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Global Oil and Gas Data Management Market to reach USD 15.39 billion by 2028

Global Oil and Gas Data Management Market Size study, by Type (Data Analysis, IT Infrastructure, Services), by Application (Upstream, Midstream, Downstream) and Regional Forecasts 2022-2028

Product Code: CMOGI-81749847
Publish Date: 30-04-2022
Page: 200

Global Oil and Gas Data Management Market is valued at approximately USD 15.80 billion in 2021 and is anticipated to grow with a healthy growth rate of more than 19.0 % over the forecast period 2022-2028. Data management is the process of ingesting, storing, organizing and maintaining the data created and collected by an organization. The increase in digitization and growing IT infrastructure has led to the adoption of Oil and Gas Data Management across the forecast period. For Instance: as per the NIP&FA, Investment in Software-as-a-Service has increased 170% over 2020 and has reached $4.5 billion in 2021, accounting for 8% of the overall private equity and venture capital deal value in India. Also, with the increase in adoption of pervasive computing devices and increase in popularity of real-time analysis, the adoption & demand for Oil and Gas Data Management is likely to increase the market growth during the forecast period. However, lack of skilled workforce and high initial investment impede the growth of the market over the forecast period of 2022-2028.

The key regions considered for the Global Oil and Gas Data Management Market study include Asia Pacific, North America, Europe, Latin America and Rest of the World. North America is the leading region across the world in terms of market share owing to the growing expenditure across the U.S. and major adoption of Oil and Gas Data Management solutions, rise in need for advanced analytics solutions and services among oil and gas companies. Whereas, Asia-Pacific is also anticipated to exhibit the highest growth rate over the forecast period 2022-2028. Factors such as tremendous investments for Oil and Gas Data Management solutions would create lucrative growth prospects for the Oil and Gas Data Management Market across Asia-Pacific region.

Major market players included in this report are:
Oracle Corporation
CliQr Technologies, Inc.
SimpliVity
Teradata
OpenDNS
Bapco (Bahrain Petroleum Company)
Noah Consulting, LLC
Schlumberger
Reltio
Wipro Limited

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 Type:
Data Analysis
IT Infrastructure
Services
By Application:
Upstream
Midstream
Downstream
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 Oil and Gas 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. Oil and Gas Data Management Market, by Region, 2020-2028 (USD Billion)
1.2.2. Oil and Gas Data Management Market, by Type, 2020-2028 (USD Billion)
1.2.3. Oil and Gas Data Management Market, by Application, 2020-2028 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Oil and Gas 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 Oil and Gas Data Management Market Dynamics
3.1. Oil and Gas Data Management Market Impact Analysis (2020-2028)
3.1.1. Market Drivers
3.1.1.1. Increase in digitization
3.1.1.2. Growing IT infrastructure
3.1.2. Market Challenges
3.1.2.1. Lack of skilled workforce
3.1.2.2. High initial investment
3.1.3. Market Opportunities
3.1.3.1. Increase in adoption of pervasive computing devices
3.1.3.2. Increase in popularity of real-time analysis
Chapter 4. Global Oil and Gas Data Management Market Industry 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 (2019-2028)
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 Oil and Gas Data Management Market, by Type
6.1. Market Snapshot
6.2. Global Oil and Gas Data Management Market by Type, Performance – Potential Analysis
6.3. Global Oil and Gas Data Management Market Estimates & Forecasts by Type, 2019-2028 (USD Billion)
6.4. Oil and Gas Data Management Market, Sub Segment Analysis
6.4.1. Data Analysis
6.4.2. IT Infrastructure
6.4.3. Services
Chapter 7. Global Oil and Gas Data Management Market, by Application
7.1. Market Snapshot
7.2. Global Oil and Gas Data Management Market by Application, Performance – Potential Analysis
7.3. Global Oil and Gas Data Management Market Estimates & Forecasts by Application, 2019-2028 (USD Billion)
7.4. Oil and Gas Data Management Market, Sub Segment Analysis
7.4.1. Upstream
7.4.2. Midstream
7.4.3. Downstream
Chapter 8. Global Oil and Gas Data Management Market, Regional Analysis
8.1. Oil and Gas Data Management Market, Regional Market Snapshot
8.2. North America Oil and Gas Data Management Market
8.2.1. U.S. Oil and Gas Data Management Market
8.2.1.1. Type breakdown estimates & forecasts, 2019-2028
8.2.1.2. Application breakdown estimates & forecasts, 2019-2028
8.2.2. Canada Oil and Gas Data Management Market
8.3. Europe Oil and Gas Data Management Market Snapshot
8.3.1. U.K. Oil and Gas Data Management Market
8.3.2. Germany Oil and Gas Data Management Market
8.3.3. France Oil and Gas Data Management Market
8.3.4. Spain Oil and Gas Data Management Market
8.3.5. Italy Oil and Gas Data Management Market
8.3.6. Rest of Europe Oil and Gas Data Management Market
8.4. Asia-Pacific Oil and Gas Data Management Market Snapshot
8.4.1. China Oil and Gas Data Management Market
8.4.2. India Oil and Gas Data Management Market
8.4.3. Japan Oil and Gas Data Management Market
8.4.4. Australia Oil and Gas Data Management Market
8.4.5. South Korea Oil and Gas Data Management Market
8.4.6. Rest of Asia Pacific Oil and Gas Data Management Market
8.5. Latin America Oil and Gas Data Management Market Snapshot
8.5.1. Brazil Oil and Gas Data Management Market
8.5.2. Mexico Oil and Gas Data Management Market
8.6. Rest of The World Oil and Gas Data Management Market

Chapter 9. Competitive Intelligence
9.1. Top Market Strategies
9.2. Company Profiles
9.2.1. Oracle Corporation
9.2.1.1. Key Information
9.2.1.2. Overview
9.2.1.3. Financial (Subject to Data Availability)
9.2.1.4. Product Summary
9.2.1.5. Recent Developments
9.2.2. CliQr Technologies, Inc.
9.2.3. SimpliVity
9.2.4. Teradata
9.2.5. OpenDNS
9.2.6. Bapco (Bahrain Petroleum Company)
9.2.7. Noah Consulting, LLC
9.2.8. Schlumberger
9.2.9. Reltio
9.2.10. Wipro Limited
Chapter 10. Research Process
10.1. Research Process
10.1.1. Data Mining
10.1.2. Analysis
10.1.3. Market Estimation
10.1.4. Validation
10.1.5. Publishing
10.2. Research Attributes
10.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
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.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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