Data Wrangling Market Report 2025

This report covers market characteristics, size and growth, segmentation, regional and country breakdowns, competitive landscape, market shares, trends and strategies for this market. It traces the market’s historic and forecast market growth by geography.

The data wrangling market size has grown rapidly in recent years. It will grow from $3.28 billion in 2024 to $3.8 billion in 2025 at a compound annual growth rate (CAGR) of 15.8%. The growth in the historic period can be attributed to the growing volumes of data, growing demand for advanced analytical algorithm, the rising growth in the healthcare sector, growing volume of data, data integration requirements.

The data wrangling market size is expected to see rapid growth in the next few years. It will grow to $6.83 billion in 2029 at a compound annual growth rate (CAGR) of 15.8%. The growth in the forecast period can be attributed to growing concern about data veracity, the rapid pace of data generation, cost reduction, data complexity, the rise of self-service analytics. Major trends in the forecast period include advancement in AI and big data technologies, time-intensive nature, automated data wrangling, data quality assurance, cloud-based data wrangling.

The escalating volumes of data are poised to propel the growth of the data wrangling market in the forthcoming years. Data volume, denoting the quantity of data generated, collected, processed, or stored within a specific system, organization, or dataset, is witnessing an upward trend fueled by the proliferation of connected devices, expanding internet usage, and heightened digitalization efforts. As data volumes surge, the importance of data wrangling intensifies, as it becomes increasingly critical to effectively clean, organize, and structure large datasets. This enables users to expedite decision-making processes and derive more precise insights from the vast troves of available data. According to insights from the Linux Foundation in December 2022, end-user organizations with storage capacities of up to 20 petabytes experienced annual data growth of 566 terabytes (TB) in 2021, escalating to 1,746 TB in 2022. Similarly, organizations with storage capacities of up to 25 petabytes witnessed annual data growth of 2,208 TB in 2022, marking a threefold increase compared to the growth observed in 2021 (700 TB). Consequently, the burgeoning volumes of data are serving as a catalyst for the expansion of the data wrangling market.

Key players within the data wrangling market are focusing on the development of innovative technological tools to gain a competitive advantage. Notable among these advancements are open-source data wrangling tools, designed to facilitate the cleaning, transformation, and preparation of raw data for analysis. For instance, in November 2022, Thinking Machines, a Philippines-based technology consulting company, unveiled GeoWrangler, an open-source data wrangling tool tailored for the swift processing of geospatial data. GeoWrangler aims to enhance the efficiency and accessibility of data wrangling processes by streamlining geospatial projects and augmenting data transformation capabilities. Leveraging Python libraries, GeoWrangler simplifies the handling of large datasets and facilitates the creation of transformation workflows for geospatial data. Engineered to support location intelligence and analytics, GeoWrangler accelerates the processing of geospatial information, thereby empowering users to extract valuable insights more effectively.

In January 2022, Alteryx Inc., a prominent US-based computer software company, completed the acquisition of Trifacta for $400 million. This strategic move is anticipated to bolster Alteryx's cloud data engineering capabilities and enrich its analytics solution offerings by incorporating robust data-wrangling functionalities. Trifacta, also headquartered in the US, specializes in providing data wrangling solutions tailored for data exploration and self-service data preparation.

Major companies operating in the data wrangling market are International Business Machines Corporation, Oracle Corporation, Cloud Software Group Inc., SAS Institute Inc., Hitachi Vantara, Teradata Corporation, Informatica, Alteryx Inc., Unifi, Altair Engineering Inc., Brillio, Talend, Cloudera Inc., DataRobot Inc., Dataiku, Datawatch Corporation, Datameer Inc., Rapid Insight Inc., Paxata Inc., Zaloni, Trifacta, Onedot, Cambridge Semantics Inc., Impetus Technologies Inc., CoolaData, Ideata Analytics.

North America was the largest region in the data wrangling market in 2024. Asia-Pacific is expected to be the fastest-growing region in the forecast period. The regions covered in the data wrangling market report are Asia-Pacific, Western Europe, Eastern Europe, North America, South America, Middle East, Africa. The countries covered in the data wrangling market report are Australia, Brazil, China, France, Germany, India, Indonesia, Japan, Russia, South Korea, UK, USA, Canada, Italy, Spain.

The data wrangling market consists of revenues earned by entities by providing services such as data cleaning, data transformation, data standardization, and data visualization. The market value includes the value of related goods sold by the service provider or included within the service offering. The data wrangling market also includes sales of data integration platforms, data preparation tools, high-performance servers, and Uninterruptible Power Supply (UPS). Values in this market are ‘factory gate’ values, that is, the value of goods sold by the manufacturers or creators of the goods, whether to other entities (including downstream manufacturers, wholesalers, distributors, and retailers) or directly to end customers. The value of goods in this market includes related services sold by the creators of the goods.

The market value is defined as the revenues that enterprises gain from the sale of goods and/or services within the specified market and geography through sales, grants, or donations in terms of the currency (in USD, unless otherwise specified).

Data wrangling is the process of cleaning, structuring, and organizing raw data into a suitable format for analysis. This involves tasks such as error removal, combining complex data sets, and making the data more accessible and analyzable. Data wrangling is crucial for streamlining the data preparation process, ultimately saving time and resources in the overall data analysis workflow.

The primary components of data wrangling are tools and services. Tools are software applications or programs designed to perform specific tasks related to data processing, analysis, or management. These tools can be deployed either in the cloud or on-premises, catering to various enterprise sizes, including small and medium-sized enterprises (SMEs) and large enterprises. Data wrangling finds application across diverse industries, such as information technology and telecommunications, retail, government, banking, financial services, and insurance (BFSI), healthcare, among others.

The data wrangling market research report is one of a series of new reports that provides data wrangling market statistics, including data wrangling industry global market size, regional shares, competitors with a data wrangling market share, detailed data wrangling market segments, market trends and opportunities, and any further data you may need to thrive in the data wrangling industry. This data wrangling market research report delivers a complete perspective of everything you need, with an in-depth analysis of the current and future scenario of the industry.

The revenues for a specified geography are consumption values that are revenues generated by organizations in the specified geography within the market, irrespective of where they are produced. It does not include revenues from resales along the supply chain, either further along the supply chain or as part of other products.

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