Data Masking Market Size, Segments, Growth and Trends by Forecast to 2023
Market Highlights:
In order to
sustain the competitive market, the business enterprises are evolving new
techniques to improve their operational functionalities. Thus, the business
enterprises require experimental setup to stimulate new techniques that would
be compatible with the prevailing technology. Data masking is a secured
technique to clone the essential data without any data breach. However,
auditing of data after obfuscation is a challenging task which is expected to
hinder the growth of data masking market over the forecast period.
The data masking
market is segmented by type, component, deployment, business function,
organization size, and end user.
By type, the Data Masking Market is sub-segmented into static data masking and dynamic data masking. The
component segment consists of software and services. The service sub-segment is
further divided into professional and managed services. Based on deployment,
the data masking market is categorized into on-premise and on-cloud.
Furthermore, on the basis of functional business, the data masking is
classified into marketing & sales, finance, human resource, operations,
legal, and others. Additionally, depending on the size of the organization the
market is bifurcated into small & medium enterprise and large enterprises.
The end users of
data masking is segmented into BFSI, healthcare & life sciences, retail
& ecommerce, telecommunications
& IT, government & defense, media & entertainment, manufacturing,
and others.
Major Key Players:
·
Oracle
Corporation (U.S.)
·
Compuware
Corporation (U.S.)
·
Innovative
Routines International, Inc (U.S.)
·
Delphix
Corp (U.S.)
·
IBM
Corporation (U.S.)
·
Net
2000 Ltd. (U.S.)
·
Camouflage
Software Inc. (Canada)
·
ARCAD
Software (France),
·
Informatica
Corporation, (U.S.)
·
Hewlett
Packard Enterprise Company. (U.S.)
·
Solix
Technologies, Inc (U.S.),
·
Ekobit
d.o.o. (Croatia),
·
CA
Technologies (U.S.)
Regional Analysis:
Geographically,
the data masking market is categorized into four different regions such as
North America, Asia Pacific, Europe and the Rest of the World.
Asia Pacific
region is expected to be the fastest growing region in data masking market.
This is attributed to rising demand for e-commerce and retail sector which
increases the demand for secured online transactions which eventually expected
to drive data masking market over the review period.
North America is
expected to be a prominent region in the data masking market over forecast
period. The U.S. and Canada are the leading countries in the region owing to
highly advanced technological infrastructure which has made them early adopters
of technology.
Segmentation:
The data masking market is differentiated by type, component,
deployment, business function, organization size, and end user.
By type, the data masking market is sub-segmented into static data
masking and dynamic data masking. The component segment consists of software
and services. The service sub-segment is further divided into professional and
managed services. Based on the deployment, data masking market is categorized
into on-premise and on-cloud. Furthermore, on the basis of functional business,
data masking market is classified as marketing & sales, finance, human resource,
operations, legal, and others. Additionally, depending on the size of the
organization the market is bifurcated into small & medium enterprise and
large enterprises.
The end-users for data masking is segmented as BFSI, healthcare &
life sciences, retail & ecommerce, IT & telecommunications,
government & defense, media & entertainment, manufacturing, and others.
Target Audience:
- Research Firms.
- Government Agencies
- Data Masking Service Providers
- Associations, organizations, forums and alliances related to Data
Masking
- Government bodies such as regulating authorities and policy makers
- Industry associations
- Market research and consulting firm
- Data masking application builders
- Independent Software Vendors (ISVs)
- Analytics consulting companies

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