Data Wrangling Market Size to Surpass USD 12.6 Billion by 2032, Owing to Growing Integration of AI and Machine Learning in Data Processing | SNS Insider

GlobeNewswire On April 11, 2025 19:00 IST

The market is undergoing rapid transformation as businesses across various industries recognize the importance of data in driving strategic decisions.

Pune, April 11, 2025 (GLOBE NEWSWIRE) — Data Wrangling Market Size Analysis:

“The Data Wrangling Market size was USD 3.2 billion in 2023 and is expected to reach USD 12.6 billion by 2032, growing at a CAGR of 16.59% over the forecast period of 2024–2032.”

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Major Players Analysis Listed in this Report are:

Trifacta – Trifacta Wrangler
Talend – Talend Data Preparation
IBM – IBM Data Refinery
Alteryx – Alteryx Designer
Informatica – Informatica Data Preparation
DataRobot – DataRobot Paxata
TIBCO Software – TIBCO Clarity
Microsoft – Power Query (Excel & Power BI)
Google – Google Cloud Dataprep
Oracle – Oracle Data Integrator
AWS – AWS Glue DataBrew
SAS Institute – SAS Data Preparation
Hitachi Vantara – Pentaho Data Integration
Qlik – Qlik Data Integration
Datameer – Datameer Spectrum

Data Wrangling Market Report Scope:

Report Attributes	Details
Market Size in 2023	USD 3.2 Billion
Market Size by 2032	USD 12.6 Billion
CAGR	CAGR of 16.59% From 2024 to 2032
Base Year	2023
Forecast Period	2024-2032
Historical Data	2020-2022
Key Regional Coverage	North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe [Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]). Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia Rest of Latin America)
Key Growth Drivers	• Rising data generation across industries is fueling demand for efficient data wrangling tools to enhance analytics and decision-making.

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AI-Powered Cloud Solutions Drive Surge in Global Data Wrangling Adoption Across Key Industries

The data wrangling market is expanding at a high pace, supported by rapid data generation in industries such as finance, healthcare, and retail. Organizations are turning to cloud-based solutions to handle huge amounts of structured and unstructured data due to their scalability and affordability. The combination of AI and ML is revolutionizing data wrangling as it automates processes like anomaly detection, data classification, and cleansing, lowering human effort and increasing accuracy.

The U.S. Data Wrangling Market size was USD 1.05 billion in 2023 and is projected to reach USD 4.09 billion by 2032, growing at a CAGR of 16.3% during the forecast period of 2024–2032.

The U.S market is growing substantially, as industries like finance, healthcare, and retail are leveraging data-driven decision-making more and more. Organizations are focusing on optimizing data processing to manage escalating amounts of structured and unstructured data. Market growth is also being driven by the extensive use of cloud technology and advanced analytics tools. Furthermore, incorporating AI and machine learning in data-wrangling solutions allows for greater automation, precision, and efficiency in operations.

By Component, Solutions Segment Dominates Data Wrangling Market While Services Segment Poised for Rapid Growth

The solutions segment led the market, and it held 74% of the revenue share in 2023. The reason behind the leadership of this segment is the rise of end-to-end platforms that encompass data integration, preparation, and analysis. Large cloud vendors such as AWS, Google Cloud, and Microsoft Azure are actively backing such platforms, hence driving the solutions segment further.

The services segment is expected to exhibit the quickest expansion, with organizations investing in consulting, training, and implementation services to turn their data-wrangling operations more streamlined and derive value from datasets.

By Deployment, On-Premises Solutions Dominate Data Wrangling Market Amidst Growing Cloud Adoption

In 2023, on-premises data-wrangling platforms maintained the largest market share, largely because of the security and compliance requirements of regulated sectors such as healthcare and finance. Cloud solutions are, however, predicted to expand at the highest rate, fueled by their scalability, cost-effectiveness, and ease of integration. The transition to a hybrid and multi-cloud strategy is fueling demand for cloud-native wrangling platforms that can manage intricate, distributed workloads. As companies aim to steer clear of vendor lock-in and enhance agility, cloud adoption within the data wrangling arena is poised to gain momentum, transforming deployment preferences across sectors.

By Enterprise Size, Large Enterprises Dominate Data Wrangling Market as SMEs Rapidly Embrace Scalable Solutions

Large enterprises led the market for data wrangling in 2023, using complex tools to tackle and analyse their large and sophisticated data landscapes. Such companies need advanced solutions in order to drive accurate data, adhere to compliances, and drive meaningful insights economically. On the other hand, small and medium businesses (SMEs) are increasingly taking on scalable data-wrangling solutions to underpin their increasing data requirements. The presence of affordable, cloud-based technologies facilitates SMEs’ ability to enact data-driven solutions without heavy upfront infrastructure investments, thereby improving competitiveness within the shifting market environment.

By End-User, BFSI Sector Dominates Data Wrangling Market Amidst Rapid Growth in IT and Telecom

The BFSI industry led the way because of its strict compliance requirements and heavy dependence on high-quality, real-time information. Data wrangling solutions guarantee data accuracy, governance, and security cornerstones for the financial industry. The IT and Telecom industry is expected to expand at the most rapid rate because these firms deal with dynamic data streams in CRM systems, billing systems, and customer support operations, which necessitate efficient data wrangling for service quality and performance enhancement.

Data Wrangling Market Segmentation:

By Component

Solution
Services

By Deployment

Cloud
On-premises

By Enterprise Size

SMEs
Large Enterprises

By End-Use

BFSI
Government
Manufacturing
Retails
Healthcare
IT & Telecom
Others (Media & Entertainment, Transportation)

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North America Dominates Data Wrangling Market While Asia Pacific Emerges as Fastest-Growing Region

North America held a dominant 43% market share in 2023, and leadership is fueled by the region’s mature technology infrastructure and broad embrace of AI and automation. American-based companies are increasingly using intelligent data-wrangling platforms to improve operational agility, especially within the finance, e-commerce, and healthcare industries. The availability of large technology companies and data-driven innovation culture continue to provide North America a strong advantage.

The Asia Pacific is evolving as a high-growth region as its digital growth is surging. As its Internet user base expands rapidly, mobile penetration rises, and e-commerce and financial markets boom, the region is facing an explosion in data volume. This is making the requirement for good data-wrangling tools a priority. In addition, governments and organizations in other nations such as China, India, and South Korea are investing heavily in AI and big data infrastructure, which is predicted to further accelerate regional market demand.

Recent Developments

October 2024: Technavio projected that the global data wrangling market would grow by USD 1.49 billion between 2024 and 2028, citing the expanding role of automation, AI, and big data analytics in enterprise decision-making. The report highlights how the increasing complexity of business data is pushing organizations to adopt powerful wrangling tools to simplify data transformation, comply with regulatory mandates, and improve time-to-insight metrics.

Table of Contents – Major Key Points

1. Introduction

2. Executive Summary

3. Research Methodology

4. Market Dynamics Impact Analysis

5. Statistical Insights and Trends Reporting

6. Competitive Landscape

7. Data Wrangling Market Segmentation, by Component

8. Data Wrangling Market Segmentation, by Deployment

9. Data Wrangling Market Segmentation, by Enterprise Size

10. Data Wrangling Market Segmentation, by End User

11. Regional Analysis

12. Company Profiles

13. Use Cases and Best Practices

14. Conclusion

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