Data Wrangling Market Size, Share & Demand By 2031

(MENAFN- Straits Research) Data wrangling is converting unusable data into a form that may be used. Some names for it are data cleansing and data munging. The process of examining, reorganizing, and evaluating raw datasets to obtain high-quality data from their disorganized and complex forms is known as "data wrangling." Data that has been mishandled is used to generate valuable knowledge and guide corporate decisions. The basic goal of data wrangling is to help businesses decrease the time spent collecting and organizing data. Data wrangling also frees data scientists to focus exclusively on analysis rather than data wrangling.
"Data wrangling" describes cleaning, rearranging, and enhancing raw data to get it into the appropriate format. The technique has also altered, with data wrangling taking the place of time-consuming, detailed attempts to master various data sources. Data wrangling has several advantages, including processing vast amounts of data and the simple organization of enormous numbers. The six iterative steps of data wrangling are finding, structuring, cleaning, enriching, validating, and publishing.
Market Dynamics
Increased Adoption of Big Data Analytics by Multiple Organizations
Drives the Global Market
Multiple businesses' increased investment in data-wrangling technologies to boost revenue growth and improve service efficiencies drives the adoption of big data analytics. Senior executives of numerous companies are also swiftly embracing various styles of analytics to satisfy their commercial imperatives as big data analytics gain importance across various geographies, propelling market growth. For instance, a 2017 Forbes survey in North America found that 53% of companies employ big data analytics to increase service productivity and revenue growth. Businesses are also using big data analytics to improve customer experiences and increase organizational effectiveness, opening lucrative opportunities for market expansion.
Growth of Edge Computing Creates Tremendous Opportunities
Edge computing transforms how data is kept, processed, and distributed to millions of users. Edge computing also aids real-time applications in handling and analyzing obtained data, which is another crucial component that generates lucrative market chances. Aside from allowing businesses to easily access their data and offering a variety of security measures to their essential data, edge computing in data handling is growing due to its various cloud storage qualities. As a result, the advancement of edge computing has helped many businesses achieve data dependability and security. The industry is also predicted to gain from the increasing need for end users to evaluate huge amounts of data due to the Internet of Things (IoT) development.
Regional Analysis
North America is the most significant Global Data Wrangling Market shareholder and is estimated to exhibit a CAGR of 15.1% over the forecast period.
Due to the presence of some of the industry's leading firms in performance analytics, it serves as a vital hub for market innovation. In North America, "data wrangling" prepares data for accurate analytics and sensible decision-making effectively. Additionally, BFSI firms are increasingly using data wranglers, which allows them to reduce 15x the time spent on data preparation while streamlining procedures and educating agents on how to connect with clients online. As a result, these businesses have complete access to the profiles of their clientele. For instance, to guarantee that its 30 million customers receive excellent service worldwide, The Royal Bank of Scotland uses big data, largely unstructured and semi-structured data from online client web chats. It makes use of data wranglers to swiftly extract insights from unstructured data. This adoption is estimated to raise the demand for data wranglers over the anticipated time frame.
Additionally, this industry is also growing because of the availability of several data-wrangling suppliers and increasing technological advancements. The increased adoption of big data analytics across numerous industries, including manufacturing, professional services, finance, and federal and central government, has further aided the growth of the data-wrangling sector.
Europe is anticipated to exhibit a CAGR of 18.4% over the forecast period.
Although there is a substantial on-premises performance analytics deployment in Europe, given the prominence and accessibility of cloud computing for mass users, there may be enormous opportunities for increasing the data-wrangling sector. The data-wrangling industry's growth is also fueled by several rules and regulations to enhance an organization's security and privacy. For instance, the European government passed a regulation in 2016 to ensure sufficient protection for the personal data of the employees of businesses throughout the European states. Furthermore, the considerable shift toward cloud deployments, low-cost storage, increased degrees of automation, and data processing platforms is fueling the growth of the data-wrangling business in Europe.
Key Highlights

The global data-wrangling market size was valued at
USD 2,818.50 million in 2022.
It is estimated to reach
USD 12,406.31 billion by 2031,
growing at a
CAGR of 17.9%
during the forecast period (2023–2031).
The global data wrangling market is bifurcated into components, deployment mode, organization size, business function, and industry vertical.
Based on the components, the global data-wrangling market is bifurcated into solutions and services. The solution supplements and nutraceuticals segment dominates the global market and is projected to exhibit a CAGR of 16.8% over the forecast period.
Based on deployment mode, the global data wrangling market is segmented into on-premises and cloud-based. The on-premises segment dominates the global market and is predicted to exhibit a CAGR of 16.5% during the forecast period.
Based on organization size, the global data-wrangling market is bifurcated into large enterprises and SMEs. The large enterprise segment owns the highest market share and is predicted to exhibit a CAGR of 16.1% over the forecast period.
Based on business function, the global data-wrangling market is divided into finance, marketing and sales, operations, and human resources. The operations segment is the most significant contributor to the market and is estimated to exhibit a CAGR of 16.4% over the forecast period.
Based on industry verticals, the global data wrangling market is bifurcated into BFSI, manufacturing, healthcare, government, retail and e-commerce, IT and telecom, and education. The BFSI segment owns the highest market share and is predicted to exhibit a CAGR of 16% over the forecast period.
North America is the most significant global data-wrangling market shareholder and is estimated to exhibit a CAGR of 15.1% over the forecast period.

Competitive Players
The key players in the global data wrangling market are IBM Corporation, Oracle Corporation, SAS Institute, Tibco Software, Hitachi Vantara, Teradata Corporation, Alteryx, Impetus, Trifacta Software Inc., and Paxata Inc.
Market News

In February 2023,
Alteryx generally made its Analytics Cloud GA Platform available. It features a new decision intelligence function under Auto Insights and a revised user interface for Designer Cloud. The platform has been updated with new versions of products like Designer Cloud and Auto Insights.
In November 2023,
Amazon SageMaker now includes geospatial and governance features from AWS. The industry leader in cloud computing updated Data Wrangler with 40 new data connections and added geographic and data governance tools to its machine learning platform.

Global Data Wrangling Market: Segmentation
By Component

Solution
Service

By Deployment Mode

On-premises
Cloud-based

By Organization Size

Large Enterprises
SMEs

By Business Function

Finance, Marketing, and Sales
Operations
Human Resources

By Industry Vertical

BFSI
Manufacturing
Healthcare
Government
Retail and E-Commerce
IT and Telecom
Education
Others

By Regions

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

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