Global Data De-identification or Pseudonymity Software Market Research Report 2024

Publication ID:

PB505241905

Publication Date:

May 27, 2024

Pages:

Publisher:

MRRPB5

Countries:

Global [1]

USD 2,900.00

IT Services [2]

Computing & Electronics [3]

Description:

De-identification听is the process used to prevent someone's听personal identity听from being revealed.听
The global Data De-identification or Pseudonymity Software market was valued at US$ 403 million in 2023 and is anticipated to reach US$ 530.4 million by 2030, witnessing a CAGR of 4.3% during the forecast period 2024-2030.
The global market for data de-identification or pseudonymity software refers to the market for software solutions designed to anonymize or de-identify sensitive data. Data de-identification involves removing or altering personally identifiable information (PII) from datasets while maintaining the data's utility for analysis and research purposes. Pseudonymization involves replacing identifiable information with pseudonyms or aliases. With the rise in data breaches and privacy concerns, organizations across various industries are focusing on safeguarding sensitive data. Data de-identification or pseudonymity software is being adopted as a means to protect personal information while enabling data analysis and sharing for research, analytics, and other purposes. Regulatory Compliance and Data Protection Laws: Stringent data protection regulations, such as the General Data Protection Regulation (GDPR) in the European Union and the California Consumer Privacy Act (CCPA) in the United States, mandate the anonymization or pseudonymization of personal data. Organizations are adopting data de-identification software to achieve compliance with these regulations. Growing Adoption in Healthcare and Life Sciences: The healthcare and life sciences sectors handle vast amounts of sensitive personal data for research and analysis. Data de-identification or pseudonymity software is crucial in these industries to ensure patient privacy and comply with regulations such as the Health Insurance Portability and Accountability Act (HIPAA). These sectors are significant contributors to the demand for such software solutions. The development of advanced algorithms, such as differential privacy and generative models, has enhanced the capabilities of data de-identification and pseudonymity software. Machine learning techniques are being used to automate the process of anonymizing or pseudonymizing data, improving efficiency and accuracy. The adoption of cloud computing and the increasing need for data sharing among organizations has led to the demand for cloud-based data de-identification software. Cloud-based solutions offer scalability, flexibility, and ease of collaboration while maintaining data privacy.
This report aims to provide a comprehensive presentation of the global market for Data De-identification or Pseudonymity Software, with both quantitative and qualitative analysis, to help readers develop business/growth strategies, assess the market competitive situation, analyze their position in the current marketplace, and make informed business decisions regarding Data De-identification or Pseudonymity Software.
Report Scope
The Data De-identification or Pseudonymity Software market size, estimations, and forecasts are provided in terms of revenue ($ millions), considering 2023 as the base year, with history and forecast data for the period from 2019 to 2030. This report segments the global Data De-identification or Pseudonymity Software market comprehensively. Regional market sizes, concerning products by Type, by Application, and by players, are also provided.
For a more in-depth understanding of the market, the report provides profiles of the competitive landscape, key competitors, and their respective market ranks. The report also discusses technological trends and new product developments.
The report will help the Data De-identification or Pseudonymity Software companies, new entrants, and industry chain related companies in this market with information on the revenues, sales volume, and average price for the overall market and the sub-segments across the different segments, by company, by Type, by Application, and by regions.
Market Segmentation
By Company
TokenEx
Privacy Analytics
MENTISoftware
KI DESIGN
Thales Group
Semele
Imperva
ARCAD Software
Aircloak
AvePoint
BigID
Privitar
Orion Health
VGS Platform
Immuta
KIProtect Kodex
Segment by Type
Cloud-Based
On-Premises
Segment by Application
Individual
Enterprise
Others
By Region
North America
United States
Canada
Europe
Germany
France
UK
Italy
Russia
Nordic Countries
Rest of Europe
Asia-Pacific
China
Japan
South Korea
Southeast Asia
India
Australia
Rest of Asia
Latin America
Mexico
Brazil
Rest of Latin America
Middle East & Africa
Turkey
Saudi Arabia
UAE
Rest of MEA
Chapter Outline
Chapter 1: Introduces the report scope of the report, executive summary of different market segments (by Type, by Application, etc), including the market size of each market segment, future development potential, and so on. It offers a high-level view of the current state of the market and its likely evolution in the short to mid-term, and long term.
Chapter 2: Introduces executive summary of global market size, regional market size, this section also introduces the market dynamics, latest developments of the market, the driving factors and restrictive factors of the market, the challenges and risks faced by companies in the industry, and the analysis of relevant policies in the industry.
Chapter 3: Detailed analysis of Data De-identification or Pseudonymity Software companies鈥� competitive landscape, revenue market share, latest development plan, merger, and acquisition information, etc.
Chapter 4: Provides the analysis of various market segments by Type, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different market segments.
Chapter 5: Provides the analysis of various market segments by Application, covering the market size and development potential of each market segment, to help readers find the blue ocean market in different downstream markets.
Chapter 6, 7, 8, 9, 10: North America, Europe, Asia Pacific, Latin America, Middle East and Africa segment by country. It provides a quantitative analysis of the market size and development potential of each region and its main countries and introduces the market development, future development prospects, market space, and capacity of each country in the world.
Chapter 11: Provides profiles of key players, introducing the basic situation of the main companies in the market in detail, including product sales, revenue, price, gross margin, product introduction, recent development, etc.
Chapter 12: The main points and conclusions of the report.

Please Note - This is an on demand report and will be delivered in 2 business days (48 hours) post payment.

Table Of Contents:

1 Report Overview
1.1 Study Scope
1.2 Market Analysis by Type
1.2.1 Global Data De-identification or Pseudonymity Software Market Size Growth Rate by Type: 2019 VS 2023 VS 2030
1.2.2 Cloud-Based
1.2.3 On-Premises
1.3 Market by Application
1.3.1 Global Data De-identification or Pseudonymity Software Market Growth by Application: 2019 VS 2023 VS 2030
1.3.2 Individual
1.3.3 Enterprise
1.3.4 Others
1.4 Study Objectives
1.5 Years Considered
1.6 Years Considered
2 Global Growth Trends
2.1 Global Data De-identification or Pseudonymity Software Market Perspective (2019-2030)
2.2 Data De-identification or Pseudonymity Software Growth Trends by Region
2.2.1 Global Data De-identification or Pseudonymity Software Market Size by Region: 2019 VS 2023 VS 2030
2.2.2 Data De-identification or Pseudonymity Software Historic Market Size by Region (2019-2024)
2.2.3 Data De-identification or Pseudonymity Software Forecasted Market Size by Region (2025-2030)
2.3 Data De-identification or Pseudonymity Software Market Dynamics
2.3.1 Data De-identification or Pseudonymity Software Industry Trends
2.3.2 Data De-identification or Pseudonymity Software Market Drivers
2.3.3 Data De-identification or Pseudonymity Software Market Challenges
2.3.4 Data De-identification or Pseudonymity Software Market Restraints
3 Competition Landscape by Key Players
3.1 Global Top Data De-identification or Pseudonymity Software Players by Revenue
3.1.1 Global Top Data De-identification or Pseudonymity Software Players by Revenue (2019-2024)
3.1.2 Global Data De-identification or Pseudonymity Software Revenue Market Share by Players (2019-2024)
3.2 Global Data De-identification or Pseudonymity Software Market Share by Company Type (Tier 1, Tier 2, and Tier 3)
3.3 Players Covered: Ranking by Data De-identification or Pseudonymity Software Revenue
3.4 Global Data De-identification or Pseudonymity Software Market Concentration Ratio
3.4.1 Global Data De-identification or Pseudonymity Software Market Concentration Ratio (CR5 and HHI)
3.4.2 Global Top 10 and Top 5 Companies by Data De-identification or Pseudonymity Software Revenue in 2023
3.5 Data De-identification or Pseudonymity Software Key Players Head office and Area Served
3.6 Key Players Data De-identification or Pseudonymity Software Product Solution and Service
3.7 Date of Enter into Data De-identification or Pseudonymity Software Market
3.8 Mergers & Acquisitions, Expansion Plans
4 Data De-identification or Pseudonymity Software Breakdown Data by Type
4.1 Global Data De-identification or Pseudonymity Software Historic Market Size by Type (2019-2024)
4.2 Global Data De-identification or Pseudonymity Software Forecasted Market Size by Type (2025-2030)
5 Data De-identification or Pseudonymity Software Breakdown Data by Application
5.1 Global Data De-identification or Pseudonymity Software Historic Market Size by Application (2019-2024)
5.2 Global Data De-identification or Pseudonymity Software Forecasted Market Size by Application (2025-2030)
6 North America
6.1 North America Data De-identification or Pseudonymity Software Market Size (2019-2030)
6.2 North America Data De-identification or Pseudonymity Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
6.3 North America Data De-identification or Pseudonymity Software Market Size by Country (2019-2024)
6.4 North America Data De-identification or Pseudonymity Software Market Size by Country (2025-2030)
6.5 United States
6.6 Canada
7 Europe
7.1 Europe Data De-identification or Pseudonymity Software Market Size (2019-2030)
7.2 Europe Data De-identification or Pseudonymity Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
7.3 Europe Data De-identification or Pseudonymity Software Market Size by Country (2019-2024)
7.4 Europe Data De-identification or Pseudonymity Software Market Size by Country (2025-2030)
7.5 Germany
7.6 France
7.7 U.K.
7.8 Italy
7.9 Russia
7.10 Nordic Countries
8 Asia-Pacific
8.1 Asia-Pacific Data De-identification or Pseudonymity Software Market Size (2019-2030)
8.2 Asia-Pacific Data De-identification or Pseudonymity Software Market Growth Rate by Region: 2019 VS 2023 VS 2030
8.3 Asia-Pacific Data De-identification or Pseudonymity Software Market Size by Region (2019-2024)
8.4 Asia-Pacific Data De-identification or Pseudonymity Software Market Size by Region (2025-2030)
8.5 China
8.6 Japan
8.7 South Korea
8.8 Southeast Asia
8.9 India
8.10 Australia
9 Latin America
9.1 Latin America Data De-identification or Pseudonymity Software Market Size (2019-2030)
9.2 Latin America Data De-identification or Pseudonymity Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
9.3 Latin America Data De-identification or Pseudonymity Software Market Size by Country (2019-2024)
9.4 Latin America Data De-identification or Pseudonymity Software Market Size by Country (2025-2030)
9.5 Mexico
9.6 Brazil
10 Middle East & Africa
10.1 Middle East & Africa Data De-identification or Pseudonymity Software Market Size (2019-2030)
10.2 Middle East & Africa Data De-identification or Pseudonymity Software Market Growth Rate by Country: 2019 VS 2023 VS 2030
10.3 Middle East & Africa Data De-identification or Pseudonymity Software Market Size by Country (2019-2024)
10.4 Middle East & Africa Data De-identification or Pseudonymity Software Market Size by Country (2025-2030)
10.5 Turkey
10.6 Saudi Arabia
10.7 UAE
11 Key Players Profiles
11.1 TokenEx
11.1.1 TokenEx Company Detail
11.1.2 TokenEx Business Overview
11.1.3 TokenEx Data De-identification or Pseudonymity Software Introduction
11.1.4 TokenEx Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.1.5 TokenEx Recent Development
11.2 Privacy Analytics
11.2.1 Privacy Analytics Company Detail
11.2.2 Privacy Analytics Business Overview
11.2.3 Privacy Analytics Data De-identification or Pseudonymity Software Introduction
11.2.4 Privacy Analytics Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.2.5 Privacy Analytics Recent Development
11.3 MENTISoftware
11.3.1 MENTISoftware Company Detail
11.3.2 MENTISoftware Business Overview
11.3.3 MENTISoftware Data De-identification or Pseudonymity Software Introduction
11.3.4 MENTISoftware Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.3.5 MENTISoftware Recent Development
11.4 KI DESIGN
11.4.1 KI DESIGN Company Detail
11.4.2 KI DESIGN Business Overview
11.4.3 KI DESIGN Data De-identification or Pseudonymity Software Introduction
11.4.4 KI DESIGN Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.4.5 KI DESIGN Recent Development
11.5 Thales Group
11.5.1 Thales Group Company Detail
11.5.2 Thales Group Business Overview
11.5.3 Thales Group Data De-identification or Pseudonymity Software Introduction
11.5.4 Thales Group Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.5.5 Thales Group Recent Development
11.6 Semele
11.6.1 Semele Company Detail
11.6.2 Semele Business Overview
11.6.3 Semele Data De-identification or Pseudonymity Software Introduction
11.6.4 Semele Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.6.5 Semele Recent Development
11.7 Imperva
11.7.1 Imperva Company Detail
11.7.2 Imperva Business Overview
11.7.3 Imperva Data De-identification or Pseudonymity Software Introduction
11.7.4 Imperva Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.7.5 Imperva Recent Development
11.8 ARCAD Software
11.8.1 ARCAD Software Company Detail
11.8.2 ARCAD Software Business Overview
11.8.3 ARCAD Software Data De-identification or Pseudonymity Software Introduction
11.8.4 ARCAD Software Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.8.5 ARCAD Software Recent Development
11.9 Aircloak
11.9.1 Aircloak Company Detail
11.9.2 Aircloak Business Overview
11.9.3 Aircloak Data De-identification or Pseudonymity Software Introduction
11.9.4 Aircloak Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.9.5 Aircloak Recent Development
11.10 AvePoint
11.10.1 AvePoint Company Detail
11.10.2 AvePoint Business Overview
11.10.3 AvePoint Data De-identification or Pseudonymity Software Introduction
11.10.4 AvePoint Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.10.5 AvePoint Recent Development
11.11 BigID
11.11.1 BigID Company Detail
11.11.2 BigID Business Overview
11.11.3 BigID Data De-identification or Pseudonymity Software Introduction
11.11.4 BigID Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.11.5 BigID Recent Development
11.12 Privitar
11.12.1 Privitar Company Detail
11.12.2 Privitar Business Overview
11.12.3 Privitar Data De-identification or Pseudonymity Software Introduction
11.12.4 Privitar Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.12.5 Privitar Recent Development
11.13 Orion Health
11.13.1 Orion Health Company Detail
11.13.2 Orion Health Business Overview
11.13.3 Orion Health Data De-identification or Pseudonymity Software Introduction
11.13.4 Orion Health Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.13.5 Orion Health Recent Development
11.14 VGS Platform
11.14.1 VGS Platform Company Detail
11.14.2 VGS Platform Business Overview
11.14.3 VGS Platform Data De-identification or Pseudonymity Software Introduction
11.14.4 VGS Platform Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.14.5 VGS Platform Recent Development
11.15 Immuta
11.15.1 Immuta Company Detail
11.15.2 Immuta Business Overview
11.15.3 Immuta Data De-identification or Pseudonymity Software Introduction
11.15.4 Immuta Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.15.5 Immuta Recent Development
11.16 KIProtect Kodex
11.16.1 KIProtect Kodex Company Detail
11.16.2 KIProtect Kodex Business Overview
11.16.3 KIProtect Kodex Data De-identification or Pseudonymity Software Introduction
11.16.4 KIProtect Kodex Revenue in Data De-identification or Pseudonymity Software Business (2019-2024)
11.16.5 KIProtect Kodex Recent Development
12 Analyst's Viewpoints/Conclusions
13 Appendix
13.1 Research Methodology
13.1.1 Methodology/Research Approach
13.1.2 Data Source
13.2 Disclaimer
13.3 Author Details

Companies Mentioned:

TokenEx
Privacy Analytics
MENTISoftware
KI DESIGN
Thales Group
Semele
Imperva
ARCAD Software
Aircloak
AvePoint
BigID
Privitar
Orion Health
VGS Platform
Immuta
KIProtect Kodex

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