NEW YORK, Dec. 14, 2010 /PRNewswire/ -- Reportlinker.com announces that a new market research report is available in its catalogue:
http://www.reportlinker.com/p0346136/Smart-Grid-Data-Analytics.html
Smart Grid Data Analytics
Business Intelligence, Situational Awareness, and Predictive Analytics for Utility Customer Information and Grid Operations: Market Analysis and Forecasts
Smart Grid Data Analytics Information is the lifeblood of every organization. As utilities transition to the smart grid and expand it over time with the installation of thousands and sometimes millions of smart meters, they must address the most challenging question. How can I take advantage of the flood of data resulting from the smart meters and other intelligent devices on the smart grid? As soon as a utility company begins to receive data, it must be able to transform the raw data into useful information, such as reviewing it for any changes or events in the grid that trigger alarms into outage management systems and other real-time systems. Data analytics plays a major role in converting volume of data into business value – from the very beginning of a smart grid deployment.
There are multiple market forces fueling a growing demand among utilities for smart grid data analytics software and services, but one major driver is the significant benefit that can be derived by turning data into valuable and actionable information through analysis of the massive amount of data that is generated by smart meters and other devices. Utilizing smart grid data analytics tools and related services, utilities will be able to gain better insights into their customers' energy consumption behavior to serve them more effectively, manage billing issues, communicate about outages, and to collaborate with them to foster energy conservation and reduce peak demand. Data analytics also plays a central role in optimizing the smart grid operation, providing insights into the performance of the distribution system and its various assets in order to help avoid power failures.
This Pike Research report examines global and regional smart grid data analytics software and service trends, analyzes key market drivers and barriers, and forecasts market size and growth prospects by region and different service segments from 2009 through 2015. In addition, Pike Research profiles and assesses the major vendors active in the smart grid data analytics market.
Key questions addressed:
* What is the size of the total smart grid data analytics market opportunity on a year by year basis – worldwide and regionally – through 2015?
* What are the growth trends and prospects in the smart grid data analytics software and services market on a global and regional basis?
* What are the various market forces driving and inhibiting growth with respect to smart grid data analytics software and services?
* Which market segments offer the most promising opportunities?
* Who are the key vendors in the smart grid data analytics market?
* What are their capabilities and strategic plans?
* What kind of competition are smart grid data analytics vendors facing in this market
Who needs this report?
* Utilities
* IT services vendors
* Telecom providers
* Software vendors with data analytics tools
* Automotive companies
* Industry associations
* Government agencies
* Investor community
Table of Contents
1. Executive Summary
1.1 Introduction to Smart Grid Data Analytics
1.2 Market Opportunities
1.3 Market Forces
1.4 Competitive Landscape
2. Market Issues
2.1 Competitive Landscape
2.1.1 Meter Types
2.1.2 Definition of Smart Meter
2.1.3 Definition of Smart Meter Data Analytics
2.2 Market Drivers
2.2.1 Risk Mitigation
2.2.2 Request for Data Analysis from External Stakeholders
2.2.3 Customer Expectations
2.2.4 Middle Market Prospects
2.2.5 Cloud Computing
2.2.6 Smart Grid Data Analytics Benefits
2.2.6.1 Customer Management Data Analytics
2.2.6.1.1 Billing Data
2.2.6.1.2 Revenue Data
2.2.6.1.3 Usage Data
2.2.6.1.4 Demand Response
2.2.6.2 Grid Operation Data Analytics
2.2.6.2.1 Outage Management and Distribution Optimization
2.2.6.2.2 Asset Management
2.2.6.2.3 Energy Management Systems
2.2.7 Smart Grid Data Challenges
2.2.7.1 The Data Tsunami
2.2.7.2 Complexity of Data Analytics – Data Rich and Information Poor
2.2.7.2.1 Lack of Data Integration
2.2.7.2.2 Meter Data Management
2.2.7.2.3 Situational Awareness
2.2.7.2.4 Data Quality and Integrity
2.2.7.2.5 A Plethora of Different Types of Data
2.2.7.2.6 Structured and Unstructured Data
2.2.7.2.7 New and Old Data
2.2.7.2.8 Event Data
2.2.7.3 Turning Data into Usable and Actionable Information
2.2.7.3.1 Predictive Data Analytics
2.3 Market Inhibitors
2.3.1 Lack of Knowledge
2.3.2 Shortage of Skills and Talent Plus an Aging and Retiring Workforce
2.3.3 Concern about Data Privacy and Cyber Security
2.3.4 Stringent Data Analytics Requirements
2.3.5 Lack of Standards
2.3.6 Transformational Change
2.4 Market Adoption of the Smart Grid
2.4.1 The Americas
2.4.1.1 United States
2.4.1.2 Canada
2.4.1.3 Latin America
2.4.2 Europe
2.4.3 Asia Pacific
2.4.3.1 Australia
2.4.3.2 China
2.4.3.3 South Korea
3. Competitive Landscape
3.1 Market Fragmentation
3.2 A Winning Value Proposition
3.3 Software and Services Vendor Profiles
3.3.1 Accenture
3.3.2 Aclara Software
3.3.3 AT&T
3.3.4 Capgemini
3.3.5 Ecologic Analytics
3.3.6 eMeter
3.3.7 IBM
3.3.8 Infosys
3.3.9 Itron
3.3.10 KEMA
3.3.11 Martin Dawes Analytics
3.3.12 Microsoft
3.3.13 NorthStar Utilities
3.3.14 OPOWER
3.3.15 Oracle
3.3.16 OSIsoft
3.3.17 SAIC
3.3.18 SAP
3.3.19 Siemens
3.3.20 Telvent
3.3.21 Teradata
4. Market Forecasts
4.1 Forecast Introduction
4.2 The Utility Environment
4.3 Assumptions Determining this Forecast
4.4 Worldwide Smart Meter Installed Base by Region
4.5 Worldwide Smart Meter Data Analytics by Region
4.6 Smart Grid Data Analytics Software versus Services Spending
4.6.1 Smart Grid Data Analytics Software Spending
4.6.2 Smart Grid Data Analytics Services Spending
4.6.3 Smart Grid Data Analytics Services Spending by Service Segment
5. Company Directory
6. Acronym and Abbreviation List
7. Table of Contents
8. Table of Charts and Figures
9. Scope of Study
9.1 Data Collection
9.2 Defining the Electric Utility Market
9.3 Defining the Smart Grid Data Analytics Market
9.4 Defining Service Offerings
9.4.1 Consulting
9.4.2 Implementation
9.4.3 Outsourcing
9.4.4 Software Support and Training
10. Sources and Methodology, Notes
List of Charts and Figures
* Smart Grid Data Analytics External Spending by Region, World Markets: 2009-2015
* Smart Meter Penetration Rate of All Electrical Meters by Region, World Markets: 2008-2015
* Smart Meter Installed Base by Region, World Markets: 2008-2015
* Advanced Smart Meter Installed Base by Region, World Markets: 2008-2015
* Smart Grid Data Analytics External Spending by Region, World Markets: 2009-2015
* Smart Grid Data Analytics External Spending Share by Region: 2010 and 2015
* Percentage of Total Smart Grid Data Analytics Spending for Services and Software: 2009-2015
* Smart Grid Data Analytics Services and Software Spending Growth, World Markets: 2010-2015
* Percentage of Smart Grid Data Analytics External Spending on Services by Service Segment: 2009-2015
List of Tables
* Smart Grid Data Analytics External Spending by Region, World Markets: 2009-2015
* Smart Grid Data Analytics External Spending Share by Region, World Markets: 2009-2015
* Smart Grid Data Analytics External Spending on Software by Region, World Markets: 2009-2015
* Smart Grid Data Analytics External Spending on Services by Region, World Markets: 2009-2015
* Smart Grid Data Analytics External Spending on Services by Service Segment: 2009-2015
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