURE 34 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT IS EXPECTED TO EXHIBIT
A HIGHER CAGR DURING THE FORECAST PERIOD 71
FIGURE 35 MANAGED SERVICES SEGMENT IS EXPECTED TO EXHIBIT A HIGHER CAGR DURING THE FORECAST PERIOD 74
FIGURE 36 NORTH AMERICA IS EXPECTED TO HOLD THE LARGEST MARKET SIZE DURING
THE FORECAST PERIOD 77
FIGURE 37 ASIA PACIFIC IS EXPECTED TO HAVE THE HIGHEST GROWTH RATE IN
THE MACHINE LEARNING MARKET DURING THE FORECAST PERIOD 78
FIGURE 38 NORTH AMERICA: MARKET SNAPSHOT 80
FIGURE 39 NORTH AMERICA: HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED
TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 81
FIGURE 40 MAJOR FINTECH COMPANIES IN NORTH AMERICA USING MACHINE LEARNING 83
FIGURE 41 EUROPE: HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED TO
GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 88
FIGURE 42 ASIA PACIFIC: MARKET SNAPSHOT 94
FIGURE 43 ASIA PACIFIC: HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED
TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 95
FIGURE 44 MIDDLE EAST AND AFRICA: HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 101
FIGURE 45 LATIN AMERICA: HEALTHCARE AND LIFE SCIENCES VERTICAL IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 107
FIGURE 46 INTERNATIONAL BUSINESS MACHINES CORPORATION: COMPANY SNAPSHOT 114
FIGURE 47 MICROSOFT CORPORATION: COMPANY SNAPSHOT 117
FIGURE 48 SAP SE: COMPANY SNAPSHOT 120
FIGURE 49 AMAZON WEB SERVICES, INC.: COMPANY SNAPSHOT 127
FIGURE 50 GOOGLE INC.: COMPANY SNAPSHOT 133
FIGURE 51 FAIR ISAAC CORPORATION: COMPANY SNAPSHOT 136
FIGURE 52 BAIDU, INC.: COMPANY SNAPSHOT 139
FIGURE 53 HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP: COMPANY SNAPSHOT 142
FIGURE 54 INTEL CORPORATION: COMPANY SNAPSHOT 145
FIGURE 55 MARKETS AND MARKETS KNOWLEDGE STORE: SNAPSHOT 1 156
FIGURE 56 MARKETS AND MARKETS KNOWLEDGE STORE: SNAPSHOT 2 157


【レポートのキーワード】

機械学習

★調査レポート[機械学習の世界市場予測(~2022年)] ( Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022 / MAM-TC5578) 販売に関する免責事項
[機械学習の世界市場予測(~2022年)] ( Machine Learning Market by Vertical (BFSI, Healthcare and Life Sciences, Retail, Telecommunication, Government and Defense, Manufacturing, Energy and Utilities), Deployment Mode, Service, Organization Size, and Region - Global Forecast to 2022 / MAM-TC5578) についてEメールでお問い合わせ


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