The global data masking market size was valued at USD 691.81 million in 2022. It is estimated to reach USD 2358.9 million by 2031, growing at a CAGR of 14.6% during the forecast period (2023–2031). The data masking market growth is fueled by increased demand for data masking solutions across sectors.
Data masking is a technique to secure sensitive or confidential information by substituting, obscuring, or scrambling original data with fictional but plausible data. It is also known as data obfuscation or data anonymization. The primary purpose of data masking is to keep sensitive information safe and secure, even when it must be communicated with individuals or systems who do not need access to the underlying sensitive data. This strategy protects sensitive information against unwanted access or data breaches in various industries, including finance, healthcare, e-commerce, and software development.
The rise of organizational data and data protection from various internal and external exposures fuel the market's growth. Furthermore, an increase in private security and safety expenditure and an increase in cyber-attacks drive market expansion. On the other hand, the lack of professional technicians who can handle the program is impeding industry expansion. Furthermore, the growing demand for secure big data by dynamically masking sensitive information in Hadoop is expected to drive significant growth in the worldwide market for data masking.
Strict data protection requirements have substantially impacted the worldwide data masking business. Because of the necessity of complying with data privacy rules, enterprises have turned to data masking solutions to safeguard sensitive data from unwanted access while remaining compliant. The General Data Protection Regulation (GDPR) is one of the world's most important data privacy rules. It sets significant sanctions for noncompliance and mandates tight standards for the security of personal data. Despite masking's ability to eliminate sensitive data exposure, many businesses fail to follow the recommendations and risk breaches. The most well-known case involves the apparel store H&M, which was fined 35 million Euros for breaking GDPR standards. It was discovered that management had access to sensitive data such as religious convictions, personal concerns, etc. That is what GDPR seeks to avoid, and for this reason, data masking is essential.
However, heavily regulated businesses like banking and healthcare are already using data masking to comply with privacy laws. The Payment Card Industry Data Security Standard (PCI DSS) and the Health Insurance Portability and Accountability Act (HIPAA) are two examples. Furthermore, the EU-US Data Privacy Framework was implemented in July 2023 to ensure data can move freely (safely and legitimately) between the US and the EU. Hence, these regulations are projected to impact the data masking market trends during the forecast period.
Implementing data masking solutions can be complicated, especially in big and complex IT settings. It necessitates a thorough awareness of the organization's data landscape as well as the complexities of its IT systems. The intricacy of data masking technologies can stymie their uptake and deployment. According to Imperva, a single data masking technology utilized throughout the entire enterprise is impractical in large enterprises. Because of budget/business considerations, various IT administration methods, or different security/regulatory requirements, each line of business may be required to implement its own data masking. Furthermore, Gartner reports that data masking implementation initiatives can be resource-intensive, particularly in big and complex enterprises. This can result in prolonged project deadlines and increased implementation expenses.
Furthermore, data is frequently stored across platforms. In these circumstances, the data masking team must work with data stored or processed on various platforms (MySQL, Snowflake, Redshift, or Athena). Because the implementation of data masking is based on the data platform itself, and each platform requires different coding, inputs, and technology, the initial data masking method and maintenance in the long term is complicated.
Cloud services have become widely used across industries. With the migration to the cloud, enterprises require strong data security solutions to safeguard sensitive data in cloud settings. Data masking technologies for cloud security provide a huge business opportunity.
The organization is looking for a comprehensive cloud security plan with the growing necessity of protecting customer data and adhering to data protection requirements. This strategy includes data masking technologies that protect sensitive client data stored in the cloud while allowing the corporation to conduct its data analytics and business activities securely. As more businesses move their data and apps to cloud platforms, securing sensitive information within these settings becomes increasingly important. Data masking solutions that connect seamlessly with cloud services and provide robust data protection are well-positioned to address this rising need.
Study Period | 2019-2031 | CAGR | % |
Historical Period | 2019-2021 | Forecast Period | 2023-2031 |
Base Year | 2022 | Base Year Market Size | USD 691.81 Million |
Forecast Year | 2031 | Forecast Year Market Size | USD 2358.9 Million |
Largest Market | North America | Fastest Growing Market | Asia Pacific |
The global data masking market analysis is conducted in North America, Europe, Asia-Pacific, the Middle East and Africa, and Latin America.
North America is the most significant global market shareholder and is estimated to grow at an impressive healthy CAGR over the forecast period. The expansion of the data masking sector in North America over the assessment period can be attributed to the widespread acceptance of data masking methods in nations such as Canada and the United States. This is due to the presence of heavyweights such as Oracle Corporation, IBM Corporation, and numerous others, which are expected to drive the market throughout the forecast period.
In addition, one of the key causes driving demand for security measures such as data masking in the North American region is the increased digital storage of medical records and other healthcare data. Furthermore, the severe data privacy laws mandated by the governing authorities of various nations in the area to demand strong data protection measures are adding to market growth. Furthermore, the increased use of data masking in the e-commerce business to help secure critical consumer information such as credit card numbers and addresses is positively influencing the market in the region.
Asia-Pacific is anticipated to exhibit a healthy CAGR over the forecast period. According to the data masking market insights, the region is predicted to grow faster because developing countries like India and China are the world's two largest economies. The region's automotive sector has grown in recent years. The expansion of these industries was fueled by a significant population shift and a rise in disposable income, which resulted in increased demand. These two countries are growing faster, and many developmental efforts are being undertaken to establish new manufacturing businesses and product launches. All of these actions add to big data. Every day, much data is stored, which is critical. The increasing digitization of developing countries such as India, China, and Singapore has generated the most unstructured data.
Furthermore, the number of linked devices in China is increasing due to technical improvements. It has the world's largest Internet of Things (IoT) market. Furthermore, 5G and 5 G-enabled gadgets will enhance device interconnection tremendously. As a result, the number of connected devices grows, thus increasing the market's demand for security goods. As a result, other parties can more easily alter and mimic websites, and sensitive user data shared with the website can be captured by foreign intelligence services.
Europe is expected to grow rapidly during the predicted period. Germany, France, and the United Kingdom are the region's leaders. This is due to a significant investment in R&D in encryption technology to protect private data.
Additionally, the EU establishes guidelines for how any company managing the data of any EU citizen may store or process that data. Among many other criteria, Article 32 of the General Data Protection Regulation (GDPR) says that data masking shall be used to pseudonymize sensitive data to protect EU residents from data breaches and other unauthorized access. Compliance with the GDPR is in the best interests of a business, considering that disobedience can result in anything from a written warning to a fine of 20 million EUR.
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The global data masking market share is segmented based on component, Type, business function, and region.
The market is further segmented by component into Services, Software, Managed Services, and Professional Services.
Services hold the major share of the market. The data masking services market includes a wide range of options that aid in implementing, managing, and optimizing data masking systems. These services include consulting, training, maintenance, and support services. Services are critical for successfully assisting firms in successfully implementing data masking solutions, customizing them to their specific needs, and ensuring continuous support and maintenance. They control the industry because services provide specific knowledge and expertise in deploying data masking solutions. They have the abilities required to modify and tailor the solution to the specific demands of enterprises, providing excellent data security.
The key technology of data masking solutions is data masking software. It comprises the tools and platforms that allow enterprises to protect sensitive data using data masking techniques. Data masking software is the technology businesses use to conceal or anonymize sensitive data, ensuring its security and compliance with data privacy requirements.
The market is sub-segmented based on Type into Dynamic and Static Data Masking.
Dynamic Data Masking accounts for the largest share of the market. When data is accessed, dynamic data masking involves real-time data obfuscation or anonymization. It safeguards sensitive data while authorized users view or search it. Dynamic data masking often relies on policies and regulations to select who can see the true data and who sees disguised data. Dynamic data masking is frequently utilized when real-time data access is required, such as online applications, consumer portals, or data analytics platforms. It enables enterprises to provide controlled access to sensitive data without exposing it to all database users. In addition, only authorized users can see the real data, while unauthorized users or those with limited access capabilities see the masked data.
In contrast, static data masking entails permanently altering sensitive data in non-production situations. This is often done during data provisioning, which involves creating copies of production data for testing, development, or analytics. The sensitive data is replaced with masked or fictional data that retains the original material's format and structure.
The segment can be further bifurcated by business function into Sales and Marketing, Human Resources, Legal, Finance, and Operations.
Human Resources dominates the market. Human resource data masking is critical for protecting employee data, such as personally identifiable information (PII), payroll details, and performance assessments. HR departments can handle personnel records and other HR-related tasks more securely by concealing this information. Human resources teams use data masking to preserve employee privacy while conducting HR tasks such as payroll processing, performance evaluations, and background checks. It is critical to safeguard this information to protect employee privacy and comply with data protection rules. Data masking solutions provide a safe technique to disguise sensitive HR data while allowing it to be used for HR operations.
Data masking protects customer data, sales leads, and marketing campaign information in the sales and marketing function. It protects sensitive client information, such as contact information and transaction history, while allowing sales and marketing teams to use accurate data.