Global Smart Grid Data Analytics Market Report, Trends, Size, Share, Analysis, Estimations and Forecasts to 2022, top key players - SAS, Itron, AutoGrid, Sensus, Silver Spring Networks and others

Smart grid data analytics consists of solutions that enable the analysis of the deluge of data produced during smart grid operations. These solutions are increasingly gaining significance among utility providers and energy companies to effectively manage grid operations, plan investment in distribution networks, and monitor consumer behavior. The demand for sustainable and cost-effective supply of power by consumers and producers in the utility industry has catalyzed the smart grid data analytics market. In a constantly evolving energy landscape, large volumes of data are generated from sensors, smart meters, automated distribution systems, and other sensing equipment.

Key Players:
SAS, Itron, AutoGrid, Sensus, Silver Spring Networks, IBM, Infosys, Microsoft, SAP, Verizon, Accenture, EMC Corporation

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Based on the type of solution, the smart grid data analytics solution is segmented into advanced metering infrastructure, demand response analytics, asset management, grid optimization, and energy forecasting and data visualization solutions. Among these, the asset management occupied a major market share in 2014, in terms of revenue. However, the accelerating adoption of smart metering technologies and the increasing reliance of AMI to manage various smart meters technologies are key factors expected to bring AMI analytics segment to the forefront.

This report studies the global Smart Grid Data Analytics market, mainly for the regions such as North America, Europe, China, Japan, Southeast Asia and India. The detailed analysis on production, price & revenue and market share are given for the below mentioned top manufacturers in global market.

The report will enable both existing firms and new entrants to clinch the pulse of the market, which sequentially helps firms to congress a greater market share. Companies procuring this report could use any or many of the below listed 5 strategies to extend their market share.

1) Market Penetration: Extensive facts on the products and services offered by dominant players in the Smart Grid Data Analytics market. The report inspects the Smart Grid Data Analytics market by products, applications, end user and region.

2) Product development/innovation: complex observation on upcoming technologies, R & D activities, and new product introductions in the Smart Grid Data Analytics market.

3) Market development: complete information on cost effective emerging markets.
The report studies the markets for Smart Grid Data Analytics across different regions.

4) Market diversification: Extensive material on new products, untapped regions, recent developments and investments in the Smart Grid Data Analytics market.

5) Competitive assessment: Overall estimate of market shares, strategies, products and distribution channels of the main players in the Smart Grid Data Analytics market.

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The analysis tools such as SWOT analysis and Porter’s five forces model have been included in order to present the competition predominant in the global Smart Grid Data Analytics market. Various graphics, tables, and charts have been used in order to present an accurate understanding of this market. The Smart Grid Data Analytics market has also been studied in terms of its regulatory scenario and value chain analysis.

Table of Contents:

Global Smart Grid Data Analytics Market Research Report 2018-2023

Chapter 1 Smart Grid Data Analytics Market Overview
Chapter 2 Global Economic Impact
Chapter 3 Competition by Manufacturers
Chapter 4 Production, Revenue (Value) by Region (2018-2023)
Chapter 5 Supply (Production), Consumption, Export, Import by Regions (2018-2023)
Chapter 6 Production, Revenue (Value), Price Trend by Type
Chapter 7 Analysis by Application
Chapter 8 Manufacturing Cost Analysis
Chapter 9 Industrial Chain, Sourcing Strategy and Downstream Buyers
Chapter 10 Marketing Strategy Analysis, Distributors/Traders
Chapter 11 Market Effect Factors Analysis
Chapter 12 Market Forecast (2018-2023)
Chapter 13 Appendix

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