Data Wrangling Market4

According to the latest report by IMARC Group, titled, “Data Wrangling Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2022-2027“, The global data wrangling market size reached a value of US$ 2.2 Billion in 2021. Looking forward, IMARC Group expects the market to reach US$ 5.5 Billion by 2027, exhibiting a CAGR of 16.7% during 2022-2027.

Data wrangling refers to the process of transforming raw data into a readily used format. It includes discovering, structuring, cleaning, enriching, validating, and publishing data. It merges various types of information from different sources, such as databases, web services, and files, to make them easier to analyze, which helps in identifying discrepancies in the business. It also facilitates data format within an intuitive user interface and efficiently schedules and automates the data flow process. Data wrangling acts as a preparation stage for the data mining process and allows business users to make decisions timely. It also enables them to tackle more complex data and produce more accurate results for better decision-making. Apart from this, it relies on advanced technologies, such as artificial intelligence (AI), machine learning (ML), and data analytics for advanced tasks. It assists in backing up data, ensuring databases operate without errors, and keeping the data secure. At present, it finds extensive applications in the government and public sector, healthcare and life sciences, retail and e-commerce, media and entertainment, and manufacturing industries.

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Global Data Wrangling Market Trends and Drivers:

The rapid expansion of data sources is resulting in the rising need for storing and organizing large quantities of information for analysis. This currently represents one of the primary factors positively influencing the market. In addition, business firms use data wrangling tools to support data security, ensure accurate and recurring data modeling results, detect corporate fraud, perform customer behavior analysis, and recognize the business value of the data promptly. Apart from this, data wrangling finds extensive applications in financial services and insurance companies to produce actionable insights from the data that have a potential business value associated with them. This, in confluence with rapid digitization and the development of big data, data wrangling helps in combining structured, semi-structured, and unstructured data sources for analysis, which is bolstering the market growth. Apart from this, as data wrangling can be manual or automated, small, medium and large-scale organizations are using these solutions to filter inconsistent low-quality data and improve organizational processes, which is creating a positive market outlook. Furthermore, the business, financial services, and insurance (BFSI) use data wrangling processes to improve data security, optimize online banking portals, and empower the analytics team to spend less time organizing their data and more time in delivering analysis and insights. These associated benefits are expected to strengthen the growth of the market in the coming years.

Data Wrangling Market 2022-2027 Competitive Analysis and Segmentation:

IMARC Group provides an analysis of the key trends in each sub-segment of the global data wrangling market report, along with forecasts for growth at the global and regional level from 2022-2027. Our report has categorized the market based on component, deployment mode, organization size, business function and industry vertical.

Competitive Landscape:

The competitive landscape of the industry has also been examined along with the profiles of the key players.

  • Altair Engineering Inc.
  • Hitachi Vantara Corporation
  • Impetus Technologies Inc.
  • International Business Machines Corporation
  • Oracle Corporation
  • SAS Institute Inc.
  • Teradata Corporation
  • TIBCO Software Inc
  • Trifacta Software Inc.

Breakup by Component:

  • Solution
  • Service

Breakup by Deployment Mode:

  • On-premises
  • Cloud-based

Breakup by Organization Size:

  • Large Enterprises
  • Small and Medium Enterprises

Breakup by Business Function:

  • Finance
  • Marketing and Sales
  • Operations
  • Human Resources

Breakup by Industry Vertical:

  • BFSI
  • Government and Public Sector
  • Healthcare and Life Science
  • Retail and E-commerce
  • Media and Entertainment
  • IT and Telecom
  • Manufacturing
  • Others

Breakup by Region:

  • North America
  • Asia-Pacific
  • Europe
  • Latin America
  • Middle East and Africa

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