Data Wrangling Market to Expand by USD 1.49 Billion from 2024-2028, Benefits of Data Wrangling Solutions Drive Revenue, Report on AI-Redefined Market Landscape - Technavio

NEW YORK, Nov. 7, 2024 /PRNewswire/ -- Report with market evolution powered by AI - The global data wrangling market  size is estimated to grow by USD 1.49 billion from 2024-2028, according to Technavio. The market is estimated to grow at a CAGR of  14.8%  during the forecast period. Numerous benefits provided by data wrangling solutions is driving market growth, with a trend towards rising need of technology in healthcare sector. However, lack of awareness of data wrangling tools among smes  poses a challenge.Key market players include Altair Engineering Inc., Alteryx Inc., Dataiku Inc., DataRobot Inc., Dell Technologies Inc., eXalt Solutions Inc., Hitachi Ltd., Ideata Analytics, Impetus Technologies Inc., Innovative Routines International (IRI) Inc., International Business Machines Corp., Medallia Inc., Microsoft Corp., Oracle Corp., Rapid Insight Inc., SAS Institute Inc., Teradata Corp., TIBCO Software Inc., Wipro Ltd., and Zoho Corp. Pvt. Ltd..

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The healthcare sector encounters numerous challenges, such as managing disease outbreaks and enhancing operational efficiency. With an influx of daily data, including patient details, medical history, treatment records, and payment information, healthcare organizations require solutions to prepare, clean, and format this data for insightful analysis. Data wrangling plays a vital role in this process by transforming raw data into structured formats. During the COVID-19 pandemic, data wrangling tools became essential for cleaning and organizing patient data, enabling quick decision-making. As healthcare adopts advanced technologies like AI and machine learning, the demand for data wrangling solutions increases, as these technologies rely on clean, structured data for accurate predictions and insights. The growing focus on personalized medicine and patient-centric care necessitates integrating diverse data sources, further emphasizing the importance of data wrangling for managing complexity and improving decision-making, patient outcomes, and healthcare system efficiency. As healthcare data volume expands, data wrangling's role in driving innovation and quality care will continue to grow, positively impacting the market's growth during the forecast period. 

In today's digital world, businesses are generating and collecting massive amounts of data. This data needs to be processed and transformed into valuable insights to drive business growth. Trends like digital transformation, big data analytics, and e-commerce are leading the charge in data usage. Data integration, structuring, and transformation are key areas of focus for professional services and consulting firms. Data security is paramount, with encryption, access controls, and data protection laws ensuring data privacy. Technology hubs are emerging as centers for innovation in data munging, information mapping, and enterprise mobility. Industries like healthcare, telecommunications, financial services, and insurance are leveraging cloud solutions for data analysis. Data quality, edge computing, and financial services are also seeing significant investment. Anomalies in data require attention, with cloud-based analytics and data lineage tools helping to identify and address them. Metadata management, data cataloging, and data cleaning are essential for data unification and self-service data preparation. Big data, digitalization, finance, IoT devices, smart cities, and life sciences are all driving the need for data analysis tools. Data loss prevention is a critical concern, with firms investing in solutions to mitigate risk. Overall, the data wrangling market is thriving, with innovation and growth expected to continue. 

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•         Data wrangling refers to the process of extracting valuable insights from raw data using advanced technologies like machine learning and big data analytics. Small and medium-sized enterprises (SMEs) primarily use conventional Extract, Transform, Load (ETL) tools due to their user-friendly interface and affordability. However, these tools lack the necessary functionality for SMEs to fully adopt data wrangling technology, limiting its growth potential. Moreover, in developing countries such as China and India, where there is a high concentration of businesses, the lack of awareness about data wrangling techniques among SMEs will hinder market expansion during the forecast period.

•         In today's business world, managing data effectively is crucial for success. However, data wrangling presents several challenges for organizations. These include information mapping to connect data from various sources, enterprise mobility to access data on-the-go, ensuring data quality, and implementing edge computing for real-time analysis. Industries like financial services, insurance, and life sciences face unique data challenges. Cloud solutions offer scalability and flexibility, but data loss and security are major concerns. Data analytics tools help make sense of big data, but data lineage, metadata management, and data cataloging are essential for maintaining data accuracy. Self-service data preparation is important for enabling business users, while AI and machine learning require data cleaning and unification. Data management, data preparation, and real-time analysis are key for IT and telecom, while data governance is crucial for large enterprises and SMEs alike. IoT devices and smart cities generate vast amounts of data, requiring multi-cloud strategies and hybrid cloud solutions. Data analytics is the end goal, but data loss, data security, and data privacy are ongoing challenges that must be addressed.

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This data wrangling market report extensively covers market segmentation by

1. Sector 
• 1.1 BFSI
• 1.2 Government and public sector
• 1.3 Healthcare
• 1.4 Others
2. Geography 
• 2.1 North America
• 2.2 Europe
• 2.3 APAC
• 2.4 Middle East and Africa
• 2.5 South America

1.1 BFSI-  The BFSI sector's reliance on data wrangling has grown significantly due to the digitization of services and the resulting generation of large volumes of data. Data wranglers optimize operational processes and provide insights to agents for effective online customer interaction. They reduce data preparation time by more than 15 times, enabling a 360-degree client view. With massive data generation, proper management is crucial to prevent unwanted events like data breaches. The Royal Bank of Scotland, serving over 30 million customers globally, uses data wranglers to extract insights from unstructured data, particularly web chats. These factors are driving the demand for data wrangling solutions in the BFSI sector, ensuring secure and efficient data management.

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The Data Wrangling Market is experiencing significant growth due to the increasing volume, variety, and velocity of data being generated across industries. Data loss and theft continue to be major concerns, driving the need for data management and security solutions. Artificial intelligence and machine learning are revolutionizing data analysis by automating data preparation and enabling real-time analysis. Cloud-based solutions and multi-cloud strategies are becoming increasingly popular for data management, offering flexibility and scalability. Data munging, information mapping, and data cleaning are essential data preparation tasks for ensuring data quality. Finance, insurance, and IoT devices are generating massive amounts of data, making data unification and self-service data preparation crucial. Big data and real-time analysis are transforming industries like finance and smart cities, requiring edge computing to process data at the source. Data analytics is at the heart of these trends, enabling businesses to gain valuable insights and make informed decisions.

The Data Wrangling Market is experiencing significant growth due to the increasing demand for Artificial Intelligence (AI) and Machine Learning (ML) applications in Data Analytics. Businesses are focusing on Data Management and Preparation to derive valuable insights from their data. Real-time analysis is becoming essential for Large Enterprises and SMEs in IT and Telecom, Finance, Healthcare, Telecommunications, E-commerce, and other sectors. On-premises and Cloud-based solutions are popular for Data Management, with Multi-cloud strategies and Hybrid cloud gaining traction. Data Security and Governance are top priorities, with Digital Transformation driving the adoption of Big Data Analytics, Data Integration, and Data Transformation. Data Structuring, Professional Services, and Consulting are crucial for Data Encryption, Access Controls, and Data Protection Laws. Technology hubs are investing in Data Analytics Tools and Edge Computing to support Digitalization and IoT devices. Data Quality, Anomalies, and Cloud-based Analytics are key areas of focus, along with Data Lineage, Metadata Management, Data Cataloging, Data Cleaning, and Data Unification. Self-service Data Preparation and Big Data are transforming industries such as Life Sciences, Finance, and Insurance. Data Loss prevention is a growing concern, with a need for advanced Data Analytics and AI-driven solutions. The market is expected to continue growing, driven by the increasing importance of Data in the Digital Age.

1 Executive Summary
2 Market Landscape
3 Market Sizing
4 Historic Market Size
5 Five Forces Analysis
6 Market Segmentation

• Sector
• BFSI
• Government And Public Sector
• Healthcare
• Others
• Geography
• North America
• Europe
• APAC
• Middle East And Africa
• South America

7 Customer Landscape
8 Geographic Landscape
9 Drivers, Challenges, and Trends
10 Company Landscape
11 Company Analysis
12 Appendix

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SOURCE Technavio