Big data is a term that describes the large volume of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
Big Data applications
Here are some examples of Big Data applications:
Smart Grid case: it is crucial to manage in real time the national electronic power consumption and to monitor Smart grids operations. This is achieved through multiple connections among smart meters, sensors, control centers and other infrastructures. Big Data analytics helps to identify at-risk transformers and to detect abnormal behaviors of the connected devices. Grid Utilities can thus choose the best treatment or action. The real-time analysis of the generated Big Data allow to model incident scenarios. This enables to establish strategic preventive plans in order to decrease the corrective costs. In addition, Energy-forecasting analytics help to better manage power demand load, to plan resources, and hence to maximize prots .
E-health: connected health platforms are already used to personalize health services (e.g., CISCO solution) Big Data is generated from different heterogeneous sources (e.g., laboratory and clinical data, patients symptoms uploaded from distant sensors, hospitals operations, pharmaceutical data). The advanced analysis of medical data sets has many beneficial applications. It enables to personalize health services (e.g., doctors can monitor online patients symptoms in order to adjust prescription); to adapt public health plans according to population symptoms, disease evolution and other parameters.It is also useful to optimize hospital operations and to decrease health cost expenditure.
Internet of Things (IoT): IoT represents one of the main markets of big data applications. Because of the high variety of objects, the applications of IoT are continuously evolving. Nowadays, there are various Big Data applications supporting for logistic enterprises. In fact, it is possible to track vehicles positions with sensors, wireless adapters, and GPS. Thus, such data driven applications enable companies not only to supervise and manage employees but also to optimize delivery routes. This is by exploiting and combining various information including past driving experience.Smart city is also a hot research area based on the application of IoT data.
Public utilities: Utilities such as water supply organizations are placing sensors in the pipelines to monitor flow of water in the complex water supply networks. It is reported in the Press that Bangalore Water Supply and Sewage Board is implementing a real-time monitoring system to detect leakages, illegal connections and remotely control valves to ensure equitable supply of water to different areas of the city. It helps tp reduce the need for valve operators and to timely identifying and fixing water pipes that are leaking.
Transportation and logistics: Many public road transport companies are using RFID (Radiofrequency Identification) and GPS to track busesand explore interesting data to improve there services… For instance, data collected about the number of passengers using the buses in different routes are used to optimize bus routes and the frequency of trips. various real-time system has been implemented not only to provide passengers with recommendations but also to offer valuable information on when to expect the next bus which will take him to the desired destination. Mining Big Data helps also to improve travelling business by predicting demand about public or private networks. For instance, in India that has one of the largest railway networks in the world, the total number of reserved seats issued every day is around 250,000 and reservation can be made 60 days in advance. Making predictions from such data is a complicated issue because it depends on several factors such as weekends, festivals, night train, starting or intermediate station. By using the machine learning algorithms, it is possible to mine and apply advanced analytics on past and new big data collection. In fact advanced analytics can ensure high accuracy of results regarding many issues.
Political services and government monitoring: Many government such as India and United States are mining data to monitor political trends and analyze population sentiments. There are many applications that combine many data sources: social network communications, personal interviews, and voter compositions. Such systems enable also to detect local issues in addition to national issues. Furthermore, governments may use Big Data systems to optimize the use of valuable resources and utilities. For instance, sensors can be placed in the pipelines of water supply chains to monitor water flow in large networks. So it is possible for many countries to rely on real-time monitoring system to detect leakages, illegal connections and remotely control valves to ensure equitable supply of water to different areas of the city.