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Global Big Data in Power Sector Market - Growth Trends and Forecasts 2017 - 2022

  • ID: 4385521
  • Report
  • Region: Global
  • 133 pages
  • Mordor Intelligence
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What does data represent? Data enables one to have better insights into activities and events. Todays requirements are very different than what the power companies faced a few years back. For example a customer wants to know his power consumption levels for each day and an engineer wants to know which particular activities from which customers at what point of time constitute the extra demand for power or which equipment needs replacement or maintenance. These people are not ready to wait for a monthly bill or wait for a failure to happen. Moreover for the power company the shift of preference is from preventive to predictive maintenance. The benefit of this is reduction in failures and delivery of quality power. Better information about power consumption can lead to shifting of consumption in off peak hours by consumer for lowering of tariff and power companies can cut transmission losses if they are more aware about usage source and patterns.

Supervisory control and data acquisition (SCADA) systems have been in use for a number of years. Which enable data collection from multiple locations using Remote Terminal Units (RTU) and Programmable logic controller (PLC). SCADA also records and processes high frequency data however the challenges lay in handling of observational data. The adaptation of Smart Grid system in several countries on one hand has proved its usefulness, and on the other created new challenges. The operationalization of Smart Grid is dependent upon several intelligent and smart equipment in the grid. These equipment have specific needs and require specific management system. For example the installation of Smart meters is getting popular in developed markets and its usage is expected to spread to the rest of the world. The major attribute of Smart Meter is that it provides information about power consumption in every five minutes. A new solution is needed to handle diverse set of smart equipment at multiple places which keeps increasing with the passage of time. Big data management system can provide with advanced analytics, and algorithm to handle these kind of data. Equipped with tools like, Hadoop, R, data MongoDB etc, Big data technology is evolving keeping in pace with the market demand.

The global market for the usage of big data in power sector currently stands at $XXX and the estimation is that it is going to be $XXX by 2022. Although the usage is more prevalent in USA the rest of the world is expected to soon catch up with the trend.


Power projects involve substantial investments and immense risk factors. So any technological attempt to increase efficiency and reduce cost is appreciated by the stakeholders. To enable enhanced situational awareness by using advanced equipment technology requires real time gathering of data which is ensured by the applications of big data. Power companies world over are facing the pressure for increasing tariffs and any tool that helps in its reduction will be welcomed by the companies. Furthermore the power corporations have long standing challenges of ensuring safety of their employees engaged in installation, repair and maintenance activities. Technology that reduces their concern will be adopted by the companies.


The biggest issue that bothers companies using high technology is the availability of qualified personnel. The collection of huge quantity of data requires substantial investments in terms of both hardware and software. Another restraint for the use of big data is that, most it come in various unstructured formats. What is needed is new algorithms designed to be flexible enough to handle high volumes of unstructured data.


Currently the world market for big data is evolving at a fast rate. Many new equipment are in the process of being developed and many are being introduced in the market. The adopters of this technology chance to gain substantial competitive advantage. The benefits of big data includes opportunity to create better asset utilization and high efficiency of operations.
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1. Executive Summary
2. Research Methodology
3. Market Overview
3.1 Introduction
3.2 Markets Covered
3.3 Market Demand till 2022
3.4 Recent Trends and Opportunities
3.5 Government Policies and Regulations
4. Market Dynamics
4.1 Drivers
4.1.1 Risks involved in Capital Intensive Projects
4.1.2 Need for Real Time Analysis
4.1.3 Demand for lowering the cost of Power Tariffs
4.1.4 Requirements for Higher Safety
4.2 Constraints
4.2.1 Talent Shortage
4.2.2 Massive Requirements for Data Storage
4.2.3 Unstructured Data
4.2.4 High Cost of Initial Investments
4.2.5 Flexible Algorithm To Handle Scale and Volume of Data
4.3 Opportunities
4.3.1 Competitive Advantage
4.3.2 Higher Efficiency
4.3.3 Better Asset Utilization
5. Global Big Data in Power Sector Value Chain Analysis
6. Porters Five Force Analysis
6.1 Bargaining Power of Supplier
6.2 Bargaining Power of Consumers
6.3 Threat of New Entrants
6.4 Threat of Substitute Products and Services
6.5 Degree of Competition
7. Global Big Data in Power Sector Market by Industry
7.1 Power Generation
7.2 Power Transmission
7.3 Power Distribution
8. Global Big Data in Power Sector Market Segmentation, by Technology
8.1 R
8.2 Hadoop
8.3 MongoDB
8.4 NoSQL
8.5 MapReduce
8.6 HPCC
8.7 PIG
8.8 Quantcast File System
9. Global Big Data in Power Sector Market Analysis, by Geography
9.1 North America
9.2 Europe
9.3 Africa
9.4 South and Central America
9.5 Asia-Pacific
9.6 South and Central America
10. Key Company Analysis
10.1 Microsoft
10.2 Siemens
10.3 IBM
10.4 SAP
10.5 Accenture
10.6 Palantir
10.7 SAS
10.8 Oracle
10.9 Teradata
11. Competitive Landscape
11.1 Mergers & Acquisitions
11.2 Joint Ventures, Collaborations and Agreements
11.3 Market Share Analysis
12. Appendix
12.1 Contact Us
12.2 Disclaimer
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