Data Wrangling Market Size (2024 - 2029)

Data Wrangling Market Analysis

The Data Wrangling Market size is estimated at USD 3.41 billion in 2024, and is expected to reach USD 5.75 billion by 2029, growing at a CAGR of 11.03% during the forecast period (2024-2029).

The creation of various automated technologies has already enhanced and improved the data-wrangling procedure. The industry would create more complex AI solutions during the forecast period to assist the processes of data wrangling and data analysis.

• The adoption of sophisticated analytics algorithms to choose insights that might revolutionize a business entity results from the rapid development in the quantity and reliability of data collected throughout many industrial verticals. Massive amounts of unstructured data have also been produced due to the surge in Big Data usage. Applications for iterative and interactive data wrangling may identify distributions and inconsistencies and suggest process improvement.
• Data manipulation can offer statistical insights into the metadata by making the information more consistent. Increased metadata consistency makes it possible for automated technologies to examine the data more quickly and precisely, frequently leading to these findings. Data wrangling would clean the information to enable a model to operate without problems, mainly in developing a model about expected market performance.
• Businesses are increasingly using data wrangling for real-time forecasting and monitoring of numerous events that may impact their performance. The market for data wrangling is expanding due to the potential to mitigate risks by executing complicated judgments concerning unplanned occurrences, such as cyberattacks and other emergencies. Also, as more cyberattacks occur, there is a growing demand for data wrangling since it makes data simpler to find and recover.
• Growing concerns about information loss and theft, expanding Bring Your Own Device (BYOD) trends, and business mobility are just a few factors that are significantly accelerating the growth of the data wrangling market.The industry of data wrangling is predicted to benefit significantly from advances in edge computing.
• However, issues with data quality are limiting the market's ability to expand.The data-wrangling industry is anticipated to face challenges due to a lack of readiness to switch from conventional ETL tools to cutting-edge automated technologies. Further, one of the key obstacles to this market's expansion is the lack of knowledge about data-wrangling tools among small and medium-sized businesses.
• The COVID-19 epidemic brought on a considerable data influx. Technological firms and data aggregators exploited local data from cell towers and mobile applications to impose social segregation and close the gaps using dashboards that monitored and tracked contacts. Applications predicted hospital requirements and epidemic burden using Bluetooth, modeling efforts, and geolocation services. As a result of the flawed data produced throughout this procedure, millions of people were expected to be negatively impacted. Data wrangling is used to clean, arrange, and enhance raw data into the appropriate format for users to make better decisions more quickly and accurately. As a result, COVID-19's requirement for data wrangling provided market potential for expansion.

Data Wrangling Industry Segmentation

Data wrangling is defined as the process of preparing raw data for analysis by cleaning, arranging, and converting it into the required format. Data wrangling, also known as data cleaning or data munging, helps organizations handle more complicated data in less time, create more accurate results, and make better decisions.

The data wrangling market is segmented by component (tool, service), deployment (cloud-based, on-premises), enterprise type (large, small, and medium-sized), end-user industry (IT and telecommunication, retail, government, BFSI, and healthcare), and geography (North America, Europe, Asia-Pacific, Latin America, and the Middle East and Africa).

The market sizes and forecasts are provided in terms of value (USD) for all the above segments.