Asia Pacific Data Masking Market By Business Function (Legal & Finance Data Masking, Sales & Marketing Data Masking, HR & Operations Data Masking), Type (Static Data Masking, Dynamic Data Masking), Deployment (On-Premise, Cloud), Vertical (Retail & Ecommerce, Government, BFSI, Healthcare & Lifesciences, Media & Entertainment)
Special Offering: Industry Insights | Market Trends | Highest number of Tables | 24/7 Analyst Support
Get in-depth analysis of the COVID-19 impact on the Asia Pacific Data Masking Market
The Asia Pacific Data Masking Market would witness market growth of 16.4% CAGR during the forecast period (2017 ? 2023). With growing volume of data, the need for solutions to protect sensitive data significantly increases. The data flow has witnessed significant growth due to the adoption of IoT and remote sensors in various industrial verticals. There is a renewed focus on enhancing software and services which could assist companies in masking data. Data masking protects data without altering the content or the nature of data, and therefore, mitigating the risks related to data. Based on Business Function, the market report segments the market into Legal & Finance, Sales & Marketing, HR & Operations, and Others. Based on Type, the market report segments the market into Static and Dynamic. Based on Deployment Type, the market report segments the market into On-Premise and Cloud. Based on Vertical, the Data Masking market segments the market into Retail & Ecommerce, Government, BFSI, Healthcare & Lifesciences, Media & Entertainment, and Others. Based on Countries, the Data Masking market segments the market into China, Japan, India, South Korea, Singapore, Malaysia, and Rest of Asia Pacific. The market research report covers the analysis of key stake holders of the Data Masking Market. Key companies profiled in the report include IBM Corporation, CA Technologies, Inc., Informatica, Micro Focus (Formerly Hpe Software), Oracle Corporation, Mentis Technology, Compuware Corporation, Solix Technologies, Inc., and Delphix.