Disadvantages Of Big Data

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Table of content • Introduction. 1 • Define big data. 1 • Background on big data. 1 • Big data dimensions 2 • advantages of big data 3 • challenges or risks of big data 4 • Big data Technologies 5 • The relationship between big data and cloud computing. 5 • The relationship between big data and the semantic web. 5 • Identify a relevant field or discipline, and briefly discuss how big data is applied in this field or discipline 5 • Conclusion 6 • In-text references, as well as list of references compiled using the Harvard style. Completed assignment checklist as appendix 7 Introduction In this digital world we live in we are faced with the ever growing…show more content…
Big Data can be defined as volumes of data available in varying degrees of complexity, generated at different velocities and varying degrees of ambiguity that cannot be processed using traditional technologies, processing methods, algorithms, or any commercial off-the-shelf solutions (Krishnan, 2013). Big data is basically this huge volume of data that is hard to manage, process and organise. This data is generated either from machines, traditional enterprises or social platforms. The machine generated data includes weblogs, smart meters equipment logs and trading systems, whereas the traditional enterprise data includes customer information, web store transactions and general ledger, and lastly the social data includes data from social media platforms like Facebook and…show more content…
This does not mean that before this information age era big data did not exist. Its foundation was laid in the 1940’s by Fremont Rider, a Wesleyan University Librarian when he noticed how the American University Libraries were doubling in size every sixteen years. He then predicted that by the year 2040 Yale libraries will have approximately 200 000 000 volumes of information and it will occupy over 6 000 miles of the shelves. The term Big data was first used by Roger Mogoulas from the O’Reilly media in 2005 where he explained big data as a wide range of large data sets almost impossible to manage and process using traditional data management tools. Big data dimensions Doug Laney was the first to describe big data into the 3 dimensions or characteristics. These characteristics are namely volume, variety and velocity, the fourth v (veracity) was introduced at a later stage by IBM. The four characteristics of big data will be explained in detailed as follows: Volume Data volumes characterised by the amount of data that is generated continuously (Krishnan, 2013). It is the amount of data that needs to be generated analyzed and managed for decision making. J. Kalyvas & M. Overly have visualised the different volumes of big data as follows: • 1bit – a simple yes/no
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