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What is Big Data? Role of Big Data in Disaster Management

Big Data:
(1) Collection of scientific & engineering methods & tools that allows researchers to conduct an efficient analysis of vast quantities of data that is available.
(2) Addresses issues related to storage, accessibility, distribution, analysis & effective visual presentation of data & analysis.
(3) Entails understanding & monitoring the entire body of public & openly available communication.
(4) Challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source.
(5) Big data has opened new options for natural disaster management, primarily because of the varied possibilities it provides in visualizing, analyzing and predicting natural disasters.
(6) It has radically changed the ways through which human societies adopt natural disaster management strategies to reduce human suffering and economic losses.
(7) In a world that is now heavily dependent on information technology, the prime objective of computer experts and policy makers is to make the best of big data by sourcing information from varied formats and storing it in ways that it can be effectively used during different stages of natural disaster management.

Disaster Management:
It can be defined as the organization and management of resources and responsibilities for dealing with all humanitarian aspects of emergencies, in particular preparedness, response and recovery in order to lessen the impact of disasters.

Benefits & Importance of Big Data in Disaster Management:
(1) It entails understanding & monitoring the entire body of public and openly available communication such as messages and content exchanged on social media.
(2) It allows researchers to conduct a detailed analysis of all communications which provides valuable information that has general validity for the population at large; such as information about a disease outbreak.
(3) It helps policy makers and first responders to come with quick and concrete decision on the number of people affected, type and nature of the damage and where to allocate the resource.
(4) Many natural hazard forecasting systems rely on big data.
(5) Early warning system for tsunami, storm, forest fire, and flood can be more accurate and reliable.
(6) Crowd sourcing, cyber infrastructure, and cloud computing approach can be used to get required information for emergency management.