世界各国のリアルタイムなデータ・インテリジェンスで皆様をお手伝い

Smart Grid Big Data Analytics Market Report: Trends, Forecast and Competitive Analysis to 2031

Smart Grid Big Data Analytics Market Report: Trends, Forecast and Competitive Analysis to 2031


Smart Grid Big Data Analytics Market Trends and Forecast The future of the global smart grid big data analytics market looks promising with opportunities in the public sector, large enterprises, a... もっと見る

 

 

出版社 出版年月 電子版価格 納期 言語
Lucintel
ルシンテル
2025年8月14日 US$3,850
シングルユーザライセンス
ライセンス・価格情報
注文方法はこちら
オンデマンドレポート:ご注文後3-4週間 英語

日本語のページは自動翻訳を利用し作成しています。
実際のレポートは英文のみでご納品いたします。

本レポートは受注生産のため、2~3営業日程度ご納品のお時間をいただく場合がございます。


 

Summary

Smart Grid Big Data Analytics Market Trends and Forecast
The future of the global smart grid big data analytics market looks promising with opportunities in the public sector, large enterprises, and small & medium-sized enterprises markets. The global smart grid big data analytics market is expected to grow with a CAGR of 12.7% from 2025 to 2031. The major drivers for this market are the rising demand for energy efficiency, integration of renewable energy sources, and government policies and regulations.

• Lucintel forecasts that, within the type category, cloud-based will remain the larger segment over the forecast period.
• Within the application category, the public sector is expected to witness the highest growth.
• In terms of region, APAC is expected to witness the highest growth over the forecast period.
Gain valuable insights for your business decisions with our comprehensive 150+ page report. Sample figures with some insights are shown below.

Emerging Trends in the Smart Grid Big Data Analytics Market
The smart grid big data analytics market is evolving due to new technologies and shifting market trends. Changes in how utilities operate energy systems and relate to consumers are driving these developments. Below are five key trends driving the market:
• Increased Demand for Smart Energy Systems: There is a noticeable increase in the need for smarter and more efficient energy systems. The adoption of big data analytics is expected to make renewable energy easier to manage and more efficient. Distributors and authorities are focusing more on active analytics supported by IoT technologies for energy distribution optimization, demand prediction, and system resilience improvement.
• AI and Machine Learning Integration: AI and machine learning are improving smart grids by enabling utilities to forecast energy requirements, optimize supply, and automate maintenance. These tools help predict equipment failures and schedule maintenance in advance, reducing operational costs and downtime. Real-time demand prediction allows for better resource and energy efficiency.
• Advanced Decision Making with Real-Time Data Analytics: Utilities are increasingly using real-time data analytics to improve decision-making in grid management. Continuous data streams allow utilities to allocate energy, enhance system abilities, and reduce outages. Real-time analytics facilitate better coordination between renewable energy sources and conventional grids.
• Cloud-Based Solutions for Smart Grids: The impact of cloud computing in smart grids is evident in big data analytics, where massive datasets can be stored and processed efficiently. With new technologies being implemented, the investment in infrastructure is minimal, which benefits smaller utilities and businesses looking to enhance grid efficiency. The scalability and flexibility offered by cloud solutions are game changers for utilities.
• Integration of Smart Meters and Energy Storage: Innovations in smart grids are being achieved through the integration of smart meters and energy storage systems. Smart meters provide data that helps optimize energy distribution, while energy storage systems guarantee supply during peak demand. This combination of technologies offers an opportunity to increase resource efficiency and reduce energy consumption.
• Cybersecurity Focus: As smart grid systems become more connected and data-dependent, there is a growing focus on cybersecurity. The infrastructure and grid are at risk of cyberattacks, so efforts in cybersecurity are crucial to maintaining reliability and safety. To protect smart grid operations from cyberattacks, data encryption is enhanced, cloud services are secured, and sophisticated authentication protocols are implemented.
The merging of these components has fundamentally changed the management of smarter grid systems, transforming them into more efficient, resilient, and sustainable systems. The evolution of AI, real-time analytics, cloud computing, energy storage, and cybersecurity solutions is driving this transformation.

Recent Developments in the Smart Grid Big Data Analytics Market
Technology innovation and growth are impacting various regions, leading to changes in the smart grid big data analytics market. Utilities are modernizing their grids, enhancing efficiency, and incorporating renewable energy sources.
• AI-Powered Predictive Maintenance: AI-enabled predictive maintenance is becoming a key trend, eliminating costs and time associated with maintaining or repairing grids that are partially functioning. Grid performance is expected to improve significantly, and the entire system can be considered optimally functional without the need for intervention.
• 5G and IoT Integration for Smart Grids: The integration of 5G networks with smart grids, along with IoT devices, is improving grid operations. With 5G, assets within the grid can be monitored and controlled in real-time due to ultra-low latency and high-speed data transfer, which is crucial for effective energy distribution with increased use of renewable technologies.
• Advanced Metering Infrastructure (AMI) Expansion: The wider deployment of AMI technology allows utilities to capture detailed data on energy usage. These meters offer real-time data, enabling effective demand-side management, reducing energy theft, and improving customer billing systems.
• Blockchain for Energy Trading: Blockchain is being explored for energy trading on smart grids. It can enhance the efficiency of trading energy, especially in peer-to-peer networks where consumers can trade electricity directly with one another.
• Grid Resilience During Natural Disasters: Data analytics in smart grid technologies is strengthening grid resilience during natural disasters. By utilizing real-time sensor data, utilities can better respond to interruptions caused by extreme weather conditions like hurricanes or wildfires, improving recovery time and minimizing impacts on consumers.
These innovations are facilitating a shift toward more complex, robust, and effective global smart grids, boosting growth in the market.

Strategic Growth Opportunities in the Smart Grid Big Data Analytics Market
The smart grid big data analytics market has varying growth opportunities across core business processes. As the energy sector shifts toward more modern, intelligent, and data-centric systems, industries are identifying areas where they can leverage technology to improve efficiency. Below are primary growth opportunities across different applications:
• Smart Grid Optimization: The surge in energy demand, along with inefficiencies in grid management, presents a key opportunity for growth in big data analytics for grid optimization. Utilities can now accurately forecast patterns and reduce electricity usage to enhance grid stability during different times of day.
• Demand Response Initiatives: Big data analytics is essential in enabling effective demand response activities, where utilities adjust energy consumption patterns. These programs allow utilities to ease grid congestion, reduce energy costs, and encourage users to conserve power during peak times.
• Integrating Renewable Energy: As the integration of solar and wind power into electricity grids increases, there is a growing need for tools to analyze their contributions. Big data analytics enables forecasting renewable energy generation and regulating electricity flow to meet grid requirements without overloading traditional power plants.
• Energy Management Solutions for Customers: The range of services and energy management tools offered to consumers is expanding. Big data analytics helps provide better energy management solutions by offering customers insights into their energy usage and recommending specific methods to save energy.
• Cybersecurity and Grid Security: As more devices become connected and digital, the grid becomes more vulnerable to cyberattacks. Big data analytics helps identify, monitor, and classify unusual activity that may pose threats, ensuring the protection of vital assets from malicious attacks.
These developments underscore the increasing relevance of big data analytics in smart grid systems, which are used for optimizing energy demand, distribution, safety, and renewable energy integration.

Smart Grid Big Data Analytics Market Driver and Challenges
The smart grid big data analytics market is influenced by various technological, economic, and regulatory drivers and challenges. These factors are crucial for stakeholders seeking to understand the intricacies of the market. Below is a summary of the primary drivers and challenges influencing the industry.
The factors responsible for driving the smart grid big data analytics market include:
1. New Infrastructure: The smart grid industry has undergone significant transformation due to the development of AI, machine learning, and IoT devices that enable sophisticated data processing, predictive analytics, and automation. Grid integration and management continue to improve, resulting in decreased system downtime and increased renewable energy use.
2. Government Policies and Regulations: Governments worldwide are drafting new policies and introducing regulations aimed at achieving energy efficiency through smart grid technologies. These policies help expedite smart grid adoption through funding and regulatory measures.
3. Increasing Use of Renewable Energy: Wind and solar energy are becoming more popular as countries aim to reduce carbon emissions. Smart grid analytics is essential for successful renewable energy generation and distribution management.
4. Municipalities and Governments: Governments aiming to reduce energy consumption can leverage smart grid data analytics to manipulate energy in real-time, promoting responsible energy habits among citizens.
5. Reduction of Operational Costs: Utilities can minimize costs by improving operational efficiency with big data analytics. As operational costs decrease, investment in smart grid technologies becomes more attractive.
Challenges in the smart grid big data analytics market are:
1. Initial Investment Hurdles: The high costs associated with smart grid adoption, particularly without advanced analytics infrastructure, are a challenge in developing regions with limited budgets.
2. Data Privacy: Privacy concerns regarding consumer data present significant challenges in ensuring secure storage and compliance with privacy standards.
3. Integration Challenges: Integrating new smart grid technologies with existing legacy infrastructure is complex and difficult for many utilities, hindering the adoption of big data analytics solutions.
While technology advancements and regulatory support promise growth in the smart grid big data analytics market, managing costs, data privacy, and system integration will be critical for sustainable market development.

List of Smart Grid Big Data Analytics Companies
Companies in the market compete on the basis of product quality offered. Major players in this market focus on expanding their manufacturing facilities, R&D investments, infrastructural development, and leverage integration opportunities across the value chain. With these strategies, smart grid big data analytics companies cater to increasing demand, ensure competitive effectiveness, develop innovative products & technologies, reduce production costs, and expand their customer base. Some of the smart grid big data analytics companies profiled in this report include:
• EMC Corporation
• SAP SE
• Accenture PLC
• Oracle Corporation
• SAS Institute
• Capgemini
• Siemens

Smart Grid Big Data Analytics Market by Segment
The study includes a forecast for the global smart grid big data analytics market by type, application, and region.
Smart Grid Big Data Analytics Market by Type [Value from 2019 to 2031]:
• Cloud-Based
• On-Premise

Smart Grid Big Data Analytics Market by Application [Value from 2019 to 2031]:
• Public Sector
• Large Enterprises
• Small & Medium-Sized Enterprises

Smart Grid Big Data Analytics Market by Region [Value from 2019 to 2031]:
• North America
• Europe
• Asia Pacific
• The Rest of the World

Country Wise Outlook for the Smart Grid Big Data Analytics Market
Numerous countries are adopting new technologies to enhance their energy grids, leading to the development of the global smart grid big data analytics market. Notable advancements have been made in integrating big data, IoT, and machine learning for optimizing energy consumption, enhancing grid reliability, and integrating renewable energy sources. Below, we will explore the most important markets categorized by the United States, China, Germany, India, and Japan.
• United States: The graph shows that investment in smart grid infrastructure is one of many steps toward decarbonization and modernization. To integrate renewable energy sources, the U.S. Department of Energy (DOE) has financed numerous smart grid projects. The increased use of data analytics in utilities allows for the optimization of grid operations, the prediction of maintenance needs, and the improvement of customer interactions. The goal is to maintain grid resilience with the help of advanced predictive analytics to control energy flows during extreme climate shifts.
• China: China has always been at the forefront of smart grid deployment, achieving milestones in smart grid data analytics in line with its green energy objectives. The country’s “13th Five-Year Plan” highlights the need for smart grid development. The plan outlines the adoption of large-scale smart meters and advanced analytics platforms for grid optimization and monitoring. Chinese energy companies have implemented big data analytics to increase grid reliability, reduce energy dissipation, and aid in integrating renewable sources like solar and wind into the national grid.
• Germany: As part of its Energiewende strategy, Germany is advancing smart grid analytics. The country is bringing in renewable energy types at a faster pace than before, making it necessary to implement advanced grid analytics for effective load balancing, forecasting, and energy distribution. In Germany, smart grid technology also aims to increase grid efficiency through the use of big data in energy management, which leads to higher carbon emission reductions. There is an aggressive move toward using predictive analytics to manage infrastructure maintenance and avoid outages.
• India: India is rapidly adopting the smart grid system, particularly in urban regions where energy needs are high. The government has rolled out initiatives such as the “Smart Grid Vision” to enhance grid reliability and manage increasing demand. Big data technology enables the monitoring of energy consumption, optimizing electricity distribution, and incorporating renewable energy. India’s efforts focus on helping rural areas develop grid infrastructure while working toward greater grid resilience and energy efficiency.
• Japan: After the Fukushima disaster in 2011, Japan began investing in smart grid solutions to increase energy efficiency. The country also uses advanced data analytics for real-time monitoring of grid performance and energy distribution. Japan has initiated smart grid development to enhance grid sophistication, integrate renewable energy, and encourage consumer interest in real-time energy consumption data. Additionally, Japan uses predictive analytics to mitigate the impacts of operating the grid during natural disasters.

Features of the Global Smart Grid Big Data Analytics Market
Market Size Estimates: Smart grid big data analytics market size estimation in terms of value ($B).
Trend and Forecast Analysis: Market trends (2019 to 2024) and forecast (2025 to 2031) by various segments and regions.
Segmentation Analysis: Smart grid big data analytics market size by type, application, and region in terms of value ($B).
Regional Analysis: Smart grid big data analytics market breakdown by North America, Europe, Asia Pacific, and Rest of the World.
Growth Opportunities: Analysis of growth opportunities in different types, applications, and regions for the smart grid big data analytics market.
Strategic Analysis: This includes M&A, new product development, and competitive landscape of the smart grid big data analytics market.
Analysis of competitive intensity of the industry based on Porter’s Five Forces model.

This report answers the following 11 key questions:
Q.1. What are some of the most promising, high-growth opportunities for the smart grid big data analytics market by type (cloud-based and on-premise), application (public sector, large enterprises, and small & medium-sized enterprises), and region (North America, Europe, Asia Pacific, and the Rest of the World)?
Q.2. Which segments will grow at a faster pace and why?
Q.3. Which region will grow at a faster pace and why?
Q.4. What are the key factors affecting market dynamics? What are the key challenges and business risks in this market?
Q.5. What are the business risks and competitive threats in this market?
Q.6. What are the emerging trends in this market and the reasons behind them?
Q.7. What are some of the changing demands of customers in the market?
Q.8. What are the new developments in the market? Which companies are leading these developments?
Q.9. Who are the major players in this market? What strategic initiatives are key players pursuing for business growth?
Q.10. What are some of the competing products in this market and how big of a threat do they pose for loss of market share by material or product substitution?
Q.11. What M&A activity has occurred in the last 5 years and what has its impact been on the industry?

ページTOPに戻る


Table of Contents

Table of Contents

1. Executive Summary

2. Market Overview
2.1 Background and Classifications
2.2 Supply Chain

3. Market Trends & Forecast Analysis
3.1 Macroeconomic Trends and Forecasts
3.2 Industry Drivers and Challenges
3.3 PESTLE Analysis
3.4 Patent Analysis
3.5 Regulatory Environment
3.6 Global Smart Grid Big Data Analytics Market Trends and Forecast

4. Global Smart Grid Big Data Analytics Market by Type
4.1 Overview
4.2 Attractiveness Analysis by Type
4.3 Cloud-Based: Trends and Forecast (2019-2031)
4.4 On-Premise: Trends and Forecast (2019-2031)

5. Global Smart Grid Big Data Analytics Market by Application
5.1 Overview
5.2 Attractiveness Analysis by Application
5.3 Public Sector: Trends and Forecast (2019-2031)
5.4 Large Enterprises: Trends and Forecast (2019-2031)
5.5 Small & Medium-Sized Enterprises: Trends and Forecast (2019-2031)

6. Regional Analysis
6.1 Overview
6.2 Global Smart Grid Big Data Analytics Market by Region

7. North American Smart Grid Big Data Analytics Market
7.1 Overview
7.2 North American Smart Grid Big Data Analytics Market by Type
7.3 North American Smart Grid Big Data Analytics Market by Application
7.4 United States Smart Grid Big Data Analytics Market
7.5 Mexican Smart Grid Big Data Analytics Market
7.6 Canadian Smart Grid Big Data Analytics Market

8. European Smart Grid Big Data Analytics Market
8.1 Overview
8.2 European Smart Grid Big Data Analytics Market by Type
8.3 European Smart Grid Big Data Analytics Market by Application
8.4 German Smart Grid Big Data Analytics Market
8.5 French Smart Grid Big Data Analytics Market
8.6 Spanish Smart Grid Big Data Analytics Market
8.7 Italian Smart Grid Big Data Analytics Market
8.8 United Kingdom Smart Grid Big Data Analytics Market

9. APAC Smart Grid Big Data Analytics Market
9.1 Overview
9.2 APAC Smart Grid Big Data Analytics Market by Type
9.3 APAC Smart Grid Big Data Analytics Market by Application
9.4 Japanese Smart Grid Big Data Analytics Market
9.5 Indian Smart Grid Big Data Analytics Market
9.6 Chinese Smart Grid Big Data Analytics Market
9.7 South Korean Smart Grid Big Data Analytics Market
9.8 Indonesian Smart Grid Big Data Analytics Market

10. ROW Smart Grid Big Data Analytics Market
10.1 Overview
10.2 ROW Smart Grid Big Data Analytics Market by Type
10.3 ROW Smart Grid Big Data Analytics Market by Application
10.4 Middle Eastern Smart Grid Big Data Analytics Market
10.5 South American Smart Grid Big Data Analytics Market
10.6 African Smart Grid Big Data Analytics Market

11. Competitor Analysis
11.1 Product Portfolio Analysis
11.2 Operational Integration
11.3 Porter’s Five Forces Analysis
• Competitive Rivalry
• Bargaining Power of Buyers
• Bargaining Power of Suppliers
• Threat of Substitutes
• Threat of New Entrants
11.4 Market Share Analysis

12. Opportunities & Strategic Analysis
12.1 Value Chain Analysis
12.2 Growth Opportunity Analysis
12.2.1 Growth Opportunities by Type
12.2.2 Growth Opportunities by Application
12.3 Emerging Trends in the Global Smart Grid Big Data Analytics Market
12.4 Strategic Analysis
12.4.1 New Product Development
12.4.2 Certification and Licensing
12.4.3 Mergers, Acquisitions, Agreements, Collaborations, and Joint Ventures

13. Company Profiles of the Leading Players Across the Value Chain
13.1 Competitive Analysis
13.2 EMC Corporation
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing
13.3 SAP SE
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing
13.4 Accenture PLC
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing
13.5 Oracle Corporation
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing
13.6 SAS Institute
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing
13.7 Capgemini
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing
13.8 Siemens
• Company Overview
• Smart Grid Big Data Analytics Business Overview
• New Product Development
• Merger, Acquisition, and Collaboration
• Certification and Licensing

14. Appendix
14.1 List of Figures
14.2 List of Tables
14.3 Research Methodology
14.4 Disclaimer
14.5 Copyright
14.6 Abbreviations and Technical Units
14.7 About Us
14.8 Contact Us

List of Figures

Chapter 1
Figure 1.1: Trends and Forecast for the Global Smart Grid Big Data Analytics Market
Chapter 2
Figure 2.1: Usage of Smart Grid Big Data Analytics Market
Figure 2.2: Classification of the Global Smart Grid Big Data Analytics Market
Figure 2.3: Supply Chain of the Global Smart Grid Big Data Analytics Market
Figure 2.4: Driver and Challenges of the Smart Grid Big Data Analytics Market
Chapter 3
Figure 3.1: Trends of the Global GDP Growth Rate
Figure 3.2: Trends of the Global Population Growth Rate
Figure 3.3: Trends of the Global Inflation Rate
Figure 3.4: Trends of the Global Unemployment Rate
Figure 3.5: Trends of the Regional GDP Growth Rate
Figure 3.6: Trends of the Regional Population Growth Rate
Figure 3.7: Trends of the Regional Inflation Rate
Figure 3.8: Trends of the Regional Unemployment Rate
Figure 3.9: Trends of Regional Per Capita Income
Figure 3.10: Forecast for the Global GDP Growth Rate
Figure 3.11: Forecast for the Global Population Growth Rate
Figure 3.12: Forecast for the Global Inflation Rate
Figure 3.13: Forecast for the Global Unemployment Rate
Figure 3.14: Forecast for the Regional GDP Growth Rate
Figure 3.15: Forecast for the Regional Population Growth Rate
Figure 3.16: Forecast for the Regional Inflation Rate
Figure 3.17: Forecast for the Regional Unemployment Rate
Figure 3.18: Forecast for Regional Per Capita Income
Chapter 4
Figure 4.1: Global Smart Grid Big Data Analytics Market by Type in 2019, 2024, and 2031
Figure 4.2: Trends of the Global Smart Grid Big Data Analytics Market ($B) by Type
Figure 4.3: Forecast for the Global Smart Grid Big Data Analytics Market ($B) by Type
Figure 4.4: Trends and Forecast for Cloud-Based in the Global Smart Grid Big Data Analytics Market (2019-2031)
Figure 4.5: Trends and Forecast for On-Premise in the Global Smart Grid Big Data Analytics Market (2019-2031)
Chapter 5
Figure 5.1: Global Smart Grid Big Data Analytics Market by Application in 2019, 2024, and 2031
Figure 5.2: Trends of the Global Smart Grid Big Data Analytics Market ($B) by Application
Figure 5.3: Forecast for the Global Smart Grid Big Data Analytics Market ($B) by Application
Figure 5.4: Trends and Forecast for Public Sector in the Global Smart Grid Big Data Analytics Market (2019-2031)
Figure 5.5: Trends and Forecast for Large Enterprises in the Global Smart Grid Big Data Analytics Market (2019-2031)
Figure 5.6: Trends and Forecast for Small & Medium-Sized Enterprises in the Global Smart Grid Big Data Analytics Market (2019-2031)
Chapter 6
Figure 6.1: Trends of the Global Smart Grid Big Data Analytics Market ($B) by Region (2019-2024)
Figure 6.2: Forecast for the Global Smart Grid Big Data Analytics Market ($B) by Region (2025-2031)
Chapter 7
Figure 7.1: Trends and Forecast for the North American Smart Grid Big Data Analytics Market (2019-2031)
Figure 7.2: North American Smart Grid Big Data Analytics Market by Type in 2019, 2024, and 2031
Figure 7.3: Trends of the North American Smart Grid Big Data Analytics Market ($B) by Type (2019-2024)
Figure 7.4: Forecast for the North American Smart Grid Big Data Analytics Market ($B) by Type (2025-2031)
Figure 7.5: North American Smart Grid Big Data Analytics Market by Application in 2019, 2024, and 2031
Figure 7.6: Trends of the North American Smart Grid Big Data Analytics Market ($B) by Application (2019-2024)
Figure 7.7: Forecast for the North American Smart Grid Big Data Analytics Market ($B) by Application (2025-2031)
Figure 7.8: Trends and Forecast for the United States Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 7.9: Trends and Forecast for the Mexican Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 7.10: Trends and Forecast for the Canadian Smart Grid Big Data Analytics Market ($B) (2019-2031)
Chapter 8
Figure 8.1: Trends and Forecast for the European Smart Grid Big Data Analytics Market (2019-2031)
Figure 8.2: European Smart Grid Big Data Analytics Market by Type in 2019, 2024, and 2031
Figure 8.3: Trends of the European Smart Grid Big Data Analytics Market ($B) by Type (2019-2024)
Figure 8.4: Forecast for the European Smart Grid Big Data Analytics Market ($B) by Type (2025-2031)
Figure 8.5: European Smart Grid Big Data Analytics Market by Application in 2019, 2024, and 2031
Figure 8.6: Trends of the European Smart Grid Big Data Analytics Market ($B) by Application (2019-2024)
Figure 8.7: Forecast for the European Smart Grid Big Data Analytics Market ($B) by Application (2025-2031)
Figure 8.8: Trends and Forecast for the German Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 8.9: Trends and Forecast for the French Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 8.10: Trends and Forecast for the Spanish Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 8.11: Trends and Forecast for the Italian Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 8.12: Trends and Forecast for the United Kingdom Smart Grid Big Data Analytics Market ($B) (2019-2031)
Chapter 9
Figure 9.1: Trends and Forecast for the APAC Smart Grid Big Data Analytics Market (2019-2031)
Figure 9.2: APAC Smart Grid Big Data Analytics Market by Type in 2019, 2024, and 2031
Figure 9.3: Trends of the APAC Smart Grid Big Data Analytics Market ($B) by Type (2019-2024)
Figure 9.4: Forecast for the APAC Smart Grid Big Data Analytics Market ($B) by Type (2025-2031)
Figure 9.5: APAC Smart Grid Big Data Analytics Market by Application in 2019, 2024, and 2031
Figure 9.6: Trends of the APAC Smart Grid Big Data Analytics Market ($B) by Application (2019-2024)
Figure 9.7: Forecast for the APAC Smart Grid Big Data Analytics Market ($B) by Application (2025-2031)
Figure 9.8: Trends and Forecast for the Japanese Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 9.9: Trends and Forecast for the Indian Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 9.10: Trends and Forecast for the Chinese Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 9.11: Trends and Forecast for the South Korean Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 9.12: Trends and Forecast for the Indonesian Smart Grid Big Data Analytics Market ($B) (2019-2031)
Chapter 10
Figure 10.1: Trends and Forecast for the ROW Smart Grid Big Data Analytics Market (2019-2031)
Figure 10.2: ROW Smart Grid Big Data Analytics Market by Type in 2019, 2024, and 2031
Figure 10.3: Trends of the ROW Smart Grid Big Data Analytics Market ($B) by Type (2019-2024)
Figure 10.4: Forecast for the ROW Smart Grid Big Data Analytics Market ($B) by Type (2025-2031)
Figure 10.5: ROW Smart Grid Big Data Analytics Market by Application in 2019, 2024, and 2031
Figure 10.6: Trends of the ROW Smart Grid Big Data Analytics Market ($B) by Application (2019-2024)
Figure 10.7: Forecast for the ROW Smart Grid Big Data Analytics Market ($B) by Application (2025-2031)
Figure 10.8: Trends and Forecast for the Middle Eastern Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 10.9: Trends and Forecast for the South American Smart Grid Big Data Analytics Market ($B) (2019-2031)
Figure 10.10: Trends and Forecast for the African Smart Grid Big Data Analytics Market ($B) (2019-2031)
Chapter 11
Figure 11.1: Porter’s Five Forces Analysis of the Global Smart Grid Big Data Analytics Market
Figure 11.2: Market Share (%) of Top Players in the Global Smart Grid Big Data Analytics Market (2024)
Chapter 12
Figure 12.1: Growth Opportunities for the Global Smart Grid Big Data Analytics Market by Type
Figure 12.2: Growth Opportunities for the Global Smart Grid Big Data Analytics Market by Application
Figure 12.3: Growth Opportunities for the Global Smart Grid Big Data Analytics Market by Region
Figure 12.4: Emerging Trends in the Global Smart Grid Big Data Analytics Market

List of Tables

Chapter 1
Table 1.1: Growth Rate (%, 2023-2024) and CAGR (%, 2025-2031) of the Smart Grid Big Data Analytics Market by Type and Application
Table 1.2: Attractiveness Analysis for the Smart Grid Big Data Analytics Market by Region
Table 1.3: Global Smart Grid Big Data Analytics Market Parameters and Attributes
Chapter 3
Table 3.1: Trends of the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 3.2: Forecast for the Global Smart Grid Big Data Analytics Market (2025-2031)
Chapter 4
Table 4.1: Attractiveness Analysis for the Global Smart Grid Big Data Analytics Market by Type
Table 4.2: Market Size and CAGR of Various Type in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 4.3: Market Size and CAGR of Various Type in the Global Smart Grid Big Data Analytics Market (2025-2031)
Table 4.4: Trends of Cloud-Based in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 4.5: Forecast for Cloud-Based in the Global Smart Grid Big Data Analytics Market (2025-2031)
Table 4.6: Trends of On-Premise in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 4.7: Forecast for On-Premise in the Global Smart Grid Big Data Analytics Market (2025-2031)
Chapter 5
Table 5.1: Attractiveness Analysis for the Global Smart Grid Big Data Analytics Market by Application
Table 5.2: Market Size and CAGR of Various Application in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 5.3: Market Size and CAGR of Various Application in the Global Smart Grid Big Data Analytics Market (2025-2031)
Table 5.4: Trends of Public Sector in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 5.5: Forecast for Public Sector in the Global Smart Grid Big Data Analytics Market (2025-2031)
Table 5.6: Trends of Large Enterprises in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 5.7: Forecast for Large Enterprises in the Global Smart Grid Big Data Analytics Market (2025-2031)
Table 5.8: Trends of Small & Medium-Sized Enterprises in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 5.9: Forecast for Small & Medium-Sized Enterprises in the Global Smart Grid Big Data Analytics Market (2025-2031)
Chapter 6
Table 6.1: Market Size and CAGR of Various Regions in the Global Smart Grid Big Data Analytics Market (2019-2024)
Table 6.2: Market Size and CAGR of Various Regions in the Global Smart Grid Big Data Analytics Market (2025-2031)
Chapter 7
Table 7.1: Trends of the North American Smart Grid Big Data Analytics Market (2019-2024)
Table 7.2: Forecast for the North American Smart Grid Big Data Analytics Market (2025-2031)
Table 7.3: Market Size and CAGR of Various Type in the North American Smart Grid Big Data Analytics Market (2019-2024)
Table 7.4: Market Size and CAGR of Various Type in the North American Smart Grid Big Data Analytics Market (2025-2031)
Table 7.5: Market Size and CAGR of Various Application in the North American Smart Grid Big Data Analytics Market (2019-2024)
Table 7.6: Market Size and CAGR of Various Application in the North American Smart Grid Big Data Analytics Market (2025-2031)
Table 7.7: Trends and Forecast for the United States Smart Grid Big Data Analytics Market (2019-2031)
Table 7.8: Trends and Forecast for the Mexican Smart Grid Big Data Analytics Market (2019-2031)
Table 7.9: Trends and Forecast for the Canadian Smart Grid Big Data Analytics Market (2019-2031)
Chapter 8
Table 8.1: Trends of the European Smart Grid Big Data Analytics Market (2019-2024)
Table 8.2: Forecast for the European Smart Grid Big Data Analytics Market (2025-2031)
Table 8.3: Market Size and CAGR of Various Type in the European Smart Grid Big Data Analytics Market (2019-2024)
Table 8.4: Market Size and CAGR of Various Type in the European Smart Grid Big Data Analytics Market (2025-2031)
Table 8.5: Market Size and CAGR of Various Application in the European Smart Grid Big Data Analytics Market (2019-2024)
Table 8.6: Market Size and CAGR of Various Application in the European Smart Grid Big Data Analytics Market (2025-2031)
Table 8.7: Trends and Forecast for the German Smart Grid Big Data Analytics Market (2019-2031)
Table 8.8: Trends and Forecast for the French Smart Grid Big Data Analytics Market (2019-2031)
Table 8.9: Trends and Forecast for the Spanish Smart Grid Big Data Analytics Market (2019-2031)
Table 8.10: Trends and Forecast for the Italian Smart Grid Big Data Analytics Market (2019-2031)
Table 8.11: Trends and Forecast for the United Kingdom Smart Grid Big Data Analytics Market (2019-2031)
Chapter 9
Table 9.1: Trends of the APAC Smart Grid Big Data Analytics Market (2019-2024)
Table 9.2: Forecast for the APAC Smart Grid Big Data Analytics Market (2025-2031)
Table 9.3: Market Size and CAGR of Various Type in the APAC Smart Grid Big Data Analytics Market (2019-2024)
Table 9.4: Market Size and CAGR of Various Type in the APAC Smart Grid Big Data Analytics Market (2025-2031)
Table 9.5: Market Size and CAGR of Various Application in the APAC Smart Grid Big Data Analytics Market (2019-2024)
Table 9.6: Market Size and CAGR of Various Application in the APAC Smart Grid Big Data Analytics Market (2025-2031)
Table 9.7: Trends and Forecast for the Japanese Smart Grid Big Data Analytics Market (2019-2031)
Table 9.8: Trends and Forecast for the Indian Smart Grid Big Data Analytics Market (2019-2031)
Table 9.9: Trends and Forecast for the Chinese Smart Grid Big Data Analytics Market (2019-2031)
Table 9.10: Trends and Forecast for the South Korean Smart Grid Big Data Analytics Market (2019-2031)
Table 9.11: Trends and Forecast for the Indonesian Smart Grid Big Data Analytics Market (2019-2031)
Chapter 10
Table 10.1: Trends of the ROW Smart Grid Big Data Analytics Market (2019-2024)
Table 10.2: Forecast for the ROW Smart Grid Big Data Analytics Market (2025-2031)
Table 10.3: Market Size and CAGR of Various Type in the ROW Smart Grid Big Data Analytics Market (2019-2024)
Table 10.4: Market Size and CAGR of Various Type in the ROW Smart Grid Big Data Analytics Market (2025-2031)
Table 10.5: Market Size and CAGR of Various Application in the ROW Smart Grid Big Data Analytics Market (2019-2024)
Table 10.6: Market Size and CAGR of Various Application in the ROW Smart Grid Big Data Analytics Market (2025-2031)
Table 10.7: Trends and Forecast for the Middle Eastern Smart Grid Big Data Analytics Market (2019-2031)
Table 10.8: Trends and Forecast for the South American Smart Grid Big Data Analytics Market (2019-2031)
Table 10.9: Trends and Forecast for the African Smart Grid Big Data Analytics Market (2019-2031)
Chapter 11
Table 11.1: Product Mapping of Smart Grid Big Data Analytics Suppliers Based on Segments
Table 11.2: Operational Integration of Smart Grid Big Data Analytics Manufacturers
Table 11.3: Rankings of Suppliers Based on Smart Grid Big Data Analytics Revenue
Chapter 12
Table 12.1: New Product Launches by Major Smart Grid Big Data Analytics Producers (2019-2024)
Table 12.2: Certification Acquired by Major Competitor in the Global Smart Grid Big Data Analytics Market

 

ページTOPに戻る

ご注文は、お電話またはWEBから承ります。お見積もりの作成もお気軽にご相談ください。

webからのご注文・お問合せはこちらのフォームから承ります


よくあるご質問


Lucintel社はどのような調査会社ですか?


Lucintelは世界の多様な市場について調査を行っています。特に化学品、材料、自動車関連の調査レポートを数多く出版しています。  もっと見る


調査レポートの納品までの日数はどの程度ですか?


在庫のあるものは速納となりますが、平均的には 3-4日と見て下さい。
但し、一部の調査レポートでは、発注を受けた段階で内容更新をして納品をする場合もあります。
発注をする前のお問合せをお願いします。


注文の手続きはどのようになっていますか?


1)お客様からの御問い合わせをいただきます。
2)見積書やサンプルの提示をいたします。
3)お客様指定、もしくは弊社の発注書をメール添付にて発送してください。
4)データリソース社からレポート発行元の調査会社へ納品手配します。
5) 調査会社からお客様へ納品されます。最近は、pdfにてのメール納品が大半です。


お支払方法の方法はどのようになっていますか?


納品と同時にデータリソース社よりお客様へ請求書(必要に応じて納品書も)を発送いたします。
お客様よりデータリソース社へ(通常は円払い)の御振り込みをお願いします。
請求書は、納品日の日付で発行しますので、翌月最終営業日までの当社指定口座への振込みをお願いします。振込み手数料は御社負担にてお願いします。
お客様の御支払い条件が60日以上の場合は御相談ください。
尚、初めてのお取引先や個人の場合、前払いをお願いすることもあります。ご了承のほど、お願いします。


データリソース社はどのような会社ですか?


当社は、世界各国の主要調査会社・レポート出版社と提携し、世界各国の市場調査レポートや技術動向レポートなどを日本国内の企業・公官庁及び教育研究機関に提供しております。
世界各国の「市場・技術・法規制などの」実情を調査・収集される時には、データリソース社にご相談ください。
お客様の御要望にあったデータや情報を抽出する為のレポート紹介や調査のアドバイスも致します。



詳細検索

このレポートへのお問合せ

03-3582-2531

電話お問合せもお気軽に

 

 

2025/10/02 10:27

148.19 円

174.08 円

202.32 円

ページTOPに戻る