Data Wrangling Market to Reach USD 6.54 Billion by 2031 Amid Rising Enterprise Data Volumes and AI-Enabled Preparation Trends

Data Wrangling Market Overview and Growth Outlook 

According to Mordor Intelligence, the global data wrangling market size is expected to grow from USD 3.48 billion in 2025 to USD 3.87 billion in 2026 and is forecast to reach USD 6.54 billion by 2031, registering a CAGR of 11.08% during the forecast period. This data wrangling market forecast reflects growing enterprise reliance on analytics, increasing data volumes across sectors, and the shift from traditional ETL tools toward AI-enabled preparation platforms. Vendors are embedding generative AI features, low-code workflows, and automated lineage tracking to strengthen their data wrangling market share in competitive environments. 

As organizations manage structured, semi-structured, and unstructured datasets across hybrid environments, the data wrangling industry is becoming a core layer in analytics workflows. The market size continues to expand as enterprises prioritize faster time-to-insight, real-time dashboards, and governed data pipelines. Businesses across finance, marketing, operations, and IT are integrating preparation tools directly into cloud ecosystems to support self-service use cases while maintaining compliance.The current data wrangling market growth is shaped by demand for real-time analytics, regulatory pressure for data traceability, and the expansion of lakehouse architectures.  

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Key Data Wrangling Market Growth Drivers Adoption 

Rising Enterprise Data Volumes Across the Data Wrangling Industry: Organizations are generating data at unprecedented levels due to digitization, connected devices, and expanding cloud infrastructure. Manufacturing lines, financial transactions, telecom networks, and e-commerce platforms continuously produce high-frequency data streams. This surge directly supports data wrangling market growth, as legacy ETL systems struggle to handle diverse formats and scale requirements. Enterprises are investing in preparation platforms capable of managing local data sovereignty requirements while processing global datasets. The demand for unified transformation engines that can integrate logs, sensor data, and transactional tables is shaping core data wrangling market trends. 

AI Integration in the Data Wrangling Market: Artificial intelligence is becoming embedded within the data wrangling industry to automate transformation steps and improve data quality. Vendors are integrating generative assistants that suggest cleaning rules, detect schema drift, and recommend enrichment processes. These capabilities shorten manual preparation cycles and reduce dependency on technical specialists. AI-enabled preparation tools are influencing the data wrangling market size by expanding adoption beyond central IT teams. However, enterprises are balancing AI usage with hybrid deployment strategies to control compute costs, which remains a practical consideration within the data wrangling market forecast. 

Growing Demand for Self-Service Data Preparation: Business users increasingly expect access to governed data without relying solely on data engineering teams. Self-service tools with visual interfaces and point-and-click transformations are supporting marketing, sales, and finance functions. This shift is expanding data wrangling market share across departments rather than limiting usage to centralized analytics units. The rise of citizen data scientists and embedded preparation modules within business intelligence platforms reflects broader data wrangling market trends. Training initiatives and data literacy programs further support adoption within the data wrangling industry. 

Regulatory and Governance Requirements: Compliance requirements in banking, healthcare, and public sectors are reinforcing the need for lineage tracking and audit-ready transformation logs. Regulations such as BCBS frameworks and GDPR require structured governance practices. These mandates are strengthening the long-term data wrangling market growth trajectory by positioning preparation tools as compliance enablers rather than optional analytics add-ons. 

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Data Wrangling Market Segmentation  

By Data Type 

• Structured Data 
• Semi-Structured Data 
• Unstructured Data 

By Component 

• Software 
• Services 

By Business Function 

• Finance 
• Marketing and Sales 
• Operations 
• Other Enterprise Functions 

By End-User Industry 

• IT and Telecommunication 
• BFSI 
• Retail and E-Commerce 
• Other Industries 

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Key Players in the Data Wrangling Market 

• Alteryx, Inc. 
• Oracle Corporation 
• Teradata Corporation 
• SAS Institute Inc. 
• Altair Engineering Inc. 

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Conclusion 

The data wrangling market continues to expand as enterprises recognize the operational and compliance importance of structured data preparation. Rising data complexity, demand for real-time analytics, and AI-enabled transformation features are central to ongoing data wrangling market trends. While compute costs and limited awareness among small enterprises present short-term challenges, the overall data wrangling industry outlook remains positive.  

With increasing cross-functional adoption, enhanced governance requirements, and AI-assisted workflows, the data wrangling market growth trajectory reflects its role as a foundational layer within modern data strategies. As organizations embed preparation tools within cloud and lakehouse architectures, the data wrangling market size is expected to grow steadily through the forecast period. 

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