Big Data and Internet of Things Correlation

Introduction

It is true to say that the 21st century experiences an unprecedented and unsurpassed explosion of data. The consumers worldwide send and receive 1.3 exabytes of data monthly via smartphones alone; the number of e-mail messages sent and received daily is close to 300 billion; 22 million hours of Netflix video materials are viewed daily (Stone 4). All of this could not happen overnight. After the massive smartphone and global bandwidth prices downfall have created a perfect atmosphere for media companies to invest in data collection and production, the Big Data revolution broke out (Stone 3). The following paper is devoted to the major Big Data issues including the actors of and the reasons for its collection, the correlation of Big Data and the Internet of Things, as well as the possible future implications of the issue.

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Big Data Collection and Development

In a scientific sense, Big Data is a massive volume of information that is easily obtainable but the very amount of which complexifies its processing; the data originates from a multitude of sources and comes in petabytes and exabytes. In simpler terms, Big Data is some datasets that, taken as a whole, are characterized by great volume and complicity. Such volume is impossible to process using conventional means of data processing and analysis. Also, a significant obstacle to processing such data is the fact that it comes unstructured, such as the data gathered by Google, Yahoo, or Amazon.

As a consequence, Big Data should be rapidly and flawlessly analyzed, moved, and stored, and bug-free analysis is the idea that data giants (the ones mentioned above as well as some others) are trying to achieve (Payton and Claypoole 37). There is more to Big Data than that. The notion is often used and abused in the sphere of marketing, with software and IT establishments racing to communicate the idea of their products surpassing the others. Still more ambiguous is the information that is understood and counted as “Big Data.” For that matter, personal information about consumers that is gathered and processed by social networks and companies is leveraged as such data.

As to the media, the four V’s of Big Data are volume in which it is gathered, the velocity with which it is processed, variety of forms in which it comes, and veracity that it presents (Stone 1). Information concerning every one of us is gathered daily through simple actions that we perform. Such data includes, for instance, the exact time and place a person pays with their credit card, send a text message, books a tour, etc. Users of social media share their personal information daily and voluntarily, sometimes not realizing that by sharing it, they give it to the company that owns the website. Some data can only be gathered with the user’s permission and at their consent while others do not need the user’s awareness (Ferris et al., 28).

Big Data Collectors and Reasons for Collection

As to the forums responsible for data collection, these are numerous. Browsers, for one, keep track of the search entries and web history. These include Google, Yahoo, Bing, and other engines. As it was said, social network users provide personal information voluntarily, share posts and links, tweet, and use hashtags; thus, another means of data collection is social networking (Ferris et al., 29). Thirdly, several corporations are specializing in consumer data (Singer par. 2).

These companies, including KBM, Acxiom, and Equifax, work in collaboration with other establishments to collect consumer-related data and create their databases to trade. Such data may include the items that each consumer buys, the types of department stores from which these items were purchased, and the geographic position of these stores. Finally, there are mobile applications that collect personal data. It is not a secret that Facebook, for example, can read private text messages. However, there are also some apps that the user has to insert their daily activities, food, and body parameters.

In sum, there is a wide array of data types and means of collection. The Big Data taken as a whole encompasses life events, relationships, intellectual properties, conversations, purchases, locations, and so forth. The purposes of that may vary from company to company. In the context of media, the purposes of data collection include primarily the assessment of the audience’s current demands and forecasting their future interests. Another purpose of data collection is to estimate the time the content is viewed and the device on which it is viewed to optimize the schedule of content broadcasting. Finally, through data collection, advertisements can be targeted at particular customers, and the search can be personalized as well (Stone 5-6).

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The Internet of Things” and Big Data

The Internet of Things (IoT) can be defined as a set of gadgets that can be connected to the Internet and automatically gather and exchange information (ITU, n.pag.). The “things” in question are various devices, from sensors to vehicles to smart refrigerators and Wi-Fi enabled irrigation controllers. The IoT-featured devices and objects can be operated through networks. Thus, the main implication of the IoT is that the cyber-world is gradually but persistently integrated into the world that human beings inhabit. The human world, thus, gets a performance boost and an improvement in terms of accuracy and efficiency. Each of the IoT-enabled objects is identified as a separate and operable system that can, nevertheless, connect to similar systems through networks. As the number of IoT objects increases, it conveys the suggestion of “Internet of Everything” (O’Leary 53).

The IoT can serve as an ultimately effective source of Big Data. Firstly, the sensors embedded into the IoT-enabled devices interact with the physical world and cyber-space in both directions. As a result, enormous volumes of data are gathered. Because the collection of data via these sensors is a continuous process, the processing capacities of the sensors equal and surpass those of conventional transactional processors. Another point of consideration here is the variety of data gathered by the IoT devices. Practically every dimension of human life is covered by the Internet of Things: locations, purchases, events, video and audio materials of interest, and so forth. Lastly, the value of data is largely determined by its veracity, that is to say, whether the data is authentic and credible. The Internet of Things is working in this direction, and the results are visible: the reliability of data gathered to-date as opposed to that of ten years ago deserves every appraisal. Thus, it can be assumed that the IoT will facilitate the collection of Big Data and increase the amount and variety of it (O’Leary 55).

Big Data and IoT Implications

Together with the Internet of Things, Big Data is designed to make people’s lives better. As can be seen from the literature referred to above, the IoT keeps a steady pace in data collection and veracity improvement. It is true to say that there are some privacy concerns since the availability of such volumes of personal data stored and traded is likely to create a hotbed for malignant hackers. On the other hand, with all due security, Big Data and the IoT are likely to create a smarter world, save people effort, and facilitate the enhancement of public health and economy. Today, more than half of IoT is concentrated in transport, manufacture, and consumer-oriented apps (McLellan n.pag.). It can be predicted that more and more industries will soon start incorporating IoT and Big Data. Big Data provides a stable ground for developing strategies since reliance on such data is the main constituent of evidence-based management. It will be only logical if newly-emerged corporations and media are aimed at data-verified strategies to innovate their products basing the decisions on what the consumers want.

In terms of job creation, the use of Big Data will require business analysts and data scientists. The former will be capable of framing questions to retrieve the answers from the data and use them as evidence for decision-making. The latter will be leading the analytical tool development and monitor data reliability (McLellan n.pag.). Presumably, the persons capable of doing both will be extremely valued.

Conclusion

To conclude, the use of Big Data and the Internet of Things has set the world awash with productivity. At the moment, new productivity waves are rising to further increase the tool potential. Big Data usage is significant for the media in terms of customer strategy development, and will most probably prove beneficial later, with increased data veracity.

Works Cited

Ferris, Andy, David Moore, Nathan Pohle, and Priyanka Srivastava. “Big Data.” The Actuary Magazine 10.6 (2014): 28-32. Print.

ITU. Internet of Things Global Standards Initiative. ITU, 2016. Web.

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McLellan, Charles. “The internet of things and big data: Unlocking the power.” ZDNet. CBS Interactive, 2015. Web.

O’Leary, Daniel E. “‘Big Data’, The ‘Internet of Things’ and The ‘Internet of Signs’.” Intelligent Systems in Accounting, Finance and Management 20.1 (2013): 53-65. Print.

Payton, Theresa, and Ted Claypoole. Privacy in the Age of Big Data: Recognizing Threats, Defending Your Rights, and Protecting Your Family. Lanham, MD: Rowman & Littlefield, 2014. Print.

Singer, Natasha. “Mapping, and Sharing, the Consumer Genome.” The New York Times. The New York Times Company, 2012. Web.

Stone, Martha L. “Big Data for Media.” Reuters Institute for the Study of Journalism, 2014. Web.

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