Big data analysis

Abstract

“Big Data” can be considered as an expression which has spread suddenly. It could be depicted as a pioneering mechanism for saving, distributing, managing, visualizing and analyzing large data along with very high velocity and approaches for managing incompetent quantity of data. Here, the state-of-the-art and background of big data are reviewed. Every review-related technology and general background of big data are firstly reviewed, for example IoT, cloud computing, Hadoop and data centers. Then, we concentrate on every value chain phase belongs to big data such as data acquisition, data generation, data analysis and data storage. For the four phases, the general background is presented, the technicalities are discussed, and most recent advances are reviewed. Eventually, the various big data representative applications are examined, containing IoT, enterprise management, medial applications, online social networks, smart grid and collective intelligence. Those argumentations pursue to supply an overall overview for readers interested in this exciting area. The survey here is finalized with an argumentation of future directions and open problems.

A Large-Scale Dataset of Search Interests Related to Disease X Originating from Different Geographic Regions

“…During the outbreak of COVID-19 and similar viruses in the past, Google Trends attracted a significant amount of attention from researchers across different disciplines, such as Big Data [33,34], Data Mining [35,36], Healthcare [37,38], Epidemiology [39,40], Information Retrieval [41,42], and Data Analysis [43,44], as Google Trends helps to mine, analyze, and obtain real-time insights related to web behavior, and the features of Google Trends surpass traditional surveys [45]. However, none of the prior works in this field have focused on mining and analyzing web behavior data from Google Trends related to Disease X.…”