Smart Grid Data Analytics Market Overview 2023-2028:
IMARC Group’s latest report, titled “Smart Grid Data Analytics Market: Global Industry Trends, Share, Size, Growth, Opportunity and Forecast 2023-2028”, offers a comprehensive analysis of the industry, which comprises insights on the smart grid data analytics market demand. The report also includes competitor and regional analysis, and contemporary advancements in the market. the global smart grid data analytics market size reached US$ 2.2 Billion in 2022. Looking forward, IMARC Group expects the market to reach a value of US$ 4.3 Billion by 2028, exhibiting a growth rate (CAGR) of 10.87% during 2023-2028.
Smart Grid Data Analytics Uses :
Smart grid data analytics represents a systematic computational solution used to analyze large amounts of data produced from smart grid systems. It collects valuable information generated by the equipment and aids in predicting the load for the future. Smart grid data analytics consists of forecasting, predictive, prescriptive analytics, and optimization. It is widely utilized in demand response, grid optimization, advanced metering infrastructure analysis, etc. Smart grid data analytics helps in improving grid reliability, efficient energy transmission, and security, lowering management costs, delivering personalized energy services to consumers, etc. It is also used to gain predictive analysis, establish better decision support systems, optimize grid efficiency, etc.
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Competitive Landscape with Key Players:
- Accenture plc
- AutoGrid Systems Inc
- General Electric Company
- International Business Machines Corporation
- Itron Inc
- Landis+Gyr (Toshiba Corporation)
- SAP SE
- SAS Institute Inc
- Schneider Electric SE
- Sensus USA Inc. (Xylem Inc.)
- Siemens AG
- Tantalus System Corporation
Smart Grid Data Analytics Market Demand and Development:
The escalating demand for this solution among utility service providers, as it assists them in analyzing load behavior, decreasing power cuts, making better decisions, etc., is among the key factors stimulating the smart grid data analytics market. Moreover, the widespread adoption of smart meters by consumers to manage their energy consumption is acting as another significant growth-inducing factor. Besides this, numerous technological advancements, including the rising integration of the Internet of Things (IoT) that aid in reliable and efficient energy transmission and enhancing security, are positively influencing the global market.
Furthermore, the introduction of advanced metering infrastructure (AMI) that reduces utility costs and offers convenience to individuals by remotely reading meters and generating more accurate bills faster is also propelling the market growth. Apart from this, extensive R&D activities and the launch of favorable policies by government bodies to promote the use of renewable sources for power generation are anticipated to fuel the smart grid data analytics market over the forecasted period.
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Key Market Segmentation:
Breakup by Solution:
- Transmission and Distribution (T&D) Network
- Metering
- Customer Analytics
Breakup by Deployment:
- Cloud-based
- On-premises
Breakup by Application:
- Advanced Metering Infrastructure Analytics
- Demand Response Analysis
- Grid Optimization Analysis
- Others
Breakup by End Use Vertical:
- Private Sector (SMEs and Large Enterprises)
- Public Sector
Breakup by Region:
- North America (United States, Canada)
- Asia Pacific (China, Japan, India, Australia, Indonesia, Korea, Others)
- Europe (Germany, France, United Kingdom, Italy, Spain, Others)
- Latin America (Brazil, Mexico, Others)
- Middle East and Africa (United Arab Emirates, Saudi Arabia, Qatar, Iraq, Other)
Key Highlights of the Report:
- Market Performance (2017-2022)
- Market Outlook (2023-2028)
- Porter’s Five Forces Analysis
- Market Drivers and Success Factors
- SWOT Analysis
- Value Chain
- Comprehensive Mapping of the Competitive Landscape
Note: If you need specific information that is not currently within the scope of the report, we can provide it to you as a part of the customization.
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