Our every day life has changed forever, thanks for the ubiquitous smart phones and technology dependent information age. We leave a trail of data while travelling, shopping, driveing, bloggin, and even voting. All of these activities leave a digital signature unique to us, which if analyzed can predict our next move. Similarly, a large set of data is being created each day by businesses, researchers and the World Wide Web. According to an estimate by the government, there are about 1.2 zettabytes (250 billion DVDs) of electronic data generated each year by everything from underground physics experiments and telescopes to retail transactions and Twitter posts (Mervis 22). This data growth has created a new challenge and opportunity. The challenge is that, we don’t have sufficiently trained people to analyze Big Data. The opportunity is that if you have the right resources who can transform Big Data to a meaningful use, you guarantee the success of your business.
What is Big Data? Big data is a large stream of structured, semi-structured and unstructured data that has unique characteristics. These characteristics are collectively called the 5V’s (Keith 13). The first V stands for volume in reference to the large set of data generated. The second V is for velocity signifying the speed at which new data is generated. The third V is for a variety, which signifies that data can come in any form and from various sources. The fourth V is the veracity is in reference to the uncertainty of the data. The last V is for a value of the data. The data has a perceived value for the organization using it.
Big data analytics is the process of extracting meaningful data out of a Big Data so that predictions can be made, or events can be correl...
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5. McKinsey Global Institute, Big data: The next frontier for innovation, competition, and productivity. June 2011.
6. MCMAHON, TAMSIN. "Elect Big Brother." Maclean's 125.41 (2012): 22-26. Academic Search Complete. Web. 27 Oct. 2013.
7. Keith Gordon, “What is Big Data?” Oxford Journals. ITNOW (Autumn 2013) 55 (3): 12-13 doi:10.1093/itnow/bwt037
8. Skiba, Diane, J. "Disruption In Higher Education: Massively Open Online Courses Moocs." Nursing Education Perspectives 33.6 (2012): 416-417.CINAHL Plus with Full Text. Web. 4 Nov. 2013.
9. Solving the Jobs Gap for Big Data Analytics Careers Requires Access to Cutting Edge Technology and Big Data: Survey.. ENP newswire. (04/30/2013)
10. Mearian, Lucas. "IT Skills Gap Forces Cios To Get Creative." Computerworld 46.8 (2012): 10. Computers & Applied Sciences Complete. Web. 23 Nov. 2013.
In Laura Pappano’s essay, “The Year of the MOOC”, she describes a MOOC, or a Massive Open Online Course, an online course to build a higher education for people around the world. After examining “Chunky Peanut Butter”, by James Gregory, I am convinced he’s the best college applicant to attend a MOOC because he’s flexible and can work with anyone, he’s active in the community and he never gives up.
The Human and Ethical Aspects of Big Data, quickly outlines an array of ethical problems that big data has had and will continue to develop in the upcoming years in our society. The author begins by giving an example of the earliest use of big data, the census. Census data can provide a plethora of benefits to society, representation in government, civil planning, such as road and water treatment, as these take years to construct and having the population and these necessities, Time align is crucial. As the author, uses the example of the internment of Japanese-Americans in 1943. Here is big-data supposed to help the citizens of the Unites States, the big data that is supposed to be private. Now in 1943, big data being used to discriminate
Big Data is a term used to refer to extremely large and complex data sets that have grown beyond the ability to manage and analyse them with traditional data processing tools. However, Big Data contains a lot of valuable information which if extracted successfully, it will help a lot for business, scientific research, to predict the upcoming epidemic and even determining traffic conditions in real time. Therefore, these data must be collected, organized, storage, search, sharing in a different way than usual. In this article, invite you and learn about Big Data, methods people use to exploit it and how it helps our life.
Grover, G. (2002). Career information center eighth edition, computers, business and office. (8th ed.). Michigan: visual education corporation.
This essay will debunk this nothing-to-hide argument, centring on how data is collected and analysed should be concerning to all, including those who have done nothing wrong. This essay will begin with a brief description of data mining and the prevailing arguments for its continual use. It will then elaborate on the issues and limitations of big data mining, notably the oversights in regards to data quality, interoperability, Jeffery Seifert’s concept of ‘mission creep’ and how they disregard privacy (2006, 209). These limitations will be further shown through examples of oversights in the implementation of these practices. This essay will conclude with outlining the possible developments that are needed in order to enhance privacy while being subject to strict regulations and
The key strategy implementation efforts at Amazon all surround the use of “big data”. Big data is the growth and availability of large volumes of structured/unstructured data. The use of big data has allowed decision making based upon data and analysis instead of past experience and intuition. Big data has directed organizational change in allowing Amazon to expand from an online book store to an internet giant. Revolutionary application of big data has allowed Amazon to create superior service quality while motivating employees by providing real time information to solve customer issues. Big data has strengthened Amazon’s competitive capabilities by pioneering the application of big data and charging a monthly fee to smaller businesses
Companies have transformed technology from a supporting tool into a strategic weapon.”(Davenport, 2006) In business research, technology has become an essential means that many organizations use in their daily operations. According to the article, Analytics is a major technological tool used. It is described as “the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions."(Davenport, 2006) Data is compiled to enhance business practices. When samples are taken, they are used to examine research and understand how to solve problems or why situations are as they are. Furthermore, in this article, Thomas Davenport discusses analytics from a business standpoint. He refers to organizations that have been successful in their usage of data and statistical analysis. In addition, he also discusses how data and statistics can be vital in the efforts to improve the operations of businesses.
Davenport, Thomas H., Paul Barth, and Randy Bean. "How Big Data Is Different." MIT Sloan Management Review. N.p., 30 July 2012. Web. 18 Mar. 2014. .
Currently the world has a wealth of data, stored all over the planet (the Internet and Web are prime examples), but it is needed to be understand that data. It has been stated that the amount of data doubles approximately
...ch Reips. ““Big Data”: Big Gaps of Knowledge in the Field of Internet Science.” International Journal of Internet Science 7.1 (2012): n. pag. Web. 16 Mar. 2014.
“The Big data phenomenon is driven by staggering and energizing advances in innovation. Exploiting these advances in the agricultural division could require new hierarchical linkages to be shaped – amongst suppliers and clients and among contenders.
For the past couple of decades the majority of businesses have wanted to construct a data-driven organization or company. Furthermore, companies around the world are considering harnessing data as a basis of competitive advantage over other companies. As a result, business intelligence and data science use are popular in many organizations today. The increase in adoption of these data systems is in response to the heavy rise in communications abilities the world over. Which, in turn ,has increased the need for data products. Indeed, the Data Scientist profession is emerging to be one of the better-paying professions due to the urgent need of their labor. This paper is going to discuss what business intelligence is all about and explain data science that is usually confused to be similar to business intelligence. I will tackle a brief overview of data scientists and their role in organizations.
Big data is a concept that has been misunderstood therefore I will be writing this paper with the intentions of thoroughly discussing this technological concept and all its dimensions with regard to what constitutes big data and how the term came about. The rapid innovations in Information Technology have brought about the realisation of big data. The concept of big data is complex and has different connotations but I intend to clarify its functions. Big data refers to the concept of a collection of large and complex amounts of data that are found extremely difficult to notate or even process by most on-hand devices and database technologies.
The implementation of online learning in many universities has proven to be a successful method of course delivery (Regan, Evmenova, Baker, Jerome, Spencer, Lawson, & Werner, 2012). Dickson-Dean, Galyen, and Moore (2011) proposed that online learning can promote successful learning opportunities for students as well as rewarding benefits for all educational stakeholders. Factors that contribute to the success of online learning include, but are not limited to, flexibility and accessibility, cost reduction, increased retention, and varied learning opportunities (Neely & Tucker, 2010). Online learning and associated technology is becoming increasingly adaptable and can be used to meet the educational needs of all students while providing opportunities for differentiated instruction (Krishnakumar & Kumar, 2011). Online learning provides both students and instructors with opportun...
Adopting big data can also help the banking industry by saving them from lots of embarrassment resulting from increase in the number of customer which in turn requires banks to improve on their performance. As stated earlier banks are entrusted with lots of information and this information must be safe will be required to be accessed ready and in a timely fashion. The use a normal small database will not be enough to perform this operation and if banks don’t embrace the use of big data they might start to experience failure in there system.