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Zaid Alshaboul_ZA_wk8_Final Exam.docx - FINAL EXAM # DATA...

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FINAL EXAM # DATA ANALYTICSZaid AlshaboulData AnalyticsInstructor: David KimbleDec 17, 2021
AbstractIn terms of interpretation and analytics, Big Data is inherently difficult. A multitude ofsoftware’s are emerging to solve this data problem, and they come packaged with a myriad ofdata correlation and analysis tools. This paper examines Big Data, its difficulties, and BigData Use Cases in order to emphasise the importance of Big Data Analytics. It also includes afew samples of some of the most popular new Python tools for Big Data Analytics.
IntroductionBig Data is a broad phrase that refers to any collection of data sets that are so vast orcomplicated that they are impossible to analyse using standard data management approacheslike relational databases. RDBMS has long been thought of as a one-size-fits-all solution, yetthe demands of Big Data are diverse. Velocity, Volume, and Variety are three properties of bigdata. To turn the numerous bits and bytes into meaningful information, the data must beorganised. We can't benefit from a large amount of data unless we can make sense of it.Traditionally, statisticians conducted statistics while programmers created code. Theprogrammers used a programming language, while statisticians used specialist applicationslike IBM's SPSS to draw interferences. (Vivekananth P, Leo John Baptist A, 2015).Programmers maintained vast volumes of data in databases or log files, whereas statisticiansrelied on national statistics or market research. However, now that everyone is linked to theinternet, programmers, statisticians, scientists, analysts, and everyone else has access to a vastamount of raw data. The availability of Big Data from the cloud to almost any individualaltered the game entirely.Python For Big Data AnalyticsPython is the most preferred language for Data Analytics among Data Scientists. Python ispopular because of its ease of use and a variety of additional built-in capabilities. It hassupport for modern data structures like as maps and sets, as well as primitive types such asintegers and complex numbers. It comes with a command line shell that allows users to opendatasets, perform transformations, and execute algorithms all from one convenient command

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