全球能源和公用事業分析市場規模：按類型、部署模型、地區、範圍和預測

能源和公用事業分析市場規模和預測

2023 年能源和公用事業分析市場規模為 30.7 億美元，預計 2024 年至 2031 年複合年增長率為 16.5%，到 2031 年將達到 104.1 億美元。能源和公用事業分析是對與能源生產、分配和消耗相關的數據進行的系統計算研究。該領域利用大數據、機器學習和物聯網 (IoT) 等先進技術來收集、處理和解釋來自能源市場眾多來源的大量數據。其主要目的是透過提供可行的見解來優化營運、提高效率、促進永續性並支援決策流程。這包括使用智慧電錶、電網感測器和再生能源的數據來預測需求、避免停電並節省金錢。

分析應用於各種能源產業領域，包括發電、輸電、配電和消費。發電分析有助於預測設備維護、優化燃料並有效整合再生能源。輸配電分析透過預測和減輕潛在故障、優化負載平衡和改進故障檢測來確保電網的可靠性和穩定性。

該分析使住宅和企業消費者能夠更輕鬆地實施需求響應系統、創建量身定制的節能建議以及創建動態定價模型。此外，公用事業公司正在利用這些見解來提供即時使用數據、斷電警報和客製化能源解決方案，以改善客戶服務。

能源和公用事業分析涵蓋了旨在改變能源產業的廣泛功能。主要功能包括即時數據監控和分析、維護和可靠性預測分析以及能源分配和消耗優化演算法。異常檢測和故障預測等進階功能可提高電網安全性和效率。

全球能源和公用事業分析市場動態

主要市場推動因素

能源需求和消費模式的增加：

由於人口成長和工業擴張，全球能源消耗穩定增加，對有效能源管理的需求不斷增加。能源和公用事業分析可幫助公用事業公司識別和預測使用模式，從而實現更準確的需求預測。這改善了資源分配，減少了能源浪費，並使生產計劃更有效率。先進的分析有助於將再生能源整合到電網中，提供可靠且平衡的能源供應，滿足不斷增長的需求，同時對環境負責。

再生能源的整合：

環境問題和法規正在推動向太陽能、風能和水力發電等再生能源的轉變。將這些可變能源整合到常規系統中存在重大障礙。能源分析透過預測再生能源發電、優化能源儲存系統和確保電網穩定性來幫助解決這些複雜問題。透過評估天氣模式和歷史數據，公用事業公司可以更好地估計再生能源輸出並將其整合到傳統電力系統中。

監理合規性和環境問題：

世界各國政府正在製定嚴格的法規來限制碳排放並鼓勵永續能源實踐。能源和公用事業分析使公用事業公司能夠正確監控和報告污染物並確保遵守環境標準。此外，分析可以優化能源生產運營，以減少對環境的影響並支持企業社會責任。這種對合規性和永續性的推動是市場的關鍵驅動力，推動公用事業公司採用先進的分析解決方案。

提高客戶參與度和服務交付：

客戶對能源業務的期望正在發生變化，對個人化服務和即時資訊的需求不斷增加。能源和公用事業分析使公用事業公司能夠向客戶提供有針對性的節能建議、動態定價模型和即時使用統計數據。消費者參與度的提高可以提高滿意度和忠誠度，從而鼓勵公用事業公司投資分析解決方案。透過主動停電管理和快速問題回應提供更好的服務，進一步加強客戶和公用事業公司之間的聯繫。

主要課題

數據品質和整合：

能源和公用事業分析中最困難的課題之一是確保高品質和可靠的數據。來自不同來源（例如智慧電錶、物聯網設備和遺留系統）的資料通常具有不同的格式和標準。將這些不同的數據整合到統一的系統中可能很困難，並且會導致不一致和錯誤。數據品質差會對分析見解的有效性產生重大影響。確保資料的清潔性、準確性和跨平台相容性需要強大的資料管理策略、對資料整合技術的大量投資以及持續的維護。

網路安全威脅：

能源產業越來越依賴數位技術和網路系統，這使其成為網路攻擊的有吸引力的目標。保護敏感資料和關鍵基礎設施免受網路威脅是首要任務。高級分析系統必須安全，以避免資料外洩和不必要的存取。採取強有力的網路安全措施（例如加密、入侵偵測系統和定期安全審核）至關重要，但可能成本高且複雜。確保遵守網路安全法律和標準也增加了課題。

監理和合規問題：

駕馭能源業務複雜的監管架構是部署分析解決方案的關鍵障礙。有關資料隱私、安全和環境規範的法規因地區而異。確保遵守這些標準，同時利用數據進行分析需要仔細的準備和強大的治理結構。此外，規則會不斷變化，因此必須持續監控和調整分析系統以確保合規性。

變革管理與組織阻力：

實施分析解決方案通常需要對現有流程和工作流程進行重大變更。組織對變革的抵制可能是成功實施的主要障礙。員工可能對新技術持謹慎態度，擔心它會奪走他們的工作或使他們的角色複雜化。有效的變革管理策略，例如清晰的溝通、培訓計劃和員工參與實施過程，對於克服阻力並確保分析解決方案的順利實施至關重要。

主要趨勢：

物聯網和智慧型設備的普及：

能源產業中物聯網 (IoT) 設備的整合是推動分析市場的關鍵趨勢。智慧電錶、感測器和連網設備會產生大量數據，揭示有關能源使用模式、設備性能和電網健康狀況的精確資訊。這些數據對於即時監控和預測分析至關重要，使公用事業公司能夠優化營運、增加客戶互動並提高能源效率。隨著物聯網設備的採用不斷增加，對能夠處理大量資料並從中提取相關見解的高階分析系統的需求可能會增加。

採用人工智慧和機器學習：

人工智慧和機器學習正在改變能源和公用事業分析的格局。這些技術透過評估歷史和即時數據的模式和趨勢來改善預測、異常檢測和預測性維護。人工智慧和機器學習演算法可以優化能源生產和分配、降低營運成本並提高電網可靠性。如今，人工智慧和機器學習正在推動能源分析，因為透過機器學習驅動的洞察來預測設備故障和優化維護計劃的能力可以顯著提高營運效率並減少停機時間，這已成為解決方案的重要組成部分。

聚焦再生能源併網：

在能源領域，向太陽能、風電、水力等再生能源的轉變明顯。能源和公用事業分析是將這些可變能源整合到電網的關鍵組成部分。先進的分析工具有助於估計再生能源輸出、改善能源儲存並確保系統穩定性。透過監控天氣模式和歷史數據，公用事業公司可以更好地估計再生能源產量並確保平衡和可靠的電力供應。隨著世界轉向更永續的能源，這一趨勢預計將持續下去。

邊緣運算的興起：

邊緣運算作為一種更接近源頭處理資料、減少延遲並支援即時決策的方法，在能源領域越來越受歡迎。透過在網路邊緣實施分析，公用事業公司可以立即分析來自感測器和智慧設備的數據，縮短對營運問題的回應時間，並提高電網可靠性。邊緣運算支援即時監控、預測性維護和需求響應系統等高階應用。這一趨勢是由日益互聯的能源產業對低延遲、高效能分析解決方案日益增長的需求所推動的。

全球能源和公用事業分析的區域分析

歐洲：

歐洲：歐洲已成為能源和公用事業分析市場的主要參與者，市佔率落後於北美。該地區能源和公用事業領域分析解決方案的使用顯著增加。採用這種技術的主要動機是需要更好的能源風險管理、電網分析、需求預測和收入保證措施。隨著歐洲國家尋求更新其能源基礎設施並轉向更永續的實踐，對先進分析解決方案的需求不斷增長。

歐洲能源和公用事業分析市場按國家/地區進行細分，以代表該地區的不同區域。該市場的主要國家包括英國、德國、法國、義大利、西班牙和歐洲其他國家。每個國家都為分析解決方案提供者提供獨特的機會和課題，並受到法律框架、能源政策、市場動態和技術改進的影響。例如，英國處於智慧電網計劃的前沿，推動了對分析解決方案的需求，以提高電網性能並促進再生能源的整合。

在整個歐洲，公用事業公司越來越多地使用分析來優化營運、提高效率和消費者滿意度。電網分析允許公用事業公司即時追蹤和控制電網性能，以保持可靠性和穩定性。需求預測使公用事業公司能夠更準確地估計能源需求，從而改善資源分配和規劃。

此外，分析工具可以透過發現收入洩漏、優化定價策略和提高計費準確性來幫助確保收入安全。隨著歐洲國家繼續投資數位轉型計劃，該地區的能源和公用事業分析市場預計將擴大和創新。

亞太地區：

預計亞太地區能源和公用事業分析市場在預測期內將以 20.03% 的複合年增長率 (CAGR) 強勁成長。這種快速成長是由該地區對預測性維護、負載管理和預測解決方案不斷增長的需求所推動的，以滿足不斷變化的消費者期望並維持能源基礎設施高效運作。亞太國家正在經歷快速的城市化、工業化和數位化，分析在改善能源生產、供應和消費方面的作用日益廣泛認可。

亞太地區能源和公用事業分析市場按國家/地區劃分，以代表該地區不同的地理位置和不同的市場動態。中國、日本、印度、韓國、澳洲和亞太地區其他國家是該產業的主要參與者。每個國家對於分析解決方案提供者都有不同的機會和限制，受到法律框架、技術準備、投資目標和能源基礎設施發展的影響。

亞太地區的公用事業公司越來越依賴分析解決方案來優化營運並解決能源產業日益複雜的問題。預測性維護分析使您能夠主動識別和解決設備故障，從而減少停機時間和維護成本。負載管理分析可協助公用事業公司改善供需之間的平衡，並提高電網的穩定性和可靠性。

預測技術使公用事業公司能夠準確預測能源需求趨勢，從而實現更好的資源規劃和分配。隨著人們對能源效率、永續性和數位轉型的日益關注，亞太地區的能源和公用事業分析產業預計將出現顯著的成長和創新。

目錄

第1章全球能源與公用事業分析市場簡介

• 市場概況
• 調查範圍
• 先決條件

第 2 章執行摘要

第3章 驗證市場研究研究方法

• 數據挖掘
• 驗證
• 一次資料
• 數據源列表

第4章全球能源與公用事業分析市場展望

• 概述
• 市場動態
  • 促進因素
  • 阻礙因素
  • 機會
• 波特的五力模型
• 價值鏈分析

第5章全球能源和公用事業分析市場：按類型

• 概述
• 軟體
• 服務

第6章全球能源與公用事業分析市場：依部署模型

• 概述
• 本地
• 雲端
• 混合

第7章 全球能源與公用事業分析市場：按地區

• 概述
• 北美
  • 美國
  • 加拿大
  • 墨西哥
• 歐洲
  • 德國
  • 英國
  • 法國
  • 歐洲其他地區
• 亞太地區
  • 中國
  • 日本
  • 印度
  • 亞太其他地區
• 世界其他地區
  • 拉丁美洲
  • 中東

第8章全球能源與公用事業分析市場：競爭格局

• 概述
• 各公司市場排名
• 主要發展策略

第9章 公司簡介

• IBM Corporation
• Intel Corporation
• SAP SE
• Ericsson
• Cisco Systems Inc.
• Eaton Corporation
• Schneider Electric Company
• Capgemini
• Oracle Corporation
• Infosys

第10章附錄

• 相關研究

Energy and Utility Analytics Market Size And Forecast

Energy And Utility Analytics Market size was valued at USD 3.07 Billion in 2023 and is projected to reach USD 10.41 Billion by 2031 , growing at a CAGR of 16.5% from 2024 to 2031. Energy and Utility Analytics is the systematic computational study of data pertaining to energy production, distribution, and consumption. This field uses advanced technologies like big data, machine learning, and IoT (Internet of Things) to collect, process, and interpret massive volumes of data from numerous sources in the energy market. The primary purpose is to optimize operations, increase efficiency, promote sustainability, and aid decision-making processes by giving actionable insights. This includes using data from smart meters, grid sensors, and renewable energy sources to forecast demand, avoid outages, and save money.

The analytics are used in a variety of energy industry segments, including generation, transmission, distribution, and consumption. Analytics in generation aids in predicting equipment maintenance, fuel optimization, and effective integration of renewable energy sources. Analytics in transmission and distribution guarantee grid reliability and stability by forecasting and mitigating probable failures, optimizing load balancing, and improving fault detection.

Analytics make it easier for residential and business consumers to implement demand response systems, make individualized energy-saving recommendations, and create dynamic pricing models. Furthermore, utilities leverage these insights to improve customer service by offering real-time usage data, outage alerts, and customized energy solutions.

Energy and Utility Analytics spans a wide range of functionalities designed to transform the energy sector. Key characteristics include real-time data monitoring and analysis, predictive analytics for maintenance and reliability, and energy distribution and consumption optimization algorithms. Advanced features, such as anomaly detection and failure prediction, improve grid security and efficiency.

Global Energy And Utility Analytics Market Dynamics

The key market dynamics that are shaping the global energy and utility analytics market include:

Key Market Drivers:

Increasing Energy Demand and Consumption Patterns:

With global energy consumption steadily rising due to population growth and industrial expansion, there is an increased demand for effective energy management. Energy and utility analytics assist utilities identify and predict usage patterns, allowing for more accurate demand forecasts. This leads to improved resource allocation, less energy waste, and more efficient production schedules. Advanced analytics make it easier to integrate renewable energy sources into the grid, resulting in a dependable and balanced energy supply that fulfills expanding demand while being environmentally friendly.

Integration of Renewable Energy Sources:

Environmental concerns and regulatory regulations are driving the transition to renewable energy sources such as solar, wind, and hydropower. Integrating these variable energy sources into the regular system presents substantial hurdles. Energy analytics helps to handle these complications by projecting renewable energy generation, optimizing storage systems, and guaranteeing grid stability. By evaluating weather patterns and historical data, utilities can better estimate renewable energy output and integrate it into traditional power systems.

Regulatory Compliance and Environmental Concerns:

Governments around the world are enacting strict restrictions to limit carbon emissions and encourage sustainable energy practices. Energy and utility analytics allow utilities to correctly monitor and report pollutants, guaranteeing compliance with environmental standards. Furthermore, analytics aid in optimizing energy production operations to reduce environmental effects, hence supporting corporate social responsibility objectives. This drive for compliance and sustainability is a major market driver, compelling utilities to employ advanced analytical solutions.

Improved Customer Engagement and Service Delivery:

Customer expectations in the energy business are changing, with a greater need for individualized services and real-time information. Energy and utility analytics enable utilities to provide targeted energy-saving recommendations, dynamic pricing models, and real-time usage statistics to customers. Improved consumer involvement leads to increased satisfaction and loyalty, which encourages utilities to invest in analytics solutions. Better service delivery through proactive outage management and faster issue response further strengthens the customer-utility connection.

Key Challenges:

Data Quality and Integration:

One of the most difficult difficulties in energy and utility analytics is assuring high-quality, reliable data. Data from diverse sources, such as smart meters, IoT devices, and older systems, frequently has distinct forms and standards. Integrating these different data into a unified system is difficult and can lead to inconsistencies and mistakes. Poor data quality can have a substantial impact on the validity of analytical insights. Ensuring data cleanliness, accuracy, and compatibility across platforms necessitates strong data management strategies, significant investment in data integration technology, and continuous maintenance.

Cybersecurity Threats:

The energy sector's increasing reliance on digital technologies and networked systems makes it an attractive target for cyberattacks. Protecting sensitive data and key infrastructure from cyber threats is a top priority. Advanced analytics systems must be safe to avoid data breaches and unwanted access. Implementing strong cybersecurity measures, including as encryption, intrusion detection systems, and regular security audits, is critical, but it can be expensive and complex. Ensuring compliance with cybersecurity legislation and standards adds to the challenge.

Regulatory and Compliance Issues:

Navigating the complicated regulatory framework of the energy business is a key hurdle for deploying analytics solutions. Regulations governing data privacy, security, and environmental norms differ by area. Ensuring compliance with these standards while using data for analytics necessitates meticulous preparation and strong governance structures. Furthermore, rules are continually changing, needing ongoing monitoring and adaption of analytics systems to ensure compliance.

Change Management and Organizational Resistance:

Implementing analytics solutions frequently necessitates considerable modifications to existing processes and workflows. Organizational resistance to change can be a significant impediment to successful implementation. Employees may be wary of new technologies, fearing job displacement or increasing complexity in their roles. Effective change management tactics, including as clear communication, training programs, and staff participation in the implementation process, are critical for overcoming resistance and ensuring the smooth adoption of analytics solutions.

Key Trends:

Proliferation of IoT and Smart Devices:

The integration of Internet of Things (IoT) devices in the energy industry is a major trend propelling the analytics market. Smart meters, sensors, and linked appliances generate massive volumes of data, revealing precise information about energy usage patterns, equipment performance, and grid health. This data is critical for real-time monitoring and predictive analytics, which allow utilities to optimize operations, increase customer interaction, and improve energy efficiency. The growing deployment of IoT devices is likely to fuel demand for sophisticated analytics systems capable of processing and extracting relevant insights from huge datasets.

Adoption of AI and Machine Learning:

AI and ML are changing the energy and utilities analytics landscape. These technologies improve forecasting, anomaly detection, and predictive maintenance by evaluating patterns and trends in historical and real-time data. Artificial intelligence and machine learning algorithms can optimize energy generation and distribution, lower operational costs, and improve grid dependability. The ability to predict equipment failures and optimize maintenance schedules using ML-driven insights can greatly improve operational efficiency and reduce downtime, making AI and ML essential components of current energy analytics solutions.

Focus on Renewable Energy Integration:

The energy sector is seeing a significant shift toward renewable energy sources such as solar, wind, and hydropower. Energy and utility analytics are critical components in integrating these variable energy sources into the grid. Advanced analytics tools aid in estimating renewable energy output, improving energy storage, and ensuring system stability. By monitoring weather patterns and historical data, utilities can better estimate renewable energy output and assure a balanced and dependable power supply. This trend is projected to continue as the world transitions to more sustainable energy sources.

Rise of Edge Computing:

Edge computing is gaining popularity in the energy sector as a way to process data closer to its source, lowering latency and boosting real-time decision-making. By implementing analytics capabilities at the network's edge, utilities may instantly analyze data from sensors and smart devices, resulting in faster response times to operational issues and increased grid reliability. Edge computing enables advanced applications including real-time monitoring, predictive maintenance, and demand response systems. This trend is driven by the growing demand for low-latency, high-performance analytics solutions in the increasingly interconnected energy landscape.

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Global Energy And Utility Analytics Regional Analysis

Here is a more detailed regional analysis of the global energy and utility analytics market:

Europe:

Europe is emerging as a major participant in the energy and utilities analytics markets, trailing only North America in terms of market share. The region is experiencing a significant increase in the usage of analytical solutions in the energy and utilities sectors. This adoption is primarily motivated by the need for better energy risk management, grid analytics, demand forecasting, and revenue assurance measures. As European countries attempt to update their energy infrastructure and shift to more sustainable practices, the need for advanced analytics solutions is increasing.

The European market for energy and utilities analytics has been divided into country segments to represent the region's diversified geography. Key nations in this market include the United Kingdom, Germany, France, Italy, Spain, England, and the rest of Europe. Each country offers distinct opportunities and challenges for analytics solution providers, influenced by legislative frameworks, energy policies, market dynamics, and technical improvements. The United Kingdom, for example, has been at the forefront of smart grid initiatives, boosting demand for analytics solutions to improve grid performance and facilitate renewable energy integration.

Across Europe, utilities are increasingly using analytics to optimize operations, increase efficiency, and improve consumer happiness. Grid analytics allow utilities to track and control grid performance in real time, maintaining reliability and stability. Demand forecasting allows utilities to more correctly estimate energy needs, resulting in improved resource allocation and planning.

Additionally, analytics tools help with revenue assurance by discovering revenue leaks, optimizing pricing tactics, and improving billing accuracy. As European countries continue to invest in digital transformation programs, the region's energy and utilities analytics market is expected to expand and innovate.

Asia Pacific:

Asia-Pacific is predicted to experience significant growth in the energy and utilities analytics market, with a Compound Annual Growth Rate (CAGR) of 20.03% over the forecast period. This spike is being driven by the region's growing demand for predictive maintenance, load management, and forecasting solutions to meet changing consumer expectations and maintain the efficient operation of energy infrastructure. As Asia-Pacific countries experience fast urbanization, industrialization, and digitization, the role of analytics in improving energy production, delivery, and consumption is becoming more widely recognized.

The Asia-Pacific energy and utilities analytics market is divided into nation segments to represent the region's diversified terrain and varying market dynamics. China, Japan, India, South Korea, Australia, and the rest of Asia-Pacific are key players in this industry. Each country has distinct opportunities and constraints for analytics solution providers, influenced by legal frameworks, technical preparedness, investment goals, and energy infrastructure development.

Utilities in Asia-Pacific are increasingly relying on analytics solutions to optimize operations and meet the growing complexities of the energy sector. Predictive maintenance analytics enable utilities to discover and address equipment faults before they occur, lowering downtime and maintenance costs. Load management analytics help utilities to better balance supply and demand, resulting in grid stability and reliability.

Forecasting technologies allow utilities to precisely predict energy demand trends, resulting in better resource planning and allocation. With a growing emphasis on energy efficiency, sustainability, and digital transformation, Asia-Pacific's energy and utilities analytics industry is set to grow and innovate significantly.

Global Energy And Utility Analytics Market: Segmentation Analysis

The Global Energy And Utility Analytics is Segmented on the basis of Type, Deployment Model, And Geography.

Energy And Utility Analytics Market, By Type

• Software
• Service

Based on Type, the market is segmented into Software and Service. Software is currently the dominant segment. This is because software solutions serve as the primary analytical instruments for data collecting, processing, and visualization. These tools enable utilities and energy firms to get insights into their operations and make educated decisions. Cloud-based services are witnessing the most rapid growth. Cloud services provide numerous benefits, including scalability, cost-effectiveness, and ease of setup. This makes them appealing to businesses of all sizes, particularly those seeking to avoid the initial costs of on-premise software.

Energy And Utility Analytics Market, By Deployment Model

• On-Premise
• Cloud
• Hybrid

Based on Deployment Model, the market is bifurcated into On-Premise, Cloud, and Hybrid. The cloud segment is predominated because of its scalability, adaptability, and cost-effectiveness. Cloud-based analytics solutions enable utilities to have access to advanced analytical tools and infrastructure without requiring large upfront investments in hardware or software. This category is rapidly expanding as utilities strive to use the agility and scalability of cloud platforms to swiftly install and scale analytics solutions, therefore driving operational efficiency and innovation. The Hybrid segment has emerged as the fastest-growing segment in the Energy and Utility Analytics Market. Hybrid solutions combine on-premise and cloud-based deployment strategies, allowing utilities to manage sensitive data on-premise while leveraging the scalability and accessibility of the cloud for analytical workloads.

Key Players

• The "Global Energy And Utility Analytics Market" study report will provide valuable insight with an emphasis on the global market. The major players in the market are
• IBM Corporation, Intel Corporation, SAP SE, Ericsson, Cisco Systems, Inc., Eaton Corporation, Schneider Electric Company, Capgemini, Oracle Corporation, TIBCO Software, Inc., Infosys, and Wipro.
• The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

Our market analysis also entails a section solely dedicated to such major players wherein our analysts provide an insight into the financial statements of all the major players, along with product benchmarking and SWOT analysis. The competitive landscape section also includes key development strategies, market share, and market ranking analysis of the above-mentioned players globally.

• Energy And Utility Analytics Market Recent Developments
• In August 2022, mCloud Technologies Corp., an AI-powered asset management and Environmental, Social, and Governance ("ESG") solutions provider, signed an agreement with Agnity Inc.
• In May 2022, Siemens will bring its tried-and-true transmission grid modeling software, PSS-E, to the cloud. It makes use of the same software and user interface, as well as over 2,000 APIs and existing scripts.

TABLE OF CONTENTS

1 INTRODUCTION OF GLOBAL ENERGY AND UTILITY ANALYTICS

• 1.1 Overview of the Market
• 1.2 Scope of Report
• 1.3 Assumptions

2 EXECUTIVE SUMMARY

3 RESEARCH METHODOLOGY OF VERIFIED MARKET RESEARCH

• 3.1 Data Mining
• 3.2 Validation
• 3.3 Primary Interviews
• 3.4 List of Data Sources

4 GLOBAL ENERGY AND UTILITY ANALYTICS OUTLOOK

• 4.1 Overview
• 4.2 Market Dynamics
  • 4.2.1 Drivers
  • 4.2.2 Restraints
  • 4.2.3 Opportunities
• 4.3 Porters Five Force Model
• 4.4 Value Chain Analysis

5 GLOBAL ENERGY AND UTILITY ANALYTICS, BY TYPE

• 5.1 Overview
• 5.2 Software
• 5.3 Service

6 GLOBAL ENERGY AND UTILITY ANALYTICS, BY DEPLOYMENT MODEL

• 6.1 Overview
• 6.2 On-Premise
• 6.3 Cloud
• 6.4 Hybrid

7 GLOBAL ENERGY AND UTILITY ANALYTICS, BY GEOGRAPHY

• 7.1 Overview
• 7.2 North America
  • 7.2.1 U.S.
  • 7.2.2 Canada
  • 7.2.3 Mexico
• 7.3 Europe
  • 7.3.1 Germany
  • 7.3.2 U.K.
  • 7.3.3 France
  • 7.3.4 Rest of Europe
• 7.4 Asia Pacific
  • 7.4.1 China
  • 7.4.2 Japan
  • 7.4.3 India
  • 7.4.4 Rest of Asia Pacific
• 7.5 Rest of the World
  • 7.5.1 Latin America
  • 7.5.2 Middle East

8 GLOBAL ENERGY AND UTILITY ANALYTICS COMPETITIVE LANDSCAPE

• 8.1 Overview
• 8.2 Company Market Ranking
• 8.3 Key Development Strategies

9 COMPANY PROFILES

• 9.1 IBM Corporation
  • 9.1.1 Overview
  • 9.1.2 Financial Performance
  • 9.1.3 Product Outlook
  • 9.1.4 Key Developments
• 9.2 Intel Corporation
  • 9.2.1 Overview
  • 9.2.2 Financial Performance
  • 9.2.3 Product Outlook
  • 9.2.4 Key Developments
• 9.3 SAP SE
  • 9.3.1 Overview
  • 9.3.2 Financial Performance
  • 9.3.3 Product Outlook
  • 9.3.4 Key Developments
• 9.4 Ericsson
  • 9.4.1 Overview
  • 9.4.2 Financial Performance
  • 9.4.3 Product Outlook
  • 9.4.4 Key Developments
• 9.5 Cisco Systems Inc.
  • 9.5.1 Overview
  • 9.5.2 Financial Performance
  • 9.5.3 Product Outlook
  • 9.5.4 Key Developments
• 9.6 Eaton Corporation
  • 9.6.1 Overview
  • 9.6.2 Financial Performance
  • 9.6.3 Product Outlook
  • 9.6.4 Key Developments
• 9.7 Schneider Electric Company
  • 9.7.1 Overview
  • 9.7.2 Financial Performance
  • 9.7.3 Product Outlook
  • 9.7.4 Key Developments
• 9.8 Capgemini
  • 9.8.1 Overview
  • 9.8.2 Financial Performance
  • 9.8.3 Product Outlook
  • 9.8.4 Key Developments
• 9.9 Oracle Corporation
  • 9.9.1 Overview
  • 9.9.2 Financial Performance
  • 9.9.3 Product Outlook
  • 9.9.4 Key Developments
• 9.10 Infosys
  • 9.10.1 Overview
  • 9.10.2 Financial Performance
  • 9.10.3 Product Outlook
  • 9.10.4 Key Developments

10 Appendix

• 10.1 Related Research