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Big Data in Oil & Gas - Thematic Research

  • Published Date: 08 Jun 2018
  • Number of Pages: 37
  • Category: Technology
  • Country: Global

Big Data in Oil & Gas - Thematic Research

Summary

Cloud computing, machine learning, augmented reality, internet TV, the Internet of Things (IoT), robotics, cryptocurrencies, voice, blockchain and cybersecurity. These are the big investment themes of tomorrow and they all have one thing in common: they generate huge amount of data.

Cisco estimates that the world generates 122 exabytes of internet data traffic per month. This data traffic is growing at 24% per annum and 82% of it is consumer generated. Most of this data traffic could be monetized via a growing band of hyperscale, internet-facing data centers around the world.

Ask any CEO how they expects to sell more products and cut more costs and he will tell you that Big Data features prominently in his strategy. Big Data refers to the technology processes by which companies can profit from the large amounts of data to which they have access.

Digitization of the assets are undoubtedly proving to be a boon as they can assist the oil and gas (O&G) industry to extract high volumes of hydrocarbons by optimizing their limited resources, propelling the growth of digital oil fields. The IoT-enabled sensors mounted on the pipelines, wellheads, and other equipment generate high volumes of data that is then analyzed and interpreted to gain actionable insights about conditions and output. The future of O&G companies is expected to depend on the ability of the IoT to harness the power of Big Data with use of advanced analytics.

Scope

This report is part of our ecosystem of thematic investment research reports, supported by our “thematic engine”. About our Thematic Research Ecosystem -
- GlobalData has developed a unique thematic methodology for valuing technology, media and telecom companies based on their relative strength in the big investment themes that are impacting their industry. Whilst most investment research is underpinned by backwards looking company valuation models, GlobalData’s thematic methodology identifies which companies are best placed to succeed in a future filled with multiple disruptive threats. To do this, GlobalData tracks the performance of the top 600 technology, media and telecom stocks against the 50 most important themes driving their earnings, generating 30,000 thematic scores. The algorithms in GlobalData’s “thematic engine” help to clearly identify the winners and losers within the TMT sector. Our 600 TMT stocks are categorised into 18 sectors. Each sector scorecard has a thematic screen, a risk screen and a valuation screen. Our thematic research ecosystem has a three-tiered reporting structure: single theme, multi-theme and sector scorecard. This report is a Multi-Theme report, covering all stocks, all sectors and all themes, giving readers a strong sense of how everything fits together and how conflicting themes might interact with one another.

Reasons to buy

- Our thematic investment research product, supported by our thematic engine, is aimed at senior (C-Suite) executives in the corporate world as well as institutional investors.
- Corporations: Helps CEOs in all industries understand the disruptive threats to their competitive landscape
- Investors: Helps fund managers focus their time on the most interesting investment opportunities in global TMT.
- Our unique differentiator, compared to all our rival thematic research houses, is that our thematic engine has a proven track record of predicting winners and losers.

Publisher Name : GlobalData


PLAYERS 3
TRENDS 4
Data trends 4
Industry growth trends 5
Hardware trends 6
Software trends 7
Big Data trends in oil & gas 8
VALUE CHAIN 11
Software 13
INDUSTRY ANALYSIS 14
Mergers and acquisitions 17
Timeline 18
THE IMPACT OF BIG DATA ON OIL & GAS 20
Oil & gas case studies 20
Key recommendations for IT vendors 22
COMPANIES SECTION 23
Public Companies 23
Private companies 27
Oil & gas companies 29
TECHNOLOGY BRIEFING 31
GLOSSARY 33
APPENDIX: OUR “THEMATIC” RESEARCH METHODOLOGY 36



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