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Read this article. What are the main challenges of using big data?

Introduction

The current international population exceeds 7.2 billion, and over 2 billion of these people are connected to the Internet. Furthermore, 5 billion individuals are using various mobile devices, according to McKinsey (2013). As a result of this technological revolution, these millions of people are generating tremendous amounts of data through the increased use of such devices. In particular, remote sensors continuously produce much heterogeneous data that are either structured or unstructured. This data is known as Big Data. Big Data is characterized by three aspects: (a) the data are numerous, (b) the data cannot be categorized into regular relational databases, and (c) data are generated, captured, and processed very quickly. Big Data is promising for business application and is rapidly increasing as a segment of the IT industry. It has generated significant interest in various fields, including the manufacture of healthcare machines, banking transactions, social media, and satellite imaging. Traditionally, data is stored in a highly structured format to maximize its informational contents. However, current data volumes are driven by both unstructured and semistructured data. Therefore, end-to-end processing can be impeded by the translation between structured data in relational systems of database management and unstructured data for analytics.

e staggering growth rate of the amount of collected data generates numerous critical issues and challenges described by, such as rapid data growth, transfer speed, diverse data, and security issues. Nonetheless, the advancements in data storage and mining technologies enable the preservation of these increased amounts of data. In this preservation process, the nature of the data generated by organizations is modified. However, Big Data is still in its infancy stage and has not been reviewed in general. Hence, this study comprehensively surveys and classifies the various attributes of Big Data, including its volume, management, analysis, security, nature, definitions, and rapid growth rate. The study also proposes a data life cycle that uses the technologies and terminologies of Big Data. Future research directions in this field are determined by opportunities and several open issues in Big Data domination.

This study presents: (a) a comprehensive survey of Big Data characteristics; (b) a discussion of the tools of analysis and management related to Big Data; (c) the development of a new data life cycle with Big Data aspects; and (d) an enumeration of the issues and challenges 5 associated with Big Data.

The rest of the paper is organized as follows. Section 2 explains fundamental concepts and describes the rapid growth of data volume; Section 3 discusses the management of Big Data and the related tools; Section 4 proposes a new data life cycle that utilizes the technologies and terminologies of Big Data; Section 5 describes the opportunities, open issues, and challenges in this domain; and Section 6 concludes the paper. Lists of acronyms used in this paper are presented in the Acronyms section.