Big Data applications

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.