Data wrangling, sometimes referred to as data munging, is the process of transforming and mapping data from one "raw" data form into another format with the intent of making it more appropriate and valuable for a variety of downstream purposes such as analytics.
In 2018, the global Data Wrangling market size was xx million US$ and it is expected to reach xx million US$ by the end of 2025, with a CAGR of xx% during 2019-2025.

This report focuses on the global Data Wrangling status, future forecast, growth opportunity, key market and key players. The study objectives are to present the Data Wrangling development in United States, Europe and China.

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
Ideata Analytics

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

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

Market segment by Regions/Countries, this report covers
United States
Europe
China
Japan
Southeast Asia
India
Central & South America

The study objectives of this report are:
To analyze global Data Wrangling status, future forecast, growth opportunity, key market and key players.
To present the Data Wrangling development in United States, Europe and China.
To strategically profile the key players and comprehensively analyze their development plan and strategies.
To define, describe and forecast the market by product type, market and key regions.

In this study, the years considered to estimate the market size of Data Wrangling are as follows:
History Year: 2014-2018
Base Year: 2018
Estimated Year: 2019
Forecast Year 2019 to 2025
For the data information by region, company, type and application, 2018 is considered as the base year. Whenever data information was unavailable for the base year, the prior year has been considered.