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Global Oil and Gas Data Monetization Market Size study, by Component (Software/Platform, Services, Professional Services, Managed Services) by Application (Upstream, Midstream, Downstream) by Method (Indirect Data Monetization, Direct Data Monetization) and Regional Forecasts 2021-2027


Global Oil and Gas Data Monetization Market is valued approximately USD XX billion in 2020 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2021-2027... もっと見る

 

 

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Bizwit Research & Consulting LLP
ビズウィットリサーチ&コンサルティング
2022年1月15日 US$4,950
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200 英語

 

Summary

Global Oil and Gas Data Monetization Market is valued approximately USD XX billion in 2020 and is anticipated to grow with a healthy growth rate of more than XX % over the forecast period 2021-2027. In order to improve asset productivity, Oil and gas companies are turning the large volume of data into intelligence with the help of big data analytics. Data monetization helps in leveraging data insights to identify new revenue opportunities, improve production, and enhance service quality in the oil and gas industry. Growing penetration of IoT and AI devices and rising focus on asset productivity in oil & gas industry are key drivers for the growth of Oil and Gas Data Monetization market. According to UNITED NATIONS CONFERENCE ON TRADE AND DEVELOPMENT(UNCTAD)’s TECHNOLOGY AND INNOVATION REPORT 2021- in the year 2018, IoT sales estimated at USD 130 billion and in the next five years sales could grow to USD 1.5 trillion. Also, in the year 2017 there were already more IoT devices in use than people on earth – 8.4 billion. Another area which is growing at significant rate is the industrial internet of things (IIoT) which uses multiple interconnected devices for various forms of manufacturing processes . Also, with the rising focus on implementation of Industry 4.0 and growing technological advancements in Big Data and analytics, the adoption & demand for Oil and Gas Data Monetization is likely to increase the market growth during the forecast period. However, high installation cost and supply chain disruption in oil and gas industry due to covid 19 pandemic impede the growth of the market over the forecast period of 2021-2027.

The key regions considered for the global Oil and Gas Data Monetization market study includes Asia Pacific, North America, Europe, Latin America, and Rest of the World. North America is the leading/significant region across the world in terms of market share owing to availability of necessary infrastructure, increasing oil production and presence of leading players in the region. Whereas, Asia-Pacific is anticipated to exhibit highest growth rate / CAGR over the forecast period 2021-2027. Factors such as rising adoption of digital technologies, increasing oil and gas demand in the region would create lucrative growth prospects for the Oil and Gas Data Monetization market across Asia-Pacific region.

Major market player included in this report are:
Tata Consultancy Services
Halliburton,
Schlumberger Limited,
Informatica Corporation,
SAP SE,
Oracle Corporation,
Accentureplc,
IBM Corporation,
EMC Corporation,
Microsoft Corporation,
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:
Software/Platform
Services
Professional Services
Managed Services
By Application:
Upstream
Midstream
Downstream
By Method:
Indirect Data Monetization
Direct Data Monetization
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
Base year – 2020
Forecast period – 2021 to 2027

Target Audience of the Global Oil and Gas Data Monetization 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


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Table of Contents

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2019-2027 (USD Billion)
1.2.1. Oil and Gas Data Monetization Market, by Region, 2019-2027 (USD Billion)
1.2.2. Oil and Gas Data Monetization Market, by Component, 2019-2027 (USD Billion)
1.2.3. Oil and Gas Data Monetization Market, by Application, 2019-2027 (USD Billion)
1.2.4. Oil and Gas Data Monetization Market, by Method, 2019-2027 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Oil and Gas Data Monetization 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 Monetization Market Dynamics
3.1. Oil and Gas Data Monetization Market Impact Analysis (2019-2027)
3.1.1. Market Drivers
3.1.1.1. Growing penetration of IoT and AI devices.
3.1.1.2. Rising Focus on Asset Productivity in oil & gas Industry.
3.1.2. Market Challenges
3.1.2.1. High installation Cost.
3.1.2.2. Supply chain disruption due to covid 19 pandemic.
3.1.3. Market Opportunities
3.1.3.1. Rising focus on implementation of Industry 4.0
3.1.3.2. Increasing technological advancements in Big Data and analytics.
Chapter 4. Global Oil and Gas Data Monetization 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 (2018-2027)
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 Monetization Market, by Component
6.1. Market Snapshot
6.2. Global Oil and Gas Data Monetization Market by Component, Performance - Potential Analysis
6.3. Global Oil and Gas Data Monetization Market Estimates & Forecasts by Component 2018-2027 (USD Billion)
6.4. Oil and Gas Data Monetization Market, Sub Segment Analysis
6.4.1. Software/Platform
6.4.2. Services
6.4.3. Professional Services
6.4.4. Managed Services

Chapter 7. Global Oil and Gas Data Monetization Market, by Application
7.1. Market Snapshot
7.2. Global Oil and Gas Data Monetization Market by Application, Performance - Potential Analysis
7.3. Global Oil and Gas Data Monetization Market Estimates & Forecasts by Application 2018-2027 (USD Billion)
7.4. Oil and Gas Data Monetization Market, Sub Segment Analysis
7.4.1. Upstream
7.4.2. Midstream
7.4.3. Downstream

Chapter 8. Global Oil and Gas Data Monetization Market, by Method
8.1. Market Snapshot
8.2. Global Oil and Gas Data Monetization Market by Method, Performance - Potential Analysis
8.3. Global Oil and Gas Data Monetization Market Estimates & Forecasts by Method 2018-2027 (USD Billion)
8.4. Oil and Gas Data Monetization Market, Sub Segment Analysis
8.4.1. Indirect Data Monetization
8.4.2. Direct Data Monetization

Chapter 9. Global Oil and Gas Data Monetization Market, Regional Analysis
9.1. Oil and Gas Data Monetization Market, Regional Market Snapshot
9.2. North America Oil and Gas Data Monetization Market
9.2.1. U.S. Oil and Gas Data Monetization Market
9.2.1.1. Component breakdown estimates & forecasts, 2018-2027
9.2.1.2. Application breakdown estimates & forecasts, 2018-2027
9.2.1.3. Method breakdown estimates & forecasts, 2018-2027
9.2.2. Canada Oil and Gas Data Monetization Market
9.3. Europe Oil and Gas Data Monetization Market Snapshot
9.3.1. U.K. Oil and Gas Data Monetization Market
9.3.2. Germany Oil and Gas Data Monetization Market
9.3.3. France Oil and Gas Data Monetization Market
9.3.4. Spain Oil and Gas Data Monetization Market
9.3.5. Italy Oil and Gas Data Monetization Market
9.3.6. Rest of Europe Oil and Gas Data Monetization Market
9.4. Asia-Pacific Oil and Gas Data Monetization Market Snapshot
9.4.1. China Oil and Gas Data Monetization Market
9.4.2. India Oil and Gas Data Monetization Market
9.4.3. Japan Oil and Gas Data Monetization Market
9.4.4. Australia Oil and Gas Data Monetization Market
9.4.5. South Korea Oil and Gas Data Monetization Market
9.4.6. Rest of Asia Pacific Oil and Gas Data Monetization Market
9.5. Latin America Oil and Gas Data Monetization Market Snapshot
9.5.1. Brazil Oil and Gas Data Monetization Market
9.5.2. Mexico Oil and Gas Data Monetization Market
9.6. Rest of The World Oil and Gas Data Monetization Market

Chapter 10. Competitive Intelligence
10.1. Top Market Strategies
10.2. Company Profiles
10.2.1. Tata Consultancy Services
10.2.1.1. Key Information
10.2.1.2. Overview
10.2.1.3. Financial (Subject to Data Availability)
10.2.1.4. Product Summary
10.2.1.5. Recent Developments
10.2.2. Halliburton,
10.2.3. Schlumberger Limited,
10.2.4. Informatica Corporation,
10.2.5. SAP SE,
10.2.6. Oracle Corporation,
10.2.7. Accentureplc,
10.2.8. IBM Corporation,
10.2.9. EMC Corporation,
10.2.10. Microsoft Corporation,
Chapter 11. Research Process
11.1. Research Process
11.1.1. Data Mining
11.1.2. Analysis
11.1.3. Market Estimation
11.1.4. Validation
11.1.5. Publishing
11.2. Research Attributes
11.3. Research Assumption

 

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