世界各国のリアルタイムなデータ・インテリジェンスで皆様をお手伝い

サービスとしてのデータウェアハウス(DWaaS)市場:用途毎(顧客解析、資産管理、詐欺検出・脅威管理)、利用毎、産業毎、採用モデル毎、タイプ毎(EDWaaS、ODS)、企業規模毎 - 2023年までの世界市場予測

Data Warehouse as a Service (DWaaS) Market by Application (Customer Analytics, Asset Management, Fraud Detection & Threat Management), Usage, Industry Vertical, Deployment Model, Type (EDWaaS & ODS) & Organization Size - Global Forecast to 2023

 

出版社 出版年月電子版価格 ページ数図表数
MarketsandMarkets
マーケッツアンドマーケッツ
2019年1月US$5,650
シングルユーザライセンス
167 120

サマリー

幅広い市場に関する調査レポートを出版しているマーケッツアンドマーケッツ(MarketsandMarkets)のサービスとしてのデータウェアハウス(DWaaS)市場に関する調査レポートです。

Secured management of business data and applications are some of the key factors driving the growth of the market

MarketsandMarkets estimates the global data warehouse as a service market to grow from USD 1.2 billion in 2018 to USD 3.4 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 23.8% during the forecast period. The key factors driving the data warehouse as a service market include rising adoption of private cloud coupled with increasing use of column-oriented data warehouse to perform advanced analytics. However, lack of skilled personnel and reluctance to shift from traditional ETL tools to cloud are hindering the growth of the market.

Cloud offering the major cost-effective environment for analytics is a factor driving the adoption of data storage

Organizations have been using data analytics to build strategies for maximizing profits. In addition to increased accessibility and utility, the management of data stored over the cloud requires less expenditure and the user can focus more on the product and staff. The small and medium-sized organizations are focusing on its adoption to compete with the large organizations and gain more access to the data with minimum investments.

Digital transformation to build a digital ecosystem to enable seamless integration among data delivering greater business value is accelerating the growth of hybrid DWaaS

Although the cloud-based services are cost effective, their initial value lies in empowering business transformation. Hybrid deployment has witnessed increased adoption owing to its flexibility to customize solutions as per an organization’s dynamic requirements, and data security and privacy. Also, increased user and resource mobility, ongoing migrations of applications over the cloud, and the emergence of more sophisticated threats are leading organizations to adopt hybrid cloud solutions.

Growing cloud adoption coupled with expanding services by vendors such as Google and Amazon to drive APAC (Asia Pacific) data warehouse as a service market during the forecast period

China is one of the developing economies, which have undergone a tremendous transformation in the areas of manufacturing, telecommunication, and IT. The country has always set a benchmark for providing affordable solutions, which are exported to various parts of the world. Being the most affordable market with a reliable workforce, the data warehouse as a service vendors have shown their interest in establishing the market in this country. Other countries, such as Japan, Singapore, and India, are leading in such adoption, as the vendors are expanding their presence into this region by entering into partnerships with different technology players or distributors to develop their sales channels.

In-depth interviews were conducted with the Chief Executive Officers (CEOs), marketing directors, other innovation and technology directors, and executives from various key organizations operating in the data warehouse as a service market.

 By Company: Tier 1: 20%, Tier 2: 55%, and Tier 3: 25%
 By Designation: C-Level: 50%, Director Level: 25%, and Others: 25%
 By Region: North America: 60%, Europe: 20%, APAC: 10%, and RoW: 10%

The major vendors offering data warehouse as a service globally include IBM (US), AWS (US), Google (US), Microsoft (US), Snowflake (US), Teradata (US), SAP (Germany), Micro Focus (UK), Hortonworks (US), Cloudera (US), Actian (US), 1010data (US), Pivotal Software (US), Solver (US), Yellowbrick (US), Panoply (US), MarkLogic (US), MemSQL (US), Netavis (Austria), LUX Fund Technology & Solutions (US), Transwarp Technology (China), Accur8 Software (US), Atscale (US), and Veeva (US). The study includes in-depth competitive analysis of these key players in the data warehouse as a service market with their company profiles, recent developments, and key market strategies.

Research coverage

The data warehouse as a service market revenue is primarily classified into revenues from solutions, tools, and platforms. The revenue is associated with software and platform offerings associated with support and maintenance, training and education, and consulting services. Other segmentation comprises type, usage, application, deployment model, organization size, industry vertical, and region.

Key benefits of the report

The report would help the market leaders/new entrants in this market with the information on the closest approximations of the revenue numbers for the overall data warehouse as a service market and the subsegments. This report would help stakeholders understand the competitive landscape and gain insights to better position their businesses and plan suitable go-to-market strategies. The report also helps stakeholders understand the pulse of the market and provides them with the information on the key market drivers, restraints, challenges, and opportunities.
 



目次

1 INTRODUCTION 18
1.1 OBJECTIVES OF THE STUDY 18
1.2 MARKET DEFINITION 18
1.3 MARKET SCOPE 19
1.3.1 MARKET COVERED 19
1.3.2 REGIONS COVERED 20
1.4 YEARS CONSIDERED FOR THE STUDY 20
1.5 CURRENCY CONSIDERED 21
1.6 STAKEHOLDERS 21
2 RESEARCH METHODOLOGY 22
2.1 RESEARCH DATA 22
2.1.1 SECONDARY DATA 23
2.1.1.1 Key data from secondary sources 23
2.1.2 PRIMARY DATA 24
2.1.2.1 Breakup of primaries 24
2.1.2.2 Key industry insights 25
2.2 MARKET BREAKUP AND DATA TRIANGULATION 25
2.3 MARKET SIZE ESTIMATION 26
2.3.1 BOTTOM-UP APPROACH 26
2.3.2 TOP-DOWN APPROACH 27
2.4 MARKET FORECAST 28
2.5 RESEARCH ASSUMPTIONS AND LIMITATIONS 29
2.6 LIMITATIONS 29
3 EXECUTIVE SUMMARY 30
4 PREMIUM INSIGHTS 35
4.1 ATTRACTIVE OPPORTUNITIES IN THE DATA WAREHOUSE AS A SERVICE MARKET 35
4.2 DATA WAREHOUSE AS A SERVICE MARKET: MARKET SHARE, BY REGION 36
4.3 DATA WAREHOUSE AS A SERVICE MARKET, DEPLOYMENT MODEL 37
4.4 DATA WAREHOUSE AS A SERVICE MARKET IN EUROPE:
TOP 3 APPLICATIONS AND COUNTRY 37
5 MARKET OVERVIEW AND INDUSTRY TRENDS 38
5.1 INTRODUCTION 38
5.2 MARKET DYNAMICS 38
5.2.1 DRIVERS 39
5.2.1.1 Growing adoption of private cloud 39
5.2.1.2 Increasing demand for column-oriented data warehouse solutions to perform advanced analytics 39
5.2.1.3 Rapid growth in data volumes 39
5.2.1.4 Increasing need to comply with regulations and standards 39
5.2.2 RESTRAINTS 40
5.2.2.1 Reluctance to shift from traditional ETL tools to cloud 40
5.2.3 OPPORTUNITIES 40
5.2.3.1 Growing application of AI in data warehouse 40
5.2.3.2 Growing demand from SMEs 40
5.2.4 CHALLENGES 41
5.2.4.1 Lack of skilled personnel and cloud data security 41
5.3 INDUSTRY TRENDS 41
5.3.1 DATA WAREHOUSE AS A SERVICE MARKET: USE CASES 41
5.3.1.1 USE CASE 1: Increased speed of operation with cost reduction 41
5.3.1.2 USE CASE 2: Optimize frauds related to tax reductions 42
5.3.1.3 USE CASE 3: Enhancing the speed of data transfer and automation over the cloud 42
5.3.2 REGULATIONS 43
5.3.2.1 HIPAA of 1996 43
5.3.2.2 EU GDPR 43
5.3.2.3 CSCC 43
5.3.2.4 SOX Act of 2002 44
5.3.3 EVOLUTION 44
6 DATA WAREHOUSE AS A SERVICE MARKET, BY TYPE 45
6.1 INTRODUCTION 46
6.2 ENTERPRISE DATA WAREHOUSE AS A SERVICE 47
6.2.1 ORGANIZATIONAL NEED TO CONSOLIDATE AND OPERATE DATA AND PROVIDE ACCESS TO THE RIGHT USERS 47
6.3 OPERATIONAL DATA STORAGE 48
6.3.1 BENEFIT OF COMPLEMENTING AN ORGANIZATION’S CURRENT AND FUTURE REQUIREMENTS 48
7 DATA WAREHOUSE AS A SERVICE MARKET, BY USAGE 49
7.1 INTRODUCTION 50
7.2 ANALYTICS 51
7.2.1 INCREASING DEMAND FOR HIGHER DATA QUALITY AND THE NEED TO DELIVER SOUND DECISION-MAKING SKILLS 51
7.3 REPORTING 51
7.3.1 THE INCREASING NEED TO GENERATE REPORTS BASED ON ONLINE AND OFFLINE DATA 51

7.4 DATA MINING 52
7.4.1 DEMAND FOR PROCESSES TO OPTIMIZE OUTCOMES, AUTOMATE PROCESSES, AND EXTRACT IMPACTFUL INSIGHTS 52
8 DATA WAREHOUSE AS A SERVICE MARKET, BY DEPLOYMENT MODEL 54
8.1 INTRODUCTION 55
8.2 PUBLIC CLOUD 56
8.2.1 SCALABILITY, FLEXIBILITY, AND RELIABILITY BENEFITS 56
8.3 PRIVATE CLOUD 56
8.3.1 NEED FOR HIGHLY SECURE OPERATING ENVIRONMENT 56
8.4 HYBRID CLOUD 57
8.4.1 VARYING BUSINESS DEMANDS TO ADDRESS THREATS AND MANAGE COMPLEX WORKLOADS 57
9 DATA WAREHOUSE AS A SERVICE MARKET, BY ORGANIZATION SIZE 59
9.1 INTRODUCTION 60
9.2 SMALL AND MEDIUM-SIZED ENTERPRISES 61
9.2.1 NEED FOR COST-EFFECTIVE SOLUTIONS TO MEET BUDGETS AND LEAD TO BUSINESS GROWTH 61
9.3 LARGE ENTERPRISES 62
9.3.1 NEED TO MANAGE HUGE HEAPS OF ACCUMULATED DATA OVER A PUBLIC OR PRIVATE CLOUD 62
10 DATA WAREHOUSE AS A SERVICE MARKET, BY APPLICATION 63
10.1 INTRODUCTION 64
10.2 CUSTOMER ANALYTICS 65
10.2.1 NEED FOR COMPANIES TO REDUCE THEIR BUSINESS EXPENDITURE 65
10.3 RISK AND COMPLIANCE MANAGEMENT 66
10.3.1 NEED TO ENSURE FASTER TIME-TO-ANALYSIS IN RISK AND COMPLIANCE DATA 66
10.4 ASSET MANAGEMENT 67
10.4.1 INCREASING NEED FOR AUTOMATION IN MULTIPLE INDUSTRIES 67
10.5 SUPPLY CHAIN MANAGEMENT 68
10.5.1 NEED FOR DEMAND FORECASTING FOR BETTER INVENTORY, PRODUCTION, AND DISTRIBUTION MANAGEMENT 68
10.6 FRAUD DETECTION AND THREAT MANAGEMENT 69
10.6.1 INCREASING NEED TO DETECT AND IDENTIFY FRAUDULENT ACTIVITIES IN CUSTOMER ACCOUNTS 69
10.7 OTHERS 70

11 DATA WAREHOUSE AS A SERVICE MARKET, BY INDUSTRY VERTICAL 71
11.1 INTRODUCTION 72
11.2 BANKING, FINANCIAL SERVICES, AND INSURANCE 73
11.2.1 MASSIVE PARALLEL PROCESSING WITH ADVANCED CLOUD DATA WAREHOUSE TO ENABLE ORGANIZATIONS WITH BETTER ACTIVITY MONITORING 73
11.3 RETAIL AND ECOMMERCE 74
11.3.1 THE NEED TO UNDERSTAND REAL-TIME CUSTOMERS’ BEHAVIOR FOR IMPROVING DECISION-MAKING SKILLS 74
11.4 HEALTHCARE AND PHARMACEUTICALS 75
11.4.1 LEVERAGING TECHNOLOGIES TO MANAGE PATIENT-RELATED CRITICAL INFORMATION 75
11.5 TELECOMMUNICATIONS AND IT 76
11.5.1 DATA MONETIZATION COMPELS HIGH-VOLUME DATA BUSINESSES TO BENEFIT FROM USING CLOUD-BASED SOLUTIONS 76
11.6 GOVERNMENT AND PUBLIC SECTOR 77
11.6.1 THE NEED TO SEARCH AND ANALYZE REAL-TIME TERRORIST DATA AND THREATS 77
11.7 MANUFACTURING 78
11.7.1 GRADUAL USE OF CLOUD-BASED TECHNOLOGIES TO ANALYZE CUSTOMERS’ BEHAVIOR 78
11.8 MEDIA AND ENTERTAINMENT 79
11.8.1 INCREASING NUMBER OF MOBILE APPS AND CUSTOMER BASE DEMAND FASTER DATA PROCESSING SOLUTIONS 79
11.9 TRAVEL AND HOSPITALITY 79
11.9.1 THE NEED TO MONITOR AND MITIGATE THE IMPACT OF TRAFFIC ON COMMUTERS 79
11.10 OTHERS 80
12 DATA WAREHOUSE AS A SERVICE MARKET, BY REGION 82
12.1 INTRODUCTION 83
12.2 NORTH AMERICA 84
12.2.1 UNITED STATES 88
12.2.1.1 The presence of leading global players and early adoption of cloud solutions 88
12.2.2 CANADA 88
12.2.2.1 Growing investments in data management solutions for better decision-making 88
12.3 EUROPE 89
12.3.1 UNITED KINGDOM 92
12.3.1.1 Strategic partnerships and supportive government mandates to drive business models in data-driven industries 92
12.3.2 GERMANY 92
12.3.2.1 Numerous industry sectors, such as pharmaceuticals and healthcare, to adopt IoT and big data 92
12.3.3 FRANCE 92
12.3.3.1 Significant investments in AI and big data 92
12.3.4 REST OF EUROPE 92
12.4 ASIA PACIFIC 93
12.4.1 JAPAN 97
12.4.1.1 Increasing investments in new technologies and rising demand to deal with huge data volumes 97
12.4.2 CHINA 97
12.4.2.1 Increasing digitalization and regulatory mandates at the forefront 97
12.4.3 SINGAPORE 97
12.4.3.1 Strategic partnerships and acquisitions by companies 97
12.4.4 INDIA 98
12.4.4.1 Increasing number of collaborations between global and local players to offer best-in-class customer experience 98
12.4.5 REST OF ASIA PACIFIC 98
12.5 MIDDLE EAST AND AFRICA 99
12.5.1 MIDDLE EAST 102
12.5.1.1 UAE, Qatar, and Saudi Arabia to witness higher adoption of cloud-based IoT solutions 102
12.5.2 AFRICA 102
12.5.2.1 Supportive government policies 102
12.6 LATIN AMERICA 103
12.6.1 BRAZIL 106
12.6.1.1 Growth in smart cities and IoT technologies to generate large volumes of data 106
12.6.2 MEXICO 106
12.6.2.1 The trend adopting data management solutions on the rise 106
12.6.3 REST OF LATIN AMERICA 106
13 COMPETITIVE LANDSCAPE 107
13.1 OVERVIEW 107
13.2 COMPETITIVE SCENARIO 109
13.2.1 NEW PRODUCT LAUNCHES AND PRODUCT UPGRADATIONS 109
13.2.2 PARTNERSHIPS AND COLLABORATIONS 110
13.2.3 BUSINESS EXPANSIONS 111
13.3 DWAAS MARKET: PROMINENT PLAYERS 112

14 COMPANY PROFILES 113
(Business Overview, Products/ Services/ Solutions/ Tools/ Platforms Offered, Recent Developments, SWOT Analysis, and MnM View)*
14.1 AWS 113
14.2 IBM 116
14.3 MICROSOFT 119
14.4 GOOGLE 122
14.5 ORACLE 124
14.6 SAP 126
14.7 MICRO FOCUS 129
14.8 1010DATA 132
14.9 CLOUDERA 134
14.10 SNOWFLAKE 136
14.11 PIVOTAL 138
14.12 YELLOWBRICK 140
14.13 HORTONWORKS 141
14.14 TERADATA CORPORATION 143
14.15 VEEVA SYSTEMS 145
14.16 ACCUR8 SOFTWARE 147
14.17 ACTIAN 148
14.18 ATSCALE 149
14.19 LUX 150
14.20 MARKLOGIC 151
14.21 MEMSQL 152
14.22 NETAVIS SOFTWARE 153
14.23 PANOPLY 154
14.24 SOLVER 155
14.25 TRANSWARP 157
*Details on Business Overview, Products/ Services/ Solutions/ Tools/ Platforms Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
15 APPENDIX 158
15.1 INSIGHTS FROM INDUSTRY EXPERTS 158
15.2 DISCUSSION GUIDE 159
15.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 163
15.4 AVAILABLE CUSTOMIZATION 165
15.5 RELATED REPORTS 165
15.6 AUTHOR DETAILS 166

 

LIST OF TABLES

TABLE 1 UNITED STATES DOLLAR EXCHANGE RATE, 2014–2017 21
TABLE 2 FACTOR ANALYSIS 28
TABLE 3 DATA WAREHOUSE AS A SERVICE MARKET SIZE AND GROWTH RATE,
2016–2023 (USD MILLION, Y-O-Y %) 31
TABLE 4 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY TYPE,
2016–2023 (USD MILLION) 46
TABLE 5 ENTERPRISE DATA WAREHOUSE AS A SERVICE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 47
TABLE 6 OPERATIONAL DATA STORAGE: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 48
TABLE 7 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY USAGE,
2016–2023 (USD MILLION) 50
TABLE 8 ANALYTICS: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 51
TABLE 9 REPORTING: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 52
TABLE 10 DATA MINING: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 53
TABLE 11 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY DEPLOYMENT MODEL,
2016–2023 (USD MILLION) 55
TABLE 12 PUBLIC CLOUD: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 56
TABLE 13 PRIVATE CLOUD: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 57
TABLE 14 HYBRID CLOUD: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 57
TABLE 15 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 60
TABLE 16 SMALL AND MEDIUM-SIZED ENTERPRISES: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 61
TABLE 17 LARGE ENTERPRISES: DATA WAREHOUSE-AS-SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 62
TABLE 18 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY APPLICATION,
2016–2023 (USD MILLION) 64
TABLE 19 CUSTOMER ANALYTICS: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 65
TABLE 20 RISK AND COMPLIANCE MANAGEMENT: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 66
TABLE 21 ASSET MANAGEMENT: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 67
TABLE 22 SUPPLY CHAIN MANAGEMENT: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 68
TABLE 23 FRAUD DETECTION AND THREAT MANAGEMENT: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 69
TABLE 24 OTHERS: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 70
TABLE 25 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY INDUSTRY VERTICAL,
2016–2023 (USD MILLION) 72
TABLE 26 BANKING, FINANCIAL SERVICES, AND INSURANCE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 73
TABLE 27 RETAIL AND ECOMMERCE: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 74
TABLE 28 HEALTHCARE AND PHARMACEUTICALS: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 75
TABLE 29 TELECOMMUNICATIONS AND IT: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 76
TABLE 30 GOVERNMENT AND PUBLIC SECTOR: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 77
TABLE 31 MANUFACTURING: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 78
TABLE 32 MEDIA AND ENTERTAINMENT: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 79
TABLE 33 TRAVEL AND HOSPITALITY: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 80
TABLE 34 OTHERS: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 81
TABLE 35 DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 83
TABLE 36 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY APPLICATION, 2016–2023 (USD MILLION) 85
TABLE 37 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY TYPE, 2016–2023 (USD MILLION) 86
TABLE 38 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY USAGE, 2016–2023 (USD MILLION) 86
TABLE 39 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 86
TABLE 40 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 87
TABLE 41 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 87
TABLE 42 NORTH AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY COUNTRY, 2016–2023 (USD MILLION) 88
TABLE 43 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY APPLICATION,
2016–2023 (USD MILLION) 89
TABLE 44 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY TYPE,
2016–2023 (USD MILLION) 89
TABLE 45 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY USAGE,
2016–2023 (USD MILLION) 90
TABLE 46 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 90
TABLE 47 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 90
TABLE 48 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 91
TABLE 49 EUROPE: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 91
TABLE 50 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY APPLICATION, 2016–2023 (USD MILLION) 94
TABLE 51 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY TYPE,
2016–2023 (USD MILLION) 95
TABLE 52 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY USAGE,
2016–2023 (USD MILLION) 95
TABLE 53 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 95
TABLE 54 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 96
TABLE 55 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 96
TABLE 56 ASIA PACIFIC: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY COUNTRY, 2016–2023 (USD MILLION) 97
TABLE 57 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY APPLICATION, 2016–2023 (USD MILLION) 99
TABLE 58 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY TYPE, 2016–2023 (USD MILLION) 100
TABLE 59 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY USAGE, 2016–2023 (USD MILLION) 100
TABLE 60 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 100
TABLE 61 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 101
TABLE 62 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 101
TABLE 63 MIDDLE EAST AND AFRICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 102
TABLE 64 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY APPLICATION, 2016–2023 (USD MILLION) 103
TABLE 65 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY TYPE,
2016–2023 (USD MILLION) 103
TABLE 66 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY USAGE, 2016–2023 (USD MILLION) 104
TABLE 67 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 104
TABLE 68 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 104
TABLE 69 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 105
TABLE 70 LATIN AMERICA: DATA WAREHOUSE AS A SERVICE MARKET SIZE,
BY COUNTRY, 2016–2023 (USD MILLION) 105
TABLE 71 NEW PRODUCT LAUNCHES AND PRODUCT ENHANCEMENTS, 2018 109
TABLE 72 PARTNERSHIPS AND COLLABORATIONS, 2018 110
TABLE 73 BUSINESS EXPANSIONS, 2016–2018 111
TABLE 74 KEY PLAYERS IN THE DATA WAREHOUSE AS A SERVICE MARKET 112

 

LIST OF FIGURES

FIGURE 1 DATA WAREHOUSE AS A SERVICE MARKET: RESEARCH DESIGN 22
FIGURE 2 BREAKUP OF PRIMARY PARTICIPANTS’ PROFILES: BY COMPANY, DESIGNATION, AND REGION 24
FIGURE 3 DATA WAREHOUSE AS A SERVICE MARKET: BOTTOM-UP APPROACH 26
FIGURE 4 DATA WAREHOUSE AS A SERVICE MARKET: TOP-DOWN APPROACH 27
FIGURE 5 DATA WAREHOUSE AS A SERVICE MARKET SNAPSHOT, BY REGION, 2018 VS. 2023 31
FIGURE 6 DATA WAREHOUSE AS A SERVICE MARKET SNAPSHOT, BY TYPE, 2018 VS. 2023 32
FIGURE 7 DATA WAREHOUSE AS A SERVICE MARKET SNAPSHOT, BY DEPLOYMENT MODEL, 2018 VS. 2023 32
FIGURE 8 DATA WAREHOUSE AS A SERVICE MARKET SNAPSHOT, BY USAGE, 2018 VS. 2023 33
FIGURE 9 DATA WAREHOUSE AS A SERVICE MARKET SNAPSHOT, BY APPLICATION,
2018 VS. 2023 33
FIGURE 10 DATA WAREHOUSE AS A SERVICE MARKET SNAPSHOT, BY INDUSTRY VERTICAL, 2018–2023 34
FIGURE 11 RAPID GROWTH IN DATA VOLUMES TO DRIVE THE MARKET 35
FIGURE 12 NORTH AMERICA TO ACCOUNT FOR THE HIGHEST MARKET SHARE IN 2018 36
FIGURE 13 PRIVATE CLOUD SEGMENT TO DOMINATE THE MARKET IN 2018 37
FIGURE 14 CUSTOMER ANALYTICS APPLICATION AND GERMANY TO HOLD THE HIGHEST MARKET SHARES IN 2018 37
FIGURE 15 DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES: DATA WAREHOUSE AS A SERVICE MARKET 38
FIGURE 16 DATA WAREHOUSE AS A SERVICE EVOLUTION 44
FIGURE 17 OPERATIONAL DATA STORE SEGMENT TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 46
FIGURE 18 ANALYTICS SEGMENT TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 50
FIGURE 19 ON-PREMISES DEPLOYMENT MODEL TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 55
FIGURE 20 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 60
FIGURE 21 SUPPLY CHAIN MANAGEMENT APPLICATION TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 64
FIGURE 22 HEALTHCARE AND PHARMACEUTICALS INDUSTRY VERTICAL TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 72
FIGURE 23 ASIA PACIFIC TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 83
FIGURE 24 NORTH AMERICA: MARKET SNAPSHOT 85
FIGURE 25 ASIA PACIFIC: MARKET SNAPSHOT 94
FIGURE 26 KEY DEVELOPMENTS BY THE LEADING PLAYERS IN THE
DATA WAREHOUSE AS A SERVICE MARKET, 2017–2018 108
FIGURE 27 AWS: COMPANY SNAPSHOT 113
FIGURE 28 SWOT ANALYSIS: AWS 114
FIGURE 29 IBM: COMPANY SNAPSHOT 116
FIGURE 30 SWOT ANALYSIS: IBM 118
FIGURE 31 MICROSOFT: COMPANY SNAPSHOT 119
FIGURE 32 SWOT ANALYSIS: MICROSOFT 121
FIGURE 33 GOOGLE: COMPANY SNAPSHOT 122
FIGURE 34 SWOT ANALYSIS: GOOGLE 123
FIGURE 35 ORACLE: COMPANY SNAPSHOT 124
FIGURE 36 SWOT ANALYSIS: ORACLE 125
FIGURE 37 SAP: COMPANY SNAPSHOT 126
FIGURE 38 SWOT ANALYSIS: SAP 127
FIGURE 39 MICRO FOCUS: COMPANY SNAPSHOT 129
FIGURE 40 SWOT ANALYSIS: MICRO FOCUS 130
FIGURE 41 SWOT ANALYSIS: 1010DATA 133
FIGURE 42 CLOUDERA: COMPANY SNAPSHOT 134
FIGURE 43 PIVOTAL: COMPANY SNAPSHOT 138
FIGURE 44 HORTONWORKS: COMPANY SNAPSHOT 141
FIGURE 45 TERADATA CORPORATION: COMPANY SNAPSHOT 143
FIGURE 46 VEEVA SYSTEMS: COMPANY SNAPSHOT 145
 

 

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