“Big Data Analytics in Energy Sector Market” report provides profound research of industry players, dynamics, and strategies are segmented and sub-segmented to simplify the actual conditions of the industry. The report also covers scope of product market, research methodology, Porter’s Five Force analysis, and Competitive landscape of industry. This report scrutinizes all the key factors influencing growth of global Big Data Analytics in Energy Sector market, including production and value chain analysis, pricing structure, demand-supply scenario, profit margins.
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Top Players Are:
Key Market Trends:
Smart Metering to Fuel Market Growth
– The smart metering in big data analytics involves components such as grid operations, field services, resource planning, customer experience, and regulatory compliances. It helps to predict demand and forecast based on the data collected, that will boost the market growth.
– Furthermore, big data analytics in smart metering helps in forecasting energy consumption, which plays a vital role in the management of demand and supply which also mitigates the waste of energy.
– For instance, Siemens introduced incorporation of big data analytics with smart meters to achieve deeper insights from the smart grid which in turn offers data to mitigate extra energy consumption and increases profit margins.
– Developing countries such as India, Brazil, etc. are hugely investing in the energy sector, that will boost the smart metering with advanced big data techniques in recent years.
Asia-Pacific to be the Fastest Growing Market
– Increasing adoption of IoT and smart technologies and various government initiatives such as smart cities across APAC countries, including China and India vouch for APAC to be the fastest-growing region in the big data analytics in energy sector market.
– For instance, India has deployed 200,000 smart meters in 11 cities in 208 and will install 1500,000 more in 2019. It will use technology such as RF Mesh, GPRS, PLC and 6 LoWPAN. EESL aims to replace 25 crore conventional meters with smart meters in India through Smart Meters National Programme (SMNP) as this would help in reducing AT&C losses.
– In the APAC region, China will be the leading country in big data analytics in the energy utility sector due to its large population and increasing rate of adaptation of smart metering, smart grid systems across the country.
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- Market Dynamics – Drivers, Restraints, and Opportunities
- Market Segmentation – Types, Applications, Regions, and Technology
- Market Trends
- Competitive Landscape
- SWOT Analysis and Porter’s Five Forces Analysis
Scope of the Report:
Big Data Analytics helps energy utility sector by optimizing power generation and planning. Power generation planning and economic load dispatch are the two most important decision-making processes in power generation. Economic load dispatch in simple terms is matching power supply with the demand for energy from the grid over a short period of time at the lowest possible cost subject to transmission and distribution constraints. Matching energy supply and demand on the network has always been a tight balancing act, and data analytics has a significant role to play by taking advantage of collected energy data and advanced big data analytics techniques.
Most of the companies present in the market are efficient at the technological front, but require significant support for enhancing their services and expanding their businesses. Thus, mergers and acquisitions offer significant opportunities to gain the attention of a large number of providers across developed regions.
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Detailed TOC of Big Data Analytics in Energy Sector Market Report 2024:
1.1 Study Deliverables
1.2 Study Assumptions
1.3 Scope of the Study
2 RESEARCH METHODOLOGY
3 EXECUTIVE SUMMARY
4 MARKET DYNAMICS
4.1 Market Overview
4.2 Market Drivers
4.2.1 Enormous Influx of Data
4.2.2 Volatility in the Oil Prices
4.3 Market Restraints
4.3.1 Lack of Skilled Labor
4.4 Industry Attractiveness – Porter’s Five Force Analysis
4.4.1 Bargaining Power of Suppliers
4.4.2 Bargaining Power of Buyers/Consumers
4.4.3 Threat of New Entrants
4.4.4 Threat of Substitute Products
4.4.5 Intensity of Competitive Rivalry
5 MARKET SEGMENTATION
5.1 By Application
5.1.1 Grid Operations
5.1.2 Smart Metering
5.1.3 Asset & Workforce Management
5.2.1 North America
5.2.4 Latin America
5.2.5 Middle East & Africa
6 COMPETITIVE LANDSCAPE
6.1 Company Profiles
6.1.1 IBM Corporation
6.1.2 Microsoft Corporation
6.1.3 SAP SE
6.1.4 Dell Inc.
6.1.6 Infosys Limited
6.1.7 Intel Corporation
6.1.8 Siemens AG
7 INVESTMENT ANALYSIS
8 MARKET OPPORTUNITIES AND FUTURE TRENDS
Name: Ajay More
Phone: US +14242530807/ UK +44 20 3239 8187
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