“Management of Large Data: a Research Upon Analytics and Better Decision Making” |
Evolving technologies in the energy and utilitiesindustry, including smart meters and smart grids, can provide companies withunprecedented capabilities for forecasting demand, shaping customer usagepatterns, preventing outages, optimizing unit commitment and more. At the sametime, these advances also generate unprecedented data volume, speed andcomplexity. To manage and use this information to gain insight,utility companies must be capable of high-volume data management and advancedanalytics designed to transform data into actionable insights. For example,designing effective demand response programs requires that utilities executeadvanced analytics across a combination of data about customers, consumption,physical grid dynamic behavior, generation capacity, energy commodity marketsand weather. Data generated by financial transactions, different typesof sensors and meters, social media networks and numerous other sources areincreasing exponentially in terms of their volume, variety and velocity. These“3 Vs” are making datasets increasingly difficult to capture, manage and processthrough conventional means. This phenomenon is known as “big data”. Deriving value out of the huge volumes of data created byusers on a day-to-day basis has become popularised by companies like Google andFacebook that are increasingly applying analytics and decision making solutionsto capture, manage and process data. In doing so, companies benefit fromreal-time market intelligence that empowers company decision-making which, inturn, may result in increased revenues and reduced costs. Businesses benefitting from the double-digit growth inthe big data market are currently taking advantage of low barriers to entry forstart-ups, whether in terms of infrastructure and capital requirements or thereduced need for big data firms to be located in close proximity to theirclients.