1 Report Overview

• 1.1 Study Scope
• 1.2 Key Market Segments
• 1.3 Market Analysis by Type
  • 1.3.1 Global Data Wrangling Market Size Growth Rate by Type: 2020 VS 2026
  • 1.3.2 On-premises
  • 1.3.3 Cloud Based
• 1.4 Market by Application
  • 1.4.1 Global Data Wrangling Market Share by Application: 2020 VS 2026
  • 1.4.2 BFSI
  • 1.4.3 Telecom and IT
  • 1.4.4 Retail and eCommerce
  • 1.4.5 Healthcare and Life Sciences
  • 1.4.6 Travel and Hospitality
  • 1.4.7 Government
  • 1.4.8 Manufacturing
  • 1.4.9 Energy and Utilities
  • 1.4.10 Transportation and Logistics
  • 1.4.11 Others
• 1.5 Study Objectives
• 1.6 Years Considered

2 Global Growth Trends

• 2.1 Global Data Wrangling Market Perspective (2015-2026)
• 2.2 Data Wrangling Growth Trends by Regions
  • 2.2.1 Data Wrangling Market Size by Regions: 2015 VS 2020 VS 2026
  • 2.2.2 Data Wrangling Historic Market Share by Regions (2015-2020)
  • 2.2.3 Data Wrangling Forecasted Market Size by Regions (2021-2026)
• 2.3 Data Wrangling Industry Dynamic
  • 2.3.1 Data Wrangling Market Trends
  • 2.3.2 Data Wrangling Market Drivers
  • 2.3.3 Data Wrangling Market Challenges
  • 2.3.4 Data Wrangling Market Restraints

3 Competition Landscape by Key Players

• 3.1 Global Top Data Wrangling Players by Market Size
  • 3.1.1 Global Top Data Wrangling Players by Revenue (2015-2020)
  • 3.1.2 Global Data Wrangling Revenue Market Share by Players (2015-2020)
• 3.2 Global Data Wrangling Market Share by Company Type (Tier 1, Tier 2 and Tier 3)
• 3.3 Players Covered: Ranking by Data Wrangling Revenue
• 3.4 Global Data Wrangling Market Concentration Ratio
  • 3.4.1 Global Data Wrangling Market Concentration Ratio (CR5 and HHI)
  • 3.4.2 Global Top 10 and Top 5 Companies by Data Wrangling Revenue in 2019
• 3.5 Key Players Data Wrangling Area Served
• 3.6 Key Players Data Wrangling Product Solution and Service
• 3.7 Date of Enter into Data Wrangling Market
• 3.8 Mergers & Acquisitions, Expansion Plans

4 Data Wrangling Breakdown Data by Type

• 4.1 Global Data Wrangling Historic Market Size by Type (2015-2020)
• 4.2 Global Data Wrangling Forecasted Market Size by Type (2021-2026)

5 Data Wrangling Breakdown Data by Application

• 5.1 Global Data Wrangling Historic Market Size by Application (2015-2020)
• 5.2 Global Data Wrangling Forecasted Market Size by Application (2021-2026)

6 North America

• 6.1 North America Data Wrangling Market Size (2015-2026)
• 6.2 North America Data Wrangling Market Size by Type (2015-2020)
• 6.3 North America Data Wrangling Market Size by Application (2015-2020)
• 6.4 North America Data Wrangling Market Size by Country (2015-2020)
  • 6.4.1 United States
  • 6.4.2 Canada

7 Europe

• 7.1 Europe Data Wrangling Market Size (2015-2026)
• 7.2 Europe Data Wrangling Market Size by Type (2015-2020)
• 7.3 Europe Data Wrangling Market Size by Application (2015-2020)
• 7.4 Europe Data Wrangling Market Size by Country (2015-2020)
  • 7.4.1 Germany
  • 7.4.2 France
  • 7.4.3 U.K.
  • 7.4.4 Italy
  • 7.4.5 Russia
  • 7.4.6 Nordic

8 Asia-Pacific

• 8.1 Asia-Pacific Data Wrangling Market Size (2015-2026)
• 8.2 Asia-Pacific Data Wrangling Market Size by Type (2015-2020)
• 8.3 Asia-Pacific Data Wrangling Market Size by Application (2015-2020)
• 8.4 Asia-Pacific Data Wrangling Market Size by Region (2015-2020)
  • 8.4.1 China
  • 8.4.2 Japan
  • 8.4.3 South Korea
  • 8.4.4 Southeast Asia
  • 8.4.5 India
  • 8.4.6 Australia

9 Latin America

• 9.1 Latin America Data Wrangling Market Size (2015-2026)
• 9.2 Latin America Data Wrangling Market Size by Type (2015-2020)
• 9.3 Latin America Data Wrangling Market Size by Application (2015-2020)
• 9.4 Latin America Data Wrangling Market Size by Country (2015-2020)
  • 9.4.1 Mexico
  • 9.4.2 Brazil

10 Middle East & Africa

• 10.1 Middle East & Africa Data Wrangling Market Size (2015-2026)
• 10.2 Middle East & Africa Data Wrangling Market Size by Type (2015-2020)
• 10.3 Middle East & Africa Data Wrangling Market Size by Application (2015-2020)
• 10.4 Middle East & Africa Data Wrangling Market Size by Country (2015-2020)
  • 10.4.1 Turkey
  • 10.4.2 Saudi Arabia
  • 10.4.3 UAE

11Key Players Profiles

• 11.1 IBM
  • 11.1.1 IBM Company Details
  • 11.1.2 IBM Business Overview
  • 11.1.3 IBM Data Wrangling Introduction
  • 11.1.4 IBM Revenue in Data Wrangling Business (2015-2020))
  • 11.1.5 IBM Recent Development
• 11.2 Oracle
  • 11.2.1 Oracle Company Details
  • 11.2.2 Oracle Business Overview
  • 11.2.3 Oracle Data Wrangling Introduction
  • 11.2.4 Oracle Revenue in Data Wrangling Business (2015-2020)
  • 11.2.5 Oracle Recent Development
• 11.3 SAS
  • 11.3.1 SAS Company Details
  • 11.3.2 SAS Business Overview
  • 11.3.3 SAS Data Wrangling Introduction
  • 11.3.4 SAS Revenue in Data Wrangling Business (2015-2020)
  • 11.3.5 SAS Recent Development
• 11.4 Trifacta
  • 11.4.1 Trifacta Company Details
  • 11.4.2 Trifacta Business Overview
  • 11.4.3 Trifacta Data Wrangling Introduction
  • 11.4.4 Trifacta Revenue in Data Wrangling Business (2015-2020)
  • 11.4.5 Trifacta Recent Development
• 11.5 Datawatch
  • 11.5.1 Datawatch Company Details
  • 11.5.2 Datawatch Business Overview
  • 11.5.3 Datawatch Data Wrangling Introduction
  • 11.5.4 Datawatch Revenue in Data Wrangling Business (2015-2020)
  • 11.5.5 Datawatch Recent Development
• 11.6 Talend
  • 11.6.1 Talend Company Details
  • 11.6.2 Talend Business Overview
  • 11.6.3 Talend Data Wrangling Introduction
  • 11.6.4 Talend Revenue in Data Wrangling Business (2015-2020)
  • 11.6.5 Talend Recent Development
• 11.7 Alteryx
  • 11.7.1 Alteryx Company Details
  • 11.7.2 Alteryx Business Overview
  • 11.7.3 Alteryx Data Wrangling Introduction
  • 11.7.4 Alteryx Revenue in Data Wrangling Business (2015-2020)
  • 11.7.5 Alteryx Recent Development
• 11.8 Dataiku
  • 11.8.1 Dataiku Company Details
  • 11.8.2 Dataiku Business Overview
  • 11.8.3 Dataiku Data Wrangling Introduction
  • 11.8.4 Dataiku Revenue in Data Wrangling Business (2015-2020)
  • 11.8.5 Dataiku Recent Development
• 11.9 TIBCO Software
  • 11.9.1 TIBCO Software Company Details
  • 11.9.2 TIBCO Software Business Overview
  • 11.9.3 TIBCO Software Data Wrangling Introduction
  • 11.9.4 TIBCO Software Revenue in Data Wrangling Business (2015-2020)
  • 11.9.5 TIBCO Software Recent Development
• 11.10 Paxata
  • 11.10.1 Paxata Company Details
  • 11.10.2 Paxata Business Overview
  • 11.10.3 Paxata Data Wrangling Introduction
  • 11.10.4 Paxata Revenue in Data Wrangling Business (2015-2020)
  • 11.10.5 Paxata Recent Development
• 11.11 Informatica
  • 10.11.1 Informatica Company Details
  • 10.11.2 Informatica Business Overview
  • 10.11.3 Informatica Data Wrangling Introduction
  • 10.11.4 Informatica Revenue in Data Wrangling Business (2015-2020)
  • 10.11.5 Informatica Recent Development
• 11.12 Hitachi Vantara
  • 10.12.1 Hitachi Vantara Company Details
  • 10.12.2 Hitachi Vantara Business Overview
  • 10.12.3 Hitachi Vantara Data Wrangling Introduction
  • 10.12.4 Hitachi Vantara Revenue in Data Wrangling Business (2015-2020)
  • 10.12.5 Hitachi Vantara Recent Development
• 11.13 Teradata
  • 10.13.1 Teradata Company Details
  • 10.13.2 Teradata Business Overview
  • 10.13.3 Teradata Data Wrangling Introduction
  • 10.13.4 Teradata Revenue in Data Wrangling Business (2015-2020)
  • 10.13.5 Teradata Recent Development
• 11.14 IRI
  • 10.14.1 IRI Company Details
  • 10.14.2 IRI Business Overview
  • 10.14.3 IRI Data Wrangling Introduction
  • 10.14.4 IRI Revenue in Data Wrangling Business (2015-2020)
  • 10.14.5 IRI Recent Development
• 11.15 Brillio
  • 10.15.1 Brillio Company Details
  • 10.15.2 Brillio Business Overview
  • 10.15.3 Brillio Data Wrangling Introduction
  • 10.15.4 Brillio Revenue in Data Wrangling Business (2015-2020)
  • 10.15.5 Brillio Recent Development
• 11.16 Onedot
  • 10.16.1 Onedot Company Details
  • 10.16.2 Onedot Business Overview
  • 10.16.3 Onedot Data Wrangling Introduction
  • 10.16.4 Onedot Revenue in Data Wrangling Business (2015-2020)
  • 10.16.5 Onedot Recent Development
• 11.17 TMMData
  • 10.17.1 TMMData Company Details
  • 10.17.2 TMMData Business Overview
  • 10.17.3 TMMData Data Wrangling Introduction
  • 10.17.4 TMMData Revenue in Data Wrangling Business (2015-2020)
  • 10.17.5 TMMData Recent Development
• 11.18 Datameer
  • 10.18.1 Datameer Company Details
  • 10.18.2 Datameer Business Overview
  • 10.18.3 Datameer Data Wrangling Introduction
  • 10.18.4 Datameer Revenue in Data Wrangling Business (2015-2020)
  • 10.18.5 Datameer Recent Development
• 11.19 Cooladata
  • 10.19.1 Cooladata Company Details
  • 10.19.2 Cooladata Business Overview
  • 10.19.3 Cooladata Data Wrangling Introduction
  • 10.19.4 Cooladata Revenue in Data Wrangling Business (2015-2020)
  • 10.19.5 Cooladata Recent Development
• 11.20 Unifi Software
  • 10.20.1 Unifi Software Company Details
  • 10.20.2 Unifi Software Business Overview
  • 10.20.3 Unifi Software Data Wrangling Introduction
  • 10.20.4 Unifi Software Revenue in Data Wrangling Business (2015-2020)
  • 10.20.5 Unifi Software Recent Development
• 11.21 Rapid Insight
  • 10.21.1 Rapid Insight Company Details
  • 10.21.2 Rapid Insight Business Overview
  • 10.21.3 Rapid Insight Data Wrangling Introduction
  • 10.21.4 Rapid Insight Revenue in Data Wrangling Business (2015-2020)
  • 10.21.5 Rapid Insight Recent Development
• 11.22 Infogix
  • 10.22.1 Infogix Company Details
  • 10.22.2 Infogix Business Overview
  • 10.22.3 Infogix Data Wrangling Introduction
  • 10.22.4 Infogix Revenue in Data Wrangling Business (2015-2020)
  • 10.22.5 Infogix Recent Development
• 11.23 Zaloni
  • 10.23.1 Zaloni Company Details
  • 10.23.2 Zaloni Business Overview
  • 10.23.3 Zaloni Data Wrangling Introduction
  • 10.23.4 Zaloni Revenue in Data Wrangling Business (2015-2020)
  • 10.23.5 Zaloni Recent Development
• 11.24 Impetus
  • 10.24.1 Impetus Company Details
  • 10.24.2 Impetus Business Overview
  • 10.24.3 Impetus Data Wrangling Introduction
  • 10.24.4 Impetus Revenue in Data Wrangling Business (2015-2020)
  • 10.24.5 Impetus Recent Development
• 11.25 Ideata Analytics
  • 10.25.1 Ideata Analytics Company Details
  • 10.25.2 Ideata Analytics Business Overview
  • 10.25.3 Ideata Analytics Data Wrangling Introduction
  • 10.25.4 Ideata Analytics Revenue in Data Wrangling Business (2015-2020)
  • 10.25.5 Ideata Analytics Recent Development

12Analyst's Viewpoints/Conclusions

13Appendix

• 13.1 Research Methodology
  • 13.1.1 Methodology/Research Approach
  • 13.1.2 Data Source
• 13.2 Disclaimer

Data Wrangling market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Data Wrangling market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by Type and by Application in terms of revenue and forecast for the period 2015-2026.

Market segment by Type, the product can be split into
On-premises
Cloud Based

Market segment by Application, split into
BFSI
Telecom and IT
Retail and eCommerce
Healthcare and Life Sciences
Travel and Hospitality
Government
Manufacturing
Energy and Utilities
Transportation and Logistics

Based on regional and country-level analysis, the Data Wrangling market has been segmented as follows:
North America
United States
Canada
Europe
Germany
France
U.K.
Italy
Russia
Nordic
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Latin America
Mexico
Brazil
Middle East & Africa
Turkey
Saudi Arabia
UAE

In the competitive analysis section of the report, leading as well as prominent players of the global Data Wrangling market are broadly studied on the basis of key factors. The report offers comprehensive analysis and accurate statistics on revenue by the player for the period 2015-2020. It also offers detailed analysis supported by reliable statistics on price and revenue (global level) by player for the period 2015-2020.
The key players covered in this study
IBM
Oracle
SAS
Trifacta
Datawatch
Talend
Alteryx
Dataiku
TIBCO Software
Paxata
Informatica
Hitachi Vantara
Teradata
IRI
Brillio
Onedot
TMMData
Datameer
Cooladata
Unifi Software
Rapid Insight
Infogix
Zaloni
Impetus