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Global Master Data Management Market to reach USD 38.6 billion by 2028.

Global Master Data Management Market Size study, by Component (Solution, Services, Consulting Services, Integration Services, Training & Support Services), by Organization Size (SMEs & Large Enterprises), by Deployment Mode (Cloud & On-premises), by Vertical (BFSI Government, Retail, IT & Telecom, Manufacturing, Energy & Utilities, Healthcare, Other Verticals) and Regional Forecasts 2022-2028

Product Code: ICTEITS-18125512
Publish Date: 15-06-2022
Page: 200

Global Master Data Management Market is valued at approximately USD 14.5 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 15% over the forecast period 2022-2028. Master data management (or MDM) refers to various solutions, services, and standards that assist organisations in managing their master data. Master data consists of secret and crucial company data on customers, goods, financial transactions, suppliers, and others. The emergence of MDM has enabled businesses to collect and manage master data, which can then be used for data analytics and effective decision-making. Some of the key factors driving the MDM market include the critical need to install centrally placed or controlled data, increasing need for verification and compliance, and escalating demand for outstanding business performance and data quality. According to BI-SURVEY.com, master data and data quality management were particularly essential in Northern Europe and among IT users in 2017. However, current concerns about data security, as well as a lack of understanding of the benefits of data management solutions, are the primary factors impeding the growth of the master data management market size. Nonetheless, the adoption of integrated vendor solutions is expected to present service providers with new options. Master data management companies have used a variety of organic and inorganic growth tactics to expand their products in the market, including new product launches, product upgrades, partnerships and agreements, business expansions, and mergers and acquisitions. Oracle Enterprise Data Management will be updated in February 2022. Validation errors can now be downloaded to an MS Excel file with the latest release. This allows EDM users to get help or feedback from others. The file contains data like nodes, attributes, relationships, and failure messages. Similarly, Broadcom updates its CA IDMS in April 2022; the new update includes DML modification statements that alter the database’s record occurrences. Users can delete a record from the database’s database and link a member record to a set.

The key regions considered for the global Master Data Management market study include Asia Pacific, North America, Europe, Latin America, and Rest of the World. In the master data management market, North America is predicted to hold the greatest share. The rising technological improvements in the region are key factors encouraging the growth of the MDM market in North America. Market growth is projected to be aided by the growing number of MDM players across regions. Whereas, during the forecast period, APAC is expected to have the highest CAGR. Because of the influx of major international companies, the region is expanding rapidly, and many new entrepreneur setups are using cloud-based MDM solutions, which help them improve operational efficiency, streamline operations, and improve customer experience. In the Master Data Management Market, China, Japan, and India all have a lot of room to grow.

Major market players included in this report are:
IBM
Oracle
SAP
SAS
TIBCO Software
Informatica
Talend
Cloudera
Riversand
Broadcom
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:
By Component:
Solution
Services
Consulting Services
Integration Services
Training & Support Services
By Deployment Mode:
Cloud
On-premises
By Organization Size:
SMEs
Large Enterprises
By Verticals:
BFSI
Government
Retail
IT & Telecom
Manufacturing
Energy & Utilities
Healthcare
Other Verticals

By Region:
North America
U.S.
Canada
Europe
UK
Germany
France
Spain
Italy
ROE

Asia Pacific
China
India
Japan
Australia
South Korea
RoAPAC
Latin America
Brazil
Mexico
Rest of the World

Furthermore, years considered for the study are as follows:

Historical year – 2018, 2019, 2020
Base year – 2021
Forecast period – 2022 to 2028

Target Audience of the Global Master Data Management Market in Market Study:

Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2028 (USD Billion )
1.2.1. Master Data Management Market, by Region, 2020-2028 (USD Billion )
1.2.2. Master Data Management Market, by Component,2020-2028 (USD Billion )
1.2.3. Master Data Management Market, by Deployment Mode,2020-2028 (USD Billion )
1.2.4. Master Data Management Market, by Organization Size,2020-2028 (USD Billion )
1.2.5. Master Data Management Market, by Verticals,2020-2028 (USD Billion )
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Master Data Management Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Scope of the Study
2.2.2. Industry Evolution
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Master Data Management Market Dynamics
3.1. Master Data Management Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Increase in the use of data quality tools for data management
3.1.1.2. Rising need for compliance
3.1.2. Market Challenges
3.1.2.1. Data security concerns
3.1.3. Market Opportunities
3.1.3.1. Incorporation of new technologies with master data management
Chapter 4. Global Master Data Management MarketIndustry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.1.6. Futuristic Approach to Porter’s 5 Force Model (2018-2028)
4.2. PEST Analysis
4.2.1. Political
4.2.2. Economical
4.2.3. Social
4.2.4. Technological
4.3. Investment Adoption Model
4.4. Analyst Recommendation & Conclusion
4.5. Top investment opportunity
4.6. Top winning strategies
Chapter 5. Risk Assessment: COVID-19 Impact
5.1.1. Assessment of the overall impact of COVID-19 on the industry
5.1.2. Pre COVID-19 and post COVID-19 market scenario
Chapter 6. Global Master Data Management Market, by Component
6.1. Market Snapshot
6.2. Global Master Data Management Market by Component, Performance – Potential Analysis
6.3. Global Master Data Management Market Estimates & Forecasts by Component,2018-2028 (USD Billion )
6.4. Master Data Management Market, Sub Segment Analysis
6.4.1. Solution
6.4.2. Services
6.4.3. Consulting Services
6.4.4. Integration Services
6.4.5. Training & Support Services
Chapter 7. Global Master Data Management Market, by Deployment Mode
7.1. Market Snapshot
7.2. Global Master Data Management Market by Deployment Mode, Performance – Potential Analysis
7.3. Global Master Data Management Market Estimates & Forecasts by Deployment Mode,2018-2028 (USD Billion )
7.4. Master Data Management Market, Sub Segment Analysis
7.4.1. Cloud
7.4.2. On-premises
Chapter 8. Global Master Data Management Market, by Organization Size
8.1. Market Snapshot
8.2. Global Master Data Management Market by Organization Size, Performance – Potential Analysis
8.3. Global Master Data Management Market Estimates & Forecasts by Organization Size,2018-2028 (USD Billion )
8.4. Master Data Management Market, Sub Segment Analysis
8.4.1. SMEs
8.4.2. Large Enterprises
Chapter 9. Global Master Data Management Market, by Verticals
9.1. Market Snapshot
9.2. Global Master Data Management Market by Verticals, Performance – Potential Analysis
9.3. Global Master Data Management Market Estimates & Forecasts by Verticals,2018-2028 (USD Billion )
9.4. Master Data Management Market, Sub Segment Analysis
9.4.1. BFSI
9.4.2. Government
9.4.3. Retail
9.4.4. IT & Telecom
9.4.5. Manufacturing
9.4.6. Energy & Utilities
9.4.7. Healthcare
9.4.8. Other Verticals
Chapter 10. Global Master Data Management Market, Regional Analysis
10.1. Master Data Management Market, Regional Market Snapshot
10.2. North America Master Data Management Market
10.2.1. U.S.Master Data Management Market
10.2.1.1. Component breakdown estimates & forecasts, 2018-2028
10.2.1.2. Deployment Mode breakdown estimates & forecasts, 2018-2028
10.2.1.3. Organization Size breakdown estimates & forecasts, 2018-2028
10.2.1.4. Verticals breakdown estimates & forecasts, 2018-2028
10.2.2. CanadaMaster Data Management Market
10.3. Europe Master Data Management Market Snapshot
10.3.1. U.K. Master Data Management Market
10.3.2. Germany Master Data Management Market
10.3.3. France Master Data Management Market
10.3.4. Spain Master Data Management Market
10.3.5. Italy Master Data Management Market
10.3.6. Rest of EuropeMaster Data Management Market
10.4. Asia-PacificMaster Data Management Market Snapshot
10.4.1. China Master Data Management Market
10.4.2. India Master Data Management Market
10.4.3. JapanMaster Data Management Market
10.4.4. Australia Master Data Management Market
10.4.5. South Korea Master Data Management Market
10.4.6. Rest of Asia PacificMaster Data Management Market
10.5. Latin America Master Data Management Market Snapshot
10.5.1. Brazil Master Data Management Market
10.5.2. Mexico Master Data Management Market
10.6. Rest of The World Master Data Management Market

Chapter 11. Competitive Intelligence
11.1. Top Market Strategies
11.2. Company Profiles
11.2.1. IBM

11.2.1.1. Key Information
11.2.1.2. Overview
11.2.1.3. Financial (Subject to Data Availability)
11.2.1.4. Deployment Mode Summary
11.2.1.5. Recent Developments
11.2.2. Oracle
11.2.3. SAP
11.2.4. SAS
11.2.5. TIBCO Software
11.2.6. Informatica
11.2.7. Talend
11.2.8. Cloudera
11.2.9. Riversand
11.2.10. Broadcom
Chapter 12. Research Process
12.1. Research Process
12.1.1. Data Mining
12.1.2. Analysis
12.1.3. Market Estimation
12.1.4. Validation
12.1.5. Publishing
12.2. Research Attributes
12.3. Research Assumption

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We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
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