The Rise of Big Data, Cloud, and Internet of Things: Three Trends to Watch

The Rise of Big Data, Cloud, and Internet of Things: Three Trends to Watch

Reema Abdulraziq, Muneer Bani Yassein, Shadi Aljawarneh
DOI: 10.4018/978-1-5225-3029-9.ch010
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Big data refers to the huge amount of data that is being used in commercial, industrial and economic environments. There are three types of big data; structured, unstructured and semi-structured data. When it comes to discussions on big data, three major aspects that can be considered as its main dimensions are the volume, velocity, and variety of the data. This data is collected, analysed and checked for use by the end users. Cloud computing and the Internet of Things (IoT) are used to enable this huge amount of collected data to be stored and connected to the Internet. The time and the cost are reduced by means of these technologies, and in addition, they are able to accommodate this large amount of data regardless of its size. This chapter focuses on how big data, with the emergence of cloud computing and the Internet of Things (IOT), can be used via several applications and technologies.
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Big data is defined as a large amount of data with three dimensions of volume, velocity, and variety. It is brought about by the collecting and analysing of different applications and acquisitions. This has motivated the use of complicated tools to store and deal with these data (Science Definition Team Report, 2016).

The focus of big data is not on how much data are collected or produced, but on how the important data can be extracted, and the benefits that can be derived from these data. For instance, when the Hemagglutinin Type 1 and Neuraminidase Type 1 (H1N1) diseases appeared, researchers collected all the Google search queries from users to limit, from their questions, where this disease was populated. All the data were obtained from a search of about 20-100 queries. When the entire data was filtered, they found about 45 queries that were able to help them achieve their goal. This is the purpose of the use of big data, and this is what motivates the search for techniques that can deal with this large amount of data to minimize it and achieve the goals of researchers (Anwaar Ali et al., 2016).

There are a lot of techniques that deal with big data (such as cleaning and classification) and on data extraction, data fusion and data mining for data collection, data modelling, and visualization. These techniques focus on how the data is presented for use in several applications and technologies (Corporate Partnership Board Report., 2015). It is necessary to manage these big data techniques and to store the data in a faster and cheaper way for its users. Cloud computing enables users to connect to the Internet for several applications and to solve most of the big data problems caused by the huge amount of used data that has to be dealt with. Cloud computing is associated with the Internet of Things (IoT), which allows different types of data from different domains to be connected via the Internet. It can be inferred that the IoT is the whole concept of this connection, while cloud computing, which uses the open-source software, the Hadoop, is the model that is used to store and analyse the data via the Internet (Ibrahim Abaker Targio Hashem et al., Moeen Hassanalieragh et al., 2015; Jeong-Tae Kim and Sung-Han-sim et al., 2016; Al-Ali et al., 2015; Anvari-Moghaddam et al., 2015; Huang et al., 2015; Gonnot & Saniie, 2014; Zafari & Christidis, 2015; Aegis, 2015).

Big data and IoT using cloud computing play a significant role in various important applications that are classified as smart city for healthcare, smart transport and smart grids, telecom in terms of both the user and the company, and how they can communicate using big data. The food industry can use big data in a significant way in terms of the storage of its products and how the customer can be serviced in a better way. One of the important big data applications has to do with education due to the huge amount of data that can be created in several domains. There is no limit to the above applications. However, they exceed some technologies such as RFID, that uses a small wireless card for reading several information types; Wi-Fi, that focuses on how a huge amount of data can be scalable and accommodate several user needs; Zigbee, which is a wireless technology that has some features in terms of the big data era; and Ultra-wideband, that plays a significant role in the collection of information in hidden objects (Ibrahim Abaker Targio Hashem et al.; Heba Aly et al., 2015; Robinston et al., 2016; Madakam et al., 2015; Wi-Fi Alliance, 2014), as will be discussed in the next section.

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