The smart grid data analytics market was valued at USD 1451.6 million in 2019, and it is expected to reach USD 2943.9 million by 2025, registering a CAGR of 12.76%, during the period of 2020-2025. With the advent of advanced technology, such as IoT, players have been focusing on integrating smart grid solutions in a wider aspect. As data generation has been continuously experiencing an upward trend, power utility companies have been combining Big Data with billions of more rows of additional IoT and smart sensor data. The data gathered from smart meters can provide a better understanding of customer behavior, and hence, facilitate customer segmentation.

• Growing investment in smart grid projects has been driving the market studied. According to the IEA (International Energy Agency), the world electricity demand is anticipated to increase by nearly 80% between 2012 and 2040. Expansion, modernization, and decentralization of the electricity infrastructure for improved resiliency are the planned investments from organizations. The power grid infrastructure has been progressively becoming more digitized and connected, thereby, ensuring the reliable and secure flow of critical digital communications. Moreover, various projects have begun to take place across the Indian subcontinent, aimed at removing issues faced by the population regarding electricity.
• Enormous influx of data has been driving the market growth. According to the Institute of Electrical and Electronics Engineers (IEEE), to enable being smart, a massive amount of data has been exchanged between grid components and the enterprise systems that manage these components. Based on the application, information exchanged helps economically optimized bidirectional power flow between a utility and its customers.
• Also, according to a survey published by Bridge Energy, in 2019, 93% of utility vendors have been expecting the availability of solutions to analyze and process data within their company. Furthermore, smart grids collect much more data than the manual energy meter reading system. This permits the use of data analysis techniques and the preparation of highly realistic consumption forecast, as many more variables are taken into account. Therefore, the opportunities for smart grid analytics have been expanding because there is an exponential increase in the amount of data available, in order to develop analytical models.
• High costs of smart grid systems and lack of skilled professionals have been restraining the growth of the market. The most prominent limitation in smart metering is the availability of capital funding. Smart systems are comparatively expensive than the regular metering equipment that is employed by most of the service providers and users. Furthermore, different smart meters have been designed with various parameters, based on the operational requirements and consumer requirements, which inhibits as a complicated equipment that needs skilled labor for handling and installation.