Data Wrangling Market by Business Function (Marketing and Sales  Finance  Operations  HR  and Legal)  Component (Tools and Services)  Deployment Model  Organization Size  Industry Vertical  and Region - Global Forecast to 2023

Data Wrangling Market by Business Function (Marketing and Sales Finance Operations HR and Legal) Component (Tools and Services) Deployment Model Organization Size Industry Vertical and Region - Global Forecast to 2023

MarketsandMarkets | ID: 1524244447274 | Published at: 2018-05-08 | Pages: 165

  • €4.785,63


Increasing volume and velocity of data is the key growth driver for the data wrangling market
The data wrangling market size is expected to grow from USD 1.29 billion in 2018 to USD 3.18 billion by 2023, at a Compound Annual Growth Rate (CAGR) of 19.7% during the forecast period. The growth factors include the increasing volume and velocity of data and advancements in AI and ML technologies. However, companies’ reluctance to shift from traditional ETL tools to advanced automated tools is a restraining factor in the data wrangling market.
Finance business function is estimated to hold the largest market size in 2018 in the data wrangling market.
Recognition software consists of various modules used for object, voice, speech, image, gesture, facial, and character recognition. The recognition software provides highly integrated tools that help bot developers integrate AI into the software to enable the robot to tackle problems, such as language and dialog skills.
The finance business application utilizes the power of analytics to determine risk factors, enhance business processes, invest judiciously, access profitability, identify target customers, and predict future events. Along with this, analytics software also assists in improving client relations, driving revenue, managing risks, meeting regulatory obligations, streamlining back-office processes, and developing high quality products and services. Data wrangling tools are the precursor to analytics and thus would be adopted substantially with the growing use of analytics in finance business process.
Asia Pacific (APAC) is expected to grow at the highest rate during the forecast period in the data wrangling market by region
The APAC region is expected to grow at the highest rate in the data wrangling market during the forecast period. Australia, New Zealand, China, Singapore, and Japan are witnessing growth in big data and analytics startups. This would create numerous growth opportunities especially in China, India, Bangladesh, and others. With the growth of smart cities and proliferation of IoT devices, the region is expected to witness huge growth in the coming years.
Data wrangling solution providers have started expanding their footprint in Japan owing to the increase in big data and rising need for data preparation solutions. For instance, Paxata partnered with K.K. Ashisuto to serve as a distributor for Paxata’s data preparation solution. This is expected to drive the growth of data wrangling solutions during the forecast period.
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. The break-up of the profile of the primary participants is as follows:
• By Company: Tier 1 – 33 , Tier 2 –26, and Tier 3 –41%
• By Designation: C level – 37%, Director level – 44%, and Others – 19%
• By Region: North America – 36%, Europe – 29%, APAC – 25% and RoW – 10%
The data wrangling market comprises following major vendors:
1. Trifacta (US)
2. Datawatch (US)
3. Dataiku (France)
4. IBM (US)
5. SAS Institute (US)
6. Oracle (US)
7. Talend (US)
8. Alteryx (US)
9. TIBCO (US)
10. Paxata (US)
11. Informatica (US)
12. Hitachi Vantara (US)
13. Teradata (US)
14. Datameer (US)
15. Cooladata (US)
16. Unifi (US)
17. Rapid Insight (US)
18. Infogi (US)
19. Zaloni (US)
20. Impetus (US)
21. Ideata Analytics (India)
22. Onedot (Switzerland)
23. IRI (US)
24. Brillio (US)
25. TMMData (US)
Research Report
The report segments the data wrangling market by business functions (marketing and sales, finance, operations, HR, and legal), components (tools and services), deployment models (on-premises and on-demand), organization sizes (large enterprises and SMEs), verticals (BFSI, telecom and IT, retail and eCommerce, healthcare and life sciences, travel and hospitality, government, manufacturing, energy and utilities, transportation and logistics, and others), and regions (North America, Europe, APAC, MEA, and Latin America).
Reasons to Buy the Report
• To get a comprehensive overview of the global data wrangling market
• To gain wide-range of information about the top players in this market, their product portfolios, and the key strategies adopted
• To gain insights into the major countries/regions, in which the data wrangling market is flourishing across verticals

TABLE OF CONTENTS

1 INTRODUCTION 17

  • 1.1 OBJECTIVES OF THE STUDY 17
  • 1.2 MARKET DEFINITION 17
  • 1.3 MARKET SCOPE 18
  • 1.4 YEARS CONSIDERED FOR THE STUDY 19
  • 1.5 CURRENCY 19
  • 1.6 STAKEHOLDERS 20
    2 RESEARCH METHODOLOGY 21
  • 2.1 RESEARCH DATA 21
    • 2.1.1 SECONDARY DATA 22
    • 2.1.2 PRIMARY DATA 22
      • 2.1.2.1 Breakdown of primaries 23
      • 2.1.2.2 Key industry insights 24
  • 2.2 MARKET SIZE ESTIMATION 26
  • 2.3 RESEARCH ASSUMPTIONS 28
  • 2.4 LIMITATIONS 28
    3 EXECUTIVE SUMMARY 29
    4 PREMIUM INSIGHTS 34
  • 4.1 ATTRACTIVE OPPORTUNITIES IN THE DATA WRANGLING MARKET 34
  • 4.2 DATA WRANGLING MARKET, BY APPLICATION AND REGION 35
  • 4.3 DATA WRANGLING MARKET: MARKET SHARE, BY REGION 36
  • 4.4 LIFE CYCLE ANALYSIS, BY REGION, 2018 37
    5 MARKET OVERVIEW 38
  • 5.1 INTRODUCTION 38
    • 5.1.1 DRIVERS 39
      • 5.1.1.1 Increasing volume and velocity of data 39
      • 5.1.1.2 Advancements in AI and ML technologies 39
    • 5.1.2 RESTRAINTS 39
      • 5.1.2.1 Reluctance to shift from traditional ETL tools to advanced automated tools 39
    • 5.1.3 OPPORTUNITIES 40
      • 5.1.3.1 Increasing regulatory pressure 40
      • 5.1.3.2 Growth of edge computing 40
  • 5.1.4 CHALLENGES 40
    • 5.1.4.1 Lack of awareness of data wrangling tools among SMEs 40
    • 5.1.4.2 Concerns regarding data quality 41
  • 5.2 DATA TYPES 41
    • 5.2.1 CUSTOMER DATA 41
    • 5.2.2 PRODUCT DATA 42
    • 5.2.3 FINANCE DATA 42
    • 5.2.4 COMPLIANCE DATA 42
    • 5.2.5 SUPPLIER DATA 42
  • 5.3 DATA WRANGLING: USE CASES 43
    • 5.3.1 USE CASE #1: UNIFICATION OF DATA 43
    • 5.3.2 USE CASE #2: DATA WRANGLING AND ANALYTICS TO OBTAIN CUSTOMER INSIGHTS 43
    • 5.3.3 USE CASE #3: DATA INTEGRATION SAVED FORTUNE 50 TELECOM GIANT MILLIONS IN CALL CENTER INTERACTIONS 44
    • 5.3.4 USE CASE #4: ONEDOT MADE IT SIMPLE FOR ZAGENO TO INTEGRATE UNSTRUCTURED DATA AND DELIVER THE BEST POSSIBLE SEARCH RESULTS 45
      6 DATA WRANGLING MARKET, BY BUSINESS FUNCTION 46
  • 6.1 INTRODUCTION 47
  • 6.2 FINANCE 48
  • 6.3 MARKETING AND SALES 48
  • 6.4 OPERATIONS 49
  • 6.5 HUMAN RESOURCES 50
  • 6.6 LEGAL 51
    7 DATA WRANGLING MARKET, BY COMPONENT 52
  • 7.1 INTRODUCTION 53
  • 7.2 TOOLS 54
  • 7.3 SERVICES 55
    • 7.3.1 MANAGED SERVICES 56
    • 7.3.2 PROFESSIONAL SERVICES 57
      • 7.3.2.1 Consulting services 58
      • 7.3.2.2 Support and maintenance services 59
        8 DATA WRANGLING MARKET, BY DEPLOYMENT MODEL 60
  • 8.1 INTRODUCTION 61
  • 8.2 ON-PREMISES 62
  • 8.3 CLOUD 62
    9 DATA WRANGLING MARKET, BY ORGANIZATION SIZE 64
  • 9.1 INTRODUCTION 65
  • 9.2 LARGE ENTERPRISES 66
  • 9.3 SMALL AND MEDIUM-SIZED ENTERPRISES 66
    10 DATA WRANGLING MARKET, BY INDUSTRY VERTICAL 68
  • 10.1 INTRODUCTION 69
  • 10.2 BANKING, FINANCIAL SERVICES, AND INSURANCE 70
  • 10.3 GOVERNMENT AND PUBLIC SECTOR 71
  • 10.4 HEALTHCARE AND LIFE SCIENCES 72
  • 10.5 RETAIL AND ECOMMERCE 72
  • 10.6 TRAVEL AND HOSPITALITY 73
  • 10.7 AUTOMOTIVE AND TRANSPORTATION 74
  • 10.8 ENERGY AND UTILITIES 75
  • 10.9 TELECOMMUNICATION AND IT 75
  • 10.10 MANUFACTURING 76
  • 10.11 OTHERS 77
    11 DATA WRANGLING MARKET, BY REGION 78
  • 11.1 INTRODUCTION 79
  • 11.2 NORTH AMERICA 80
    • 11.2.1 BY COUNTRY 84
      • 11.2.1.1 United States 84
      • 11.2.1.2 Canada 85
  • 11.3 EUROPE 86
    • 11.3.1 BY COUNTRY 89
      • 11.3.1.1 United Kingdom 89
      • 11.3.1.2 Germany 90
      • 11.3.1.3 France 90
      • 11.3.1.4 Rest of Europe 90
  • 11.4 ASIA PACIFIC 91
    • 11.4.1 BY COUNTRY 94
      • 11.4.1.1 China 94
      • 11.4.1.2 Australia and New Zealand 94
      • 11.4.1.3 Singapore 95
      • 11.4.1.4 Japan 95
      • 11.4.1.5 Rest of APAC 95
  • 11.5 MIDDLE EAST AND AFRICA 96
    • 11.5.1 BY COUNTRY 99
      • 11.5.1.1 United Arab Emirates (UAE) 99
      • 11.5.1.2 Kingdom of Saudi Arabia 99
      • 11.5.1.3 Qatar 99
      • 11.5.1.4 South Africa 99
      • 11.5.1.5 Rest of MEA 99
  • 11.6 LATIN AMERICA 100
    • 11.6.1 BY COUNTRY 103
      • 11.6.1.1 Brazil 103
      • 11.6.1.2 Mexico 103
      • 11.6.1.3 Rest of Latin America 104
        12 COMPETITIVE LANDSCAPE 105
  • 12.1 OVERVIEW 105
  • 12.2 PROMINENT PLAYERS IN THE DATA WRANGLING MARKET 106
  • 12.3 COMPETITIVE SCENARIO 107
    • 12.3.1 NEW PRODUCT LAUNCHES AND PRODUCT UPGRADATIONS 107
    • 12.3.2 PARTNERSHIPS, COLLABORATIONS, AND AGREEMENTS 108
    • 12.3.3 BUSINESS EXPANSIONS 109
    • 12.3.4 ACQUISITIONS 109
      13 COMPANY PROFILES 110
      (Business Overview, Solutions/Software Offered, Recent Developments, SWOT Analysis, and MnM View)*
  • 13.1 IBM 110
  • 13.2 ORACLE 113
  • 13.3 SAS INSTITUTE 116
  • 13.4 TRIFACTA 119
  • 13.5 DATAWATCH 122
  • 13.6 TALEND 125
  • 13.7 ALTERYX 127
  • 13.8 DATAIKU 129
  • 13.9 TIBCO SOFTWARE 131
  • 13.10 PAXATA 133
  • 13.11 INFORMATICA 135
  • 13.12 HITACHI VANTARA 137
  • 13.13 TERADATA 139
  • 13.14 IRI, THE COSORT COMPANY 141
  • 13.15 BRILLIO 142
  • 13.16 ONEDOT 143
  • 13.17 TMMDATA 145
  • 13.18 DATAMEER 147
  • 13.19 COOLADATA 148
  • 13.20 UNIFI SOFTWARE 149
  • 13.21 RAPID INSIGHT 150
  • 13.22 INFOGIX 151
  • 13.23 ZALONI 152
  • 13.24 IMPETUS 153
  • 13.25 IDEATA ANALYTICS 154
*Details on Business Overview, Solutions/Software Offered, Recent Developments, SWOT Analysis, and MnM View might not be captured in case of unlisted companies.
14 APPENDIX 155
  • 14.1 KEY INSIGHTS OF INDUSTRY EXPERTS 155
  • 14.2 DISCUSSION GUIDE 156
  • 14.3 KNOWLEDGE STORE: MARKETSANDMARKETS’ SUBSCRIPTION PORTAL 160
  • 14.4 INTRODUCING RT: REAL-TIME MARKET INTELLIGENCE 162
  • 14.5 AVAILABLE CUSTOMIZATION 163
  • 14.6 RELATED REPORTS 163
  • 14.7 AUTHOR DETAILS 164

LIST OF TABLES

TABLE 1 DATA WRANGLING MARKET SIZE, 2016–2023 (USD MILLION) 30
TABLE 2 DATA WRANGLING MARKET SIZE, BY BUSINESS FUNCTION,
2016–2023 (USD MILLION) 47
TABLE 3 FINANCE: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 48
TABLE 4 MARKETING AND SALES: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 49
TABLE 5 OPERATIONS: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 49
TABLE 6 HUMAN RESOURCES: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 50
TABLE 7 LEGAL: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 51
TABLE 8 DATA WRANGLING MARKET SIZE, BY COMPONENT, 2016–2023 (USD MILLION) 53
TABLE 9 TOOLS: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 54
TABLE 10 SERVICES: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 55
TABLE 11 SERVICES: DATA WRANGLING MARKET SIZE, BY TYPE, 2016–2023 (USD MILLION) 56
TABLE 12 MANAGED SERVICES MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 56
TABLE 13 PROFESSIONAL SERVICES MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 57
TABLE 14 PROFESSIONAL SERVICES MARKET SIZE, BY TYPE, 2016–2023 (USD MILLION) 58
TABLE 15 CONSULTING SERVICES MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 58
TABLE 16 SUPPORT AND MAINTENANCE SERVICES MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 59
TABLE 17 DATA WRANGLING MARKET SIZE, BY DEPLOYMENT MODEL,
2016–2023 (USD MILLION) 61
TABLE 18 ON-PREMISES: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 62
TABLE 19 CLOUD: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 63
TABLE 20 DATA WRANGLING MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 65
TABLE 21 LARGE ENTERPRISES: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 66
TABLE 22 SMALL AND MEDIUM-SIZED ENTERPRISES: DATA WRANGLING MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 67
TABLE 23 DATA WRANGLING MARKET SIZE, BY INDUSTRY VERTICAL,
2016–2023 (USD MILLION) 69
TABLE 24 BANKING, FINANCIAL SERVICES, AND INSURANCE: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 70
TABLE 25 GOVERNMENT AND PUBLIC SECTOR: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 71
TABLE 26 HEALTHCARE AND LIFE SCIENCES: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 72
TABLE 27 RETAIL AND ECOMMERCE: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 73
TABLE 28 TRAVEL AND HOSPITALITY: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 74
TABLE 29 AUTOMOTIVE AND TRANSPORTATION: DATA WRANGLING MARKET SIZE,
BY REGION, 2016–2023 (USD MILLION) 74
TABLE 30 ENERGY AND UTILITIES: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 75
TABLE 31 TELECOMMUNICATION AND IT: DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 76
TABLE 32 MANUFACTURING: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 76
TABLE 33 OTHERS: DATA WRANGLING MARKET SIZE, BY REGION,
2016–2023 (USD MILLION) 77
TABLE 34 DATA WRANGLING MARKET SIZE, BY REGION, 2016–2023 (USD MILLION) 79
TABLE 35 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 81
TABLE 36 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 82
TABLE 37 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY PROFESSIONAL SERVICE, 2016–2023 (USD MILLION) 82
TABLE 38 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY BUSINESS FUNCTION, 2016–2023 (USD MILLION) 82
TABLE 39 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 83
TABLE 40 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 83
TABLE 41 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 84
TABLE 42 NORTH AMERICA: DATA WRANGLING MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 85
TABLE 43 EUROPE: DATA WRANGLING MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 86
TABLE 44 EUROPE: DATA WRANGLING MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 86
TABLE 45 EUROPE: DATA WRANGLING MARKET SIZE, BY PROFESSIONAL SERVICE,
2016–2023 (USD MILLION) 87
TABLE 46 EUROPE: DATA WRANGLING MARKET SIZE, BY BUSINESS FUNCTION,
2016–2023 (USD MILLION) 87
TABLE 47 EUROPE: DATA WRANGLING MARKET SIZE, BY DEPLOYMENT MODEL,
2016–2023 (USD MILLION) 88
TABLE 48 EUROPE: DATA WRANGLING MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 88
TABLE 49 EUROPE: DATA WRANGLING MARKET SIZE, BY INDUSTRY VERTICAL,
2016–2023 (USD MILLION) 89
TABLE 50 EUROPE: DATA WRANGLING MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 90
TABLE 51 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 91
TABLE 52 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 92
TABLE 53 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY PROFESSIONAL SERVICE, 2016–2023 (USD MILLION) 92
TABLE 54 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY BUSINESS FUNCTION,
2016–2023 (USD MILLION) 93
TABLE 55 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY DEPLOYMENT MODEL,
2016–2023 (USD MILLION) 93
TABLE 56 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 93
TABLE 57 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY INDUSTRY VERTICAL,
2016–2023 (USD MILLION) 94
TABLE 58 ASIA PACIFIC: DATA WRANGLING MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 95
TABLE 59 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY COMPONENT, 2016–2023 (USD MILLION) 96
TABLE 60 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 96
TABLE 61 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY PROFESSIONAL SERVICE, 2016–2023 (USD MILLION) 97
TABLE 62 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY BUSINESS FUNCTION, 2016–2023 (USD MILLION) 97
TABLE 63 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 97
TABLE 64 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY ORGANIZATION SIZE, 2016–2023 (USD MILLION) 98
TABLE 65 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY INDUSTRY VERTICAL, 2016–2023 (USD MILLION) 98
TABLE 66 MIDDLE EAST AND AFRICA: DATA WRANGLING MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 100
TABLE 67 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY COMPONENT,
2016–2023 (USD MILLION) 100
TABLE 68 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY SERVICE,
2016–2023 (USD MILLION) 101
TABLE 69 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY PROFESSIONAL SERVICE, 2016–2023 (USD MILLION) 101
TABLE 70 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY BUSINESS FUNCTION, 2016–2023 (USD MILLION) 101
TABLE 71 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY DEPLOYMENT MODEL, 2016–2023 (USD MILLION) 102
TABLE 72 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY ORGANIZATION SIZE,
2016–2023 (USD MILLION) 102
TABLE 73 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY INDUSTRY VERTICAL,
2016–2023 (USD MILLION) 103
TABLE 74 LATIN AMERICA: DATA WRANGLING MARKET SIZE, BY COUNTRY,
2016–2023 (USD MILLION) 104
TABLE 75 NEW PRODUCT LAUNCHES AND PRODUCT UPGRADATIONS, 2014–2018 107
TABLE 76 PARTNERSHIPS, COLLABORATIONS, AND AGREEMENTS, 2014–2018 108
TABLE 77 BUSINESS EXPANSIONS, 2014–2018 109
TABLE 78 ACQUISITIONS, 201–2018 109


LIST OF FIGURES

FIGURE 1 DATA WRANGLING MARKET: MARKET SEGMENTATION 18
FIGURE 2 DATA WRANGLING MARKET, BY REGION AND COUNTRY 19
FIGURE 3 DATA WRANGLING MARKET: RESEARCH DESIGN 21
FIGURE 4 BREAKDOWN OF PRIMARY INTERVIEWS: BY COMPANY, DESIGNATION,
AND REGION 23
FIGURE 5 DATA TRIANGULATION 25
FIGURE 6 MARKET SIZE ESTIMATION METHODOLOGY: BOTTOM-UP APPROACH 26
FIGURE 7 MARKET SIZE ESTIMATION METHODOLOGY: TOP-DOWN APPROACH 27
FIGURE 8 DATA WRANGLING MARKET: ASSUMPTIONS 28
FIGURE 9 GLOBAL DATA WRANGLING MARKET IS EXPECTED TO WITNESS SIGNIFICANT GROWTH DURING THE FORECAST PERIOD 30
FIGURE 10 DATA WRANGLING MARKET SNAPSHOT, BY COMPONENT (2018 VS. 2023) 31
FIGURE 11 DATA WRANGLING MARKET SNAPSHOT, BY SERVICE (2018 VS. 2023) 31
FIGURE 12 DATA WRANGLING MARKET SNAPSHOT, BY BUSINESS FUNCTION (2018 VS. 2023) 32
FIGURE 13 DATA WRANGLING MARKET SNAPSHOT, BY DEPLOYMENT MODEL (2018 VS. 2023) 32
FIGURE 14 DATA WRANGLING MARKET SNAPSHOT, BY INDUSTRY VERTICAL (2018 VS 2023) 33
FIGURE 15 DATA WRANGLING MARKET GROWTH IS DRIVEN BY RAPID GROWTH IN DATA VOLUMES AND STRINGENT REGULATORY AND COMPLIANCE MANDATES 34
FIGURE 16 FINANCE, AND NORTH AMERICA ARE ESTIMATED TO HAVE THE LARGEST MARKET SHARES IN 2018 35
FIGURE 17 NORTH AMERICA IS ESTIMATED TO HAVE THE LARGEST MARKET SHARE IN 2018 36
FIGURE 18 ASIA PACIFIC IS EXPECTED TO WITNESS SIGNIFICANT GROWTH DURING THE FORECAST PERIOD 37
FIGURE 19 DATA WRANGLING MARKET: DRIVERS, RESTRAINTS, OPPORTUNITIES, AND CHALLENGES 38
FIGURE 20 OPERATIONS BUSINESS FUNCTION IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 47
FIGURE 21 SERVICES SEGMENT IS EXPECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 53
FIGURE 22 MANAGED SERVICES SEGMENT IS EXPECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 55
FIGURE 23 CONSULTING SERVICES SEGMENT IS EXPECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 57
FIGURE 24 CLOUD DEPLOYMENT MODEL IS EXPECTED TO REGISTER A HIGHER CAGR DURING THE FORECAST PERIOD 61
FIGURE 25 SMALL AND MEDIUM-SIZED ENTERPRISES SEGMENT IS EXPECTED TO GROW AT A HIGHER CAGR DURING THE FORECAST PERIOD 65
FIGURE 26 HEALTHCARE AND LIFE SCIENCES INDUSTRY VERTICAL IS EXPECTED TO GROW AT THE HIGHEST CAGR DURING THE FORECAST PERIOD 69
FIGURE 27 ASIA PACIFIC IS EXPECTED TO HAVE THE HIGHEST CAGR DURING THE FORECAST PERIOD 79
FIGURE 28 ASIA PACIFIC IS EXPECTED TO REGISTER THE HIGHEST GROWTH RATE IN THE DATA WRANGLING MARKET DURING THE FORECAST PERIOD 80
FIGURE 29 NORTH AMERICA: MARKET SNAPSHOT 81
FIGURE 30 ASIA PACIFIC: MARKET SNAPSHOT 91
FIGURE 31 KEY DEVELOPMENTS BY THE LEADING PLAYERS IN THE DATA WRANGLING MARKET, 2014–2018 105
FIGURE 32 IBM: COMPANY SNAPSHOT 110
FIGURE 33 IBM: SWOT ANALYSIS 112
FIGURE 34 ORACLE: COMPANY SNAPSHOT 113
FIGURE 35 ORACLE: SWOT ANALYSIS 114
FIGURE 36 SAS INSTITUTE: COMPANY SNAPSHOT 116
FIGURE 37 SAS INSTITUTE: SWOT ANALYSIS 118
FIGURE 38 TRIFACTA: SWOT ANALYSIS 121
FIGURE 39 DATAWATCH: COMPANY SNAPSHOT 122
FIGURE 40 DATAWATCH: SWOT ANALYSIS 124
FIGURE 41 TALEND: COMPANY SNAPSHOT 125
FIGURE 42 ALTERYX: COMPANY SNAPSHOT 127
FIGURE 43 TERADATA: COMPANY SNAPSHOT 139

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