Global Smart Grid Data Analytics Market Report, Ongoing Trends, Growth Factors, Negative Factors, Opportunities, Untapped Markets, Strategies and Developments, Segments, and Forecast 2019 – 2028

Overview:  Smart Grid Data Analytics

"The Smart Grid Data Analytics Market size is expected to be worth around US$ xx Billion by 2021 from US$ X.xx million in 2031, growing at a CAGR of X.x% during the forecast period 2021 to 2031."

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Smart grid data analytics can be referred to as data analysis of a large volume of data obtained from smart grid networks. It can also be defined as a sub-segment of big data analytics.  The smart grids consist of various components, including automated power distribution systems, smart meters, smart appliances, and sensing equipment, among others in the grid network. A smart grid data analytics solution is considered an efficient option to predict the power supply required to be transmitted in the future based on analysis. It can help make decisions for short-term and long-term forecasts and aid in minimizing wastage of energy.

Key factors expected to drive the growth of the global smart grid data analytics market are rising levels of investment in smart grid networks, coupled with ever-escalating demand for electricity across the globe. In addition, increasing adoption of smart grids and rising advancements in Internet-of-Things and big data analytics are other factors expected to drive the growth of the global smart grid data analytics market.

Furthermore, growing awareness among consumers about the advantages of smart grid analytics and low cost for maintenance coupled with rising usage of smart meters worldwide are other factors expected to drive the growth of the target market over the forecasted period. However, the high costs of smart grid systems are one of the major factors expected to hamper the growth of the global smart grid data analytics market over the forecast period.

Trends:

Prominent players are collaborating with other market players to develop AMI analytics solutions owing to high adoption of smart meters. In addition, large number of new entrants venturing into the target market is another key trend observed in the global market. These trends are expected to gain popularity and encourage development of new technologies, thereby supporting market growth.

Segment Analysis:

By Solution Type:

Among the solution type segments, the AMI analytics segment is expected to dominate in the global smart grid data analytics market, owing to increasing use of flattening smart meter shipments.

By Service Type:

Among the service type segments, the professional services segment is expected to dominate in the target market.

By Deployment Model:

Among the deployment model segments, the on-premise segment is expected to dominate in the target market.

By End User:

Among the end user segments, the large enterprises segment is expected to dominate in the target market.

Regional Analysis:

The market in North America is expected to dominate in the global smart grid data analytics market. This is primarily attributed to increasing investment in the smart grid networks, coupled with increasing awareness about smart technologies in countries in the region. The market in Asia Pacific is expected to be an emerging market in the global smart grid data analytics market and is expected to register highest CAGR over the forecast period, owing rapidly growing penetration of information and communication technologies (ICT) in grid modernization in countries such as China and India in the region. The market in Europe is expected to account for significant revenue share in the global smart grid data analytics market, due to increasing number of software vendors. Moreover, the markets in Latin America, the Middle East & Africa are expected to register moderate growth rates in revenue in the global smart grid data analytics market over the forecast period.

Global Smart Grid Data Analytics Market Segmentation:

Segmentation by Solution Type:

• AMI Analytics
• Demand Response Analytics
• Grid Optimization
• Asset Management
• Others (Energy Forecasting and Data Visualization Tools)

 Segmentation by Service Type:

• Professional Services
• Support & Maintenance Services

 Segmentation by Deployment Model:

• On-premise
• Cloud-based
• Hybrid

Segmentation by End User:

• Small/Medium Enterprises
• Large Enterprises
• Public Sector

 Segmentation by region:

• North America
• Europe
• Asia Pacific
• Latin America
• Middle East & Africa