COIT20253 Business Intelligence using Big Data Assignment
Added on 2021-04-23
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Gizzle BautistaCC53 MIS - S0261553COIT20253 Business Intelligence using Big DataAssignment 1Due Date: 22 April 2016
Table of ContentsIntroduction1Big Data1Big Data and the Publishing Industry1Kobo Inc.1Online versus Offline Big Data2Selection Strategy for Big Data Application3Big Data Solutions Outcome4Technologies in Big Data Solutions4Business Impact of Big Data Solutions5Organisational Impact of Big Data Solutions6Conclusion7References8
Bautista, GizzleIntroductionWith the uprising of Big Data solutions in different fields, the need tounderstand what it does and how it affects the way organisations do their businessesis vital for every IT professional. This report aims to provide its definition andexamples of the publishing industry’s use of Big Data. This report will also investigatethe impact of Big Data solutions in the publishing industry. A positive and negativeperspective on the solution will be discussed. Furthermore, Kobo Inc.’s use of Big Datawill be presented as a case study sample. Relating all the literatures provided, thispaper aims to provide a conclusive assessment on how Big Data solution is changingthe publishing world through business intelligence analysis.Big DataIn a white paper published by Kobo (2014), the company described Big Data aslarge data sets that when correct analysis is applied can be a tool for businessforecasting. While Press (2014), contributor for Forbes magazine, provided several ofhis own definitions wherein he cited Big Data as the organisational attitude ofcombining data from different sources which could lead to better decision makingstrategies. Lastly, for MongoDB (2015), Big Data enables organisations to create newmerchandises in order to be highly competitive and at the same time save money.Big Data and the Publishing IndustryA decade ago, the only concern of book publishers is for its content to bebought while their sale status in physical stores are determined through bookscan(Davenport 2014). Nowadays, publishers, as content producers/packagers/distributors,need personalised content delivery and content recommendations (Bright 2015).Wherein, analysing a single reader’s journey and their use of multiple devicesthroughout is another spectrum to consider as per the author. Kobo Inc.Kobo Inc.’s journey in Big Data started in 2012 is originally started to solely helpcustomers but later on made as a profit centre (Christensen 2013). The companywebsite describe itself as “the world’s fastest-growing eReading services” andDigitalPublishing101 (2015) differentiated Kobo from Amazon.com Inc. as havingdirect access to publishers and that it exclusively sells ebooks.In the Big Data Innovation Summit 2013, Kobo’s VP of Big Data presented howreaders create massive amount of data. Christensen (2013) explained how readers’behaviour in store, such as visiting, searching, browsing and buying are example ofdata creation. Additionally, the readers’ actions in their ebook readers produce data(Christensen 2013).
Bautista, GizzleOnline versus Offline Big DataAccording to the MongoDB’s (2015) published white paper, the decision inselecting which Big Data technology to use depends on how the organisation intendsto use their data. If the organisation needs more real-time operational use cases thenthe company needs an online big data technology while a long-running offline analysisrequire offline big data solutions (MongoDB 2015).Figure 1 below shows MongoDB’s (2015) comparison of Online and Offline BigData:Figure 1: Online vs Offline Big DataSource: MongoDB 2015However, MongoDB (2015) argued that determining which Big Data technologyto use is not mutually exclusive as organisations would most likely need both.
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