PUBLISHER: Stratistics Market Research Consulting | PRODUCT CODE: 1916661
PUBLISHER: Stratistics Market Research Consulting | PRODUCT CODE: 1916661
According to Stratistics MRC, the Global Data Quality Management Market is accounted for $2.3 billion in 2025 and is expected to reach $7.5 billion by 2032 growing at a CAGR of 18% during the forecast period. Data Quality Management (DQM) is the systematic process of ensuring that data is accurate, complete, consistent, timely, valid, and reliable across its entire lifecycle. It involves defining data quality standards, monitoring data against those standards, identifying errors or inconsistencies, and implementing corrective actions. DQM integrates policies, processes, technologies, and governance frameworks to maintain high-quality data for operational and analytical use. By improving data integrity and usability, Data Quality Management supports better decision-making, regulatory compliance, operational efficiency, and trust in data-driven insights across organizations and business functions.
Increasing demand for accurate business insights
Enterprises are prioritizing high-quality data to strengthen decision-making, predictive analytics, and customer engagement. Poor data quality often leads to inefficiencies, compliance risks, and missed opportunities, driving organizations to invest in advanced management platforms. Financial services, healthcare, and retail sectors are leading adoption due to their reliance on real-time analytics. Vendors are embedding AI-driven validation and cleansing tools to ensure accuracy and scalability. Rising demand for trusted insights is reinforcing the strategic importance of data quality frameworks. Increasing reliance on accurate business insights is propelling growth in the market.
Scarcity of skilled data quality professionals
Enterprises struggle to recruit and retain talent capable of managing complex data ecosystems. This shortage slows implementation of advanced platforms and increases reliance on external consultants. Training and certification programs require substantial investment, adding to operational costs. Smaller organizations face greater challenges in building dedicated data quality teams compared to larger enterprises. Vendors are attempting to address this gap through automation and self-service tools, but adoption remains uneven. Scarcity of skilled professionals is restraining widespread deployment of data quality management solutions despite strong demand.
Expansion in small and midsize enterprises
SMEs increasingly recognize the importance of clean, reliable data to compete in digital-first markets. Cloud-native and subscription-based solutions are lowering entry barriers for smaller firms. Vendors are tailoring offerings with cost-effective, scalable features to meet SME requirements. Integration with CRM, ERP, and analytics platforms is reinforcing adoption in this segment. Rising investment in digital transformation among SMEs is strengthening demand for data quality solutions. Expansion in small and midsize enterprises is fostering significant growth opportunities in the market.
Rising cybersecurity and data breach risks
Enterprises face growing threats from ransomware, phishing, and insider attacks targeting sensitive datasets. Breaches undermine trust in data ecosystems and increase compliance costs. Vendors must continuously update platforms with advanced encryption and monitoring features to mitigate risks. Smaller providers struggle to meet stringent security certifications compared to established players. Regulatory emphasis on data protection adds further complexity to deployments. Rising cybersecurity risks are restraining confidence and threatening consistent growth in the Data Quality Management market.
The Covid-19 pandemic accelerated demand for data quality management as enterprises shifted to remote work and digital-first strategies. On one hand, budget constraints delayed some large-scale deployments. On the other hand, surging demand for real-time analytics and secure collaboration boosted adoption. Organizations leveraged data quality platforms to ensure transparency and accuracy in distributed ecosystems. Vendors embedded cloud-native and AI-driven features to support remote operations during the crisis. The pandemic reinforced the importance of resilient, trusted data infrastructures. Overall, Covid-19 boosted awareness of data quality management as a strategic enabler of enterprise resilience.
The software platforms segment is expected to be the largest during the forecast period
The software platforms segment is expected to account for the largest market share during the forecast period driven by demand for integrated solutions that provide cleansing, validation, and governance capabilities. Enterprises rely on software platforms to strengthen compliance and improve operational efficiency. Vendors are embedding AI-driven automation into platforms to reduce manual intervention and improve scalability. Rising demand for hybrid and multi-cloud governance is reinforcing adoption of software-based solutions. Large enterprises view platforms as critical enablers of trusted analytics and digital transformation.
The secure data sharing & collaboration segment is expected to have the highest CAGR during the forecast period
Over the forecast period, the secure data sharing & collaboration segment is predicted to witness the highest growth rate supported by rising demand for privacy-preserving frameworks in distributed ecosystems. Enterprises increasingly require secure collaboration tools to share sensitive data across departments and partners. Vendors are embedding encryption, access control, and real-time monitoring into collaboration platforms. SMEs and startups particularly benefit from cost-effective, secure sharing solutions tailored to dynamic workflows. Growing reliance on digital-first strategies is reinforcing demand in this segment.
During the forecast period, the North America region is expected to hold the largest market share driven by mature IT infrastructure, strong regulatory frameworks, and early adoption of compliance-driven data platforms. Enterprises in the United States and Canada are leading investments in data quality management to meet mandates such as SOX, HIPAA, and state-level privacy laws. The presence of major technology vendors and cloud providers further strengthens regional dominance. Financial services, healthcare, and government agencies are particularly active in deploying platforms to ensure transparency and auditability. Rising demand for hybrid and multi-cloud governance is reinforcing adoption across large enterprises.
Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR fueled by rapid digitization, expanding cloud adoption, and government-led data governance initiatives. Countries such as India, China, and Singapore are investing heavily in data quality platforms to support large-scale digital ecosystems. Enterprises in the region are adopting secure collaboration and real-time validation tools to strengthen analytics in e-commerce, fintech, and telecom sectors. Local startups are deploying cost-effective, AI-driven solutions to meet growing demand from SMEs. Government programs promoting digital trust and cybersecurity are accelerating adoption across industries. Rising demand for transparency in cross-border data flows is reinforcing the importance of data quality platforms.
Key players in the market
Some of the key players in Data Quality Management Market include IBM Corporation, Microsoft Corporation, Oracle Corporation, SAP SE, SAS Institute Inc., Informatica Inc., Talend (QlikTech International AB), Teradata Corporation, Cloudera, Inc., Snowflake Inc., Databricks, Inc., Collibra NV, Alteryx, Inc., Precisely Inc. and Experian plc.
In May 2024, Microsoft acquired specific assets of Nuix's regulatory technology business to enhance its data discovery and compliance capabilities within the Purview ecosystem. This move directly strengthens Microsoft's data governance and quality offerings for regulated industries.
In April 2023, Oracle launched Oracle Database 23c, with its key feature "JSON Relational Duality," which provides a unified data model to eliminate the friction between JSON documents and relational tables. This innovation addresses a core data quality challenge by preventing disparate data representations and ensuring consistency across different application development paradigms.
Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.