Big Data in Global Oil & Gas and Mining Market 2021

May 2018 | 79 pages | ID: BCE95E44E1DEN
NAVADHI Market Research Pvt Ltd

Abstracts

Big Data and Oil industry has some drastic similarity. Just like crude oil, if not refined properly, can not be sold in open market at profit. Likewise, data without processing will remain crude and can not help in making informed decision.

Finding and producing Hydrocarbons, Metals and Minerals are economically risky and technically challenging task. The process generates huge amount of data, and the exploration and mining industry needs new ways to integrate and interpret this data to make faster and accurate decisions. A well-organized data help finding new resources, rapid recovery rates and reducing impacts on environment.

Oil exploration and mining industry combined is 5 trillion-dollar industry and have an exponential growth rate as the demand for both is never ending. With some regulatory constraints and decrease in availability this sector need to find means to decrease expenses so as to make the extraction affordable and keep the cost under control. So they have started using big data so as reduce the cost in exploration and finding the right place to search for along with this they are also using it in operational activity to reduce expenditure.

The objective of this research study is to understand the current big data in Oil exploration and mining industry and to estimate the growth rate for the next 5 years.

The report covers the detailed analysis of 4 companies- their value chain, financial performance, and forecast, Business strategy, SWOT analysis which are involved in selling products and services in big data to the oil exploration and mining industry and having presence across different regions of the world. The details of the company and certifications are also mentioned in this report.

The big data in oil exploration and mining industry is currently valued at USD XX billion. It is expected that the market will grow at a CAGR of 11.01% and will reach USD XX billion by the year 2021. Delivering quality services, understanding exploration process, improving operational efficiency and rising demand for data driven decision making are some of the key factors which will drive the growth of this industry.

This report concludes by analyzing the industry through PESTLE, porters 5 forces and SWOT, discusses the challenges faced by the new players entering the industry and present and future trends observed. Strategic recommendations are also discussed separately and in detail for oil exploration and mining companies as well as big data service suppliers.

Scope of Report

• This report provides a detailed view of big data in Oil exploration and mining market with the current market value as well as projections for future market potential and growth rate.
• This report identifies the need for big data in Oil exploration and mining industry
• This report provides detailed information on the value chain as well as the different market segments and their segment wise market share and growth potential.
• This report provides detailed information on geography wise growth forecasts for big data in Oil exploration and mining industry globally by 2021.
• This report identifies the growth drivers and inhibitors for big data in Oil exploration and mining industry
• This report has detailed profiles of 4 key players in the big data in Oil exploration and mining industry covering their business strategy, financial performance, future forecasts and SWOT analysis
• This report identifies the key industry bodies and associations and their role in Indian Oil exploration and mining market.
• This report provides PEST (political, economic, social and technological) analysis for big data in Oil exploration and mining industry.
• This report provides porters five forces analysis for big data in Oil exploration and mining industry
• This report provides SWOT (strength, weaknesses, opportunities, threats) analysis for big data in Oil exploration and mining industry.

Contents

1. EXECUTIVE SUMMARY

1.2 Research Methodology
1.3 Key Findings
1.4 Scope of Report

2. NEED OF BIG DATA IN OIL EXPLORATION AND MINING INDUSTRY

3. BIG DATA IN OIL EXPLORATION AND MINING VALUE CHAIN

4. MARKET SEGMENTS & FORECASTS FOR GLOBAL BIG DATA MARKET

4.2 Asia Pacific Big Data Market in Oil Exploration and Mining Industry till 2021
4.2 North American Big Data Market in Oil Exploration and Mining Industry till 2021
4.3 Europe Big Data Market in Oil Exploration and Mining Industry till 2021
4.4 Latin and South America Big Data Market in Oil Exploration and Mining Industry till 2021
4.5 Middle East and Africa Big Data Market in Oil Exploration and Mining Industry till 2021

5. GROWTH DRIVERS AND INHIBITORS FOR BIG DATA IN OIL EXPLORATION AND MINING INDUSTRY

6. PROFILE OF KEY PLAYERS IN BIG DATA IN OIL EXPLORATION AND MINING

6.1 Hitachi Data System
  6.1.1 Company Profile
  6.1.2 Hitachi Data System Limited in Big Data Value Chain
  6.1.3 Financial Performance of Hitachi Data System Limited
  6.1.4 Business Strategy
    6.1.4.1 Product Level Business Strategy
    6.1.4.2 Service Level Business Strategy
  6.1.5 SWOT Analysis for Hitachi Limited
Strengths
Weaknesses
Opportunities
Threats
6.2 Hewlett Packard (HP)
  6.2.1 Company Profile
  6.2.2 HP Limited in Big Data Value Chain
  6.2.3 Financial Performance of HP Limited
  6.2.4 Business Strategy
    6.2.4.1 Product Level Business Strategy
    6.2.4.2 Service Level Business Strategy
  6.2.5 SWOT Analysis for HP Limited
Strengths
Weaknesses
Opportunities
Threats
6.3 International Business Machines (IBM)
  6.3.1 Company Profile
  6.3.2 IBM Limited in Big Data Value Chain
  6.3.3 Financial Performance of IBM Limited
  6.3.4 Business Strategy
    6.3.4.1 Product Level Business Strategy
    6.3.4.2 Service Level Business Strategy
  6.3.5 SWOT Analysis for IBM Limited
Strengths
Weaknesses
Opportunities
Threats
6.4 SAP
  6.4.1 Company Profile
  6.4.2 SAP Limited in Big Data Value Chain
  6.4.3 Financial Performance of IBM Limited
  6.4.4 Business Strategy
    6.4.4.1 Product Level Business Strategy
    6.4.4.2 Service Level Business Strategy
  6.4.5 SWOT Analysis for SAP Limited
Strengths
Weaknesses
Opportunities
Threats

7. CASE STUDY

7.2 Rio Tinto using Big data to increase productivity

8. ANALYSIS MODELS

Strengths
Weaknesses
Opportunities
Threats

9. MARKET OPPORTUNITY

10. RECOMMENDATIONS

List Of Exhibits

LIST OF EXHIBITS

Notes
Company Information

LIST OF EXHIBITS

Exhibit 3.2.1 Global Big Data Industry Value Chain
Exhibit 4.1 Market Share of Various Geographies in Global Big Data Market in Oil Exploration and Mining- 2016 (in %)
Exhibit 4.2 Forecast of Global Big Data Market 2017-21 (Billion Dollar)
Exhibit 4.3 Forecast of Global Big Data Market 2017-21 (Billion Dollar
Exhibit 4.4 Forecast of Global Big Data Market in Oil Exploration and Mining 2017-21 (in Billion Dollar)
Exhibit 4.5 Year Wise Growth Rate of Big Data form 2015-2021 (% Growth)
Exhibit 4.6 Forecast of Asia Pacific Big Data Market in Oil Exploration and Mining 2017-21 (in Billion Dollar)
Exhibit 4.7 Forecast of North America Big Data Market in Oil Exploration and Mining 2017-21 (in Billion Dollar)
Exhibit 4.8 Forecast of Europe Big Data Market in Oil Exploration and Mining 2017-21 (in Billion Dollar)
Exhibit 4.9 Forecast of Latin & South America Big Data Market in Oil Exploration and Mining 2017-21 (in Billion Dollar)
Exhibit 4.10 Forecast of Middle East & Africa Big Data Market in Oil Exploration and Mining 2017-21 (in Billion Dollar)
Exhibit 5.1 Growth Drivers and Inhibitors for Global Big Data Market in Oil Exploration and Mining
Exhibit 6.1 Company Profile – Hitachi Data System Limited
Exhibit 6.2 Contact Details – Hitachi Data System Limited
Exhibit 6.3 Hitachi Data System in Big Data Value Chain
Exhibit 6.4 IBM Revenue from 2012 to 2016 (in USD million)
Exhibit 6.5 Year-wise IBM Revenue Growth from 2012 to 2016 (in %)
Exhibit 6.6 Estimated IBM Revenue from 2016 to 2021 (in USD million)
Exhibit 6.7 Estimated Year-wise IBM Revenue Growth from 2016 to 2021 (in %)
Exhibit 6.8 Major Products and Services of Hitachi Limited
Exhibit 6.9 SWOT Analysis of Hitachi Data System Limited
Exhibit 6.10 Company Profile – HP Limited
Exhibit 6.11 Contact Details – HP Limited
Exhibit 6.12 HP Limited in Big Data Value Chain
Exhibit 6.13 HP Revenue from 2012 to 2016 (in USD million)
Exhibit 6.14 Year-wise HP Revenue Growth from 2012 to 2016 (in %)
Exhibit 6.15 Estimated HP Revenue from 2016 to 2021 (in USD million)
Exhibit 6.16 Estimated Year-wise HP Revenue Growth from 2016 to 2021 (in %)
Exhibit 6.17 Major Products and Services of HP Limited
Exhibit 6.18 SWOT Analysis of HP Limited
Exhibit 6.19 Company Profile – IBM Limited
Exhibit 6.20 Contact Details – IBM Limited
Exhibit 6.21 IBM Limited in Big Data Value Chain
Exhibit 6.22 IBM Revenue from 2012 to 2016 (in USD million)
Exhibit 6.23 Year-wise IBM Revenue Growth from 2012 to 2016 (in %)
Exhibit 6.24 Estimated IBM Revenue from 2016 to 2021 (in USD million)
Exhibit 6.25 Estimated Year-wise IBM Revenue Growth from 2016 to 2021 (in %)
Exhibit 6.26 Major Products and Services of IBM Limited
Exhibit 6.27 SWOT Analysis of IBM Limited
Exhibit 6.28 Company Profile – SAP Limited
Exhibit 6.29 Contact Details – SAP Limited
Exhibit 6.30 SAP Limited in Big Data Value Chain
Exhibit 6.31 SAP Limited Revenue from 2012 to 2016 (in USD million)
Exhibit 6.32 Year-wise SAP Limited Revenue Growth from 2012 to 2016 (in %)
Exhibit 6.33 Estimated SAP Limited in Revenue from 2016 to 2021 (in USD million)
Exhibit 6.34 Estimated Year-wise SAP Limited Revenue Growth from 2016 to 2021 (in %)
Exhibit 6.35 Major Products and Services of IBM Limited
Exhibit 6.36 SWOT Analysis of IBM Limited
Exhibit 8.1 Porter’s Five forces for Big Data in Oil exploration and Mining
Exhibit 8.2 SWOT Analysis of Big Data in Oil Exploration and Mining