Global Data Wrangling Market Is Set For A Rapid Growth And Is Expected To Reach Around USD 3.97 Billion by 2024

24-Jul-2018 | Zion Market Research

Zion Market Research has published a new report titled “Data Wrangling Market by Business Function (Finance, Marketing and Sales, Operations, Human Resources, and Legal), by Component (Tools, and Services), by Deployment (On-Premises and Cloud), and by Vertical (BFSI, Government and Public Sector, Healthcare and Life Science, Retail and E-commerce, Telecommunication and IT, Travel and Hospitality, Manufacturing, Energy & Utilities, and Others): Global Industry Perspective, Comprehensive Analysis, and Forecast, 2017-2024’’ According to the report, global data wrangling market was valued at around USD 1.12 billion in 2017 and is expected to reach approximately USD 3.97 billion in 2024, growing at a CAGR of 19.81% between 2018 and 2024. 

Data wrangling is defined as a process of unifying and cleaning complex and messy data sets for easy analysis and access. It is also known as data munging. It is also defined as a process of mapping or transforming raw data into a valuable one for different downstream purposes such as analytics. Different types of data problems faced by data analyzer are inconsistent representations of the same data, missing data, the requirement of human intervention for data problems, incorrect data, and overly sanitizing data. Visualization is a technique to identify raw data or data issues. Some of the visual representations are a matrix view, node-link diagram, and sorted matrix view.

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Global Data Wrangling Market

SQL and Excel are the oldest tools used for data wrangling but recently several new tools have been evolved for fast and powerful wrangling. Some of the new tools can be listed as “R” packages, CSVKit, DataWrangler, Trifacta Wrangler, Python and Pandas, Tabula, OpenRefine, and Mr. Data Converter. Data wrangling solutions are frequently used by several big data analytics solution providers. Some of the languages used frequently for data wrangling are Python, “R”, Java, Hadoop and Hive, Julia, Scala, and Kafka and Storm. Data wrangling targets to provide accurate and actionable data in hands of business analysts, reveal deeper intelligence within data, enable data scientist to focus on the analysis rather than wrangling or transformation of data and drive better decision-making skills, reduce the time spent for collecting and organizing the data. Leading organizations such as PepsiCo, Royal Bank of Scotland, Kaiser Permanente are utilizing the benefits of data wrangling solutions with Big Data to accelerate the analysis processes and also to incorporate new data sources that were difficult to work earlier.

Some of the major factors which are driving the data wrangling market growth are increasing pace and volume of data and advancements in machine learning and AI technologies. Data wrangling has increased the scope for business and helps them to work more efficiently. However, one of the major factor curtailing the market growth is reluctance in shifting from traditional ETL tools to automated tools. Additionally, low awareness regarding data wrangling tools in SMEs, and focus on maintaining data quality is anticipated to restrain the market growth in the forecast period. Increasing regulatory pressure and growth in edge computing are offering significant market opportunities for players in the forecast years.

Data wrangling market is segmented on the basis of business function, component, deployment, verticals, and region. On the basis of business function, the market is bifurcated into finance, marketing and sales, operations, human resources, and legal. Further, by component type, the market is segmented into tools and services. On-premises and cloud are the two modes of deployment adopted in this market. In addition, on the basis of verticals the market is categorized into BFSI, government and public sector, healthcare and life science, retail and e-commerce, telecommunication and IT, travel and hospitality, manufacturing, energy and utilities, and others. In terms of geographic region, North America is expected to dominate the market with highest market share due to the presence of developed economies in the region. Contrary, Asia Pacific region is expected to grow at the highest CAGR during the forecast period owing to the increasing manufacturing business in China and India. 

IBM Corporation, Oracle, SAS Institute, Trifacta, Datawatch, Talend, Alteryx, Dataiku, TIBCO Software, Paxata, Informatica, Hitachi Vantara, Teradata, Onedot, and Brilio are some of the major players of the data wrangling market.

The report segments the global data wrangling market as follows:

Global Data Wrangling Market: Business Function Segment Analysis

  • Finance
  • Marketing and Sales
  • Operations
  • Human Resources
  • Legal

Global Data Wrangling Market: Component Segment Analysis

  • Tools
  • Services

Global Data Wrangling Market: Deployment Segment Analysis

  • On-Premises
  • Cloud

Global Data Wrangling Market: Vertical Segment Analysis

  • BFSI
  • Government and Public Sector
  • Healthcare and Life Science
  • Retail and E-commerce
  • Telecommunication and IT
  • Travel and Hospitality
  • Manufacturing
  • Energy and Utilities
  • Others

Global Data Wrangling Market: Regional Segment Analysis

  • North America
    • The U.S.
  • Europe
    • UK
    • France
    • Germany
  • Asia Pacific
    • China
    • Japan
    • India
  • Latin America
    • Brazil
  • The Middle East and Africa

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