Introduction
In a dynamic global economy, companies and organizations have started to rely more and more on statistics gathered from their customers insights and behavior, internal processes and business operations with the aim of finding new opportunities for growth. In order to find and determine this information, large complex sets of data should be generated and analyzed by skilled professionals. The compilation of this large collection of data is known as “Big Data”.
The last years companies and organizations are more and more using Big Data to find new methods to improve the decisions they make, to discover new opportunities and improve the overall performance. For example, big data can be harnessed to address the challenges that arise when information that is dispersed across several different systems that are not interconnected by a central system. By aggregating data across systems, big data can help improve decision-making capability. It also can augment data warehouse solutions by serving as a buffer to process new data for inclusion in the data warehouse or to remove infrequently accessed or aged data. [Tech-Faq Website, 2013]
The big challenge of collecting all this data is to find solutions in how to be converted into useable information by identifying patterns and deviations from those patterns and many companies and organizations are working on it. Developers and software providers are rising to this challenge, turning big data management into a booming industry with major players in both private industry and open source communities. [Villanova University official website, 2013]
Security in Big Data
People create 2.5 quintillion bytes of data every day and almost 90% of the data in the world today has been cre...
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...eedings of the 4th International Symposium on Information, Computer, and Communications Security. techterms Website, "P2P", [Internet] http http://www.techterms.com/definition/p2p [Accessed December 05, 2013]
SearchCIO.comofficial website, “digital rights management [DRM]”, [Internet] http://searchcio.techtarget.com/definition/digital-rights-management [Accessed December 05, 2013]
David Cash, Alptekin Küpçü, Daniel Wichs [2013] Dynamic Proofs of Retrievability via Oblivious RAM, Advances in Cryptology – EUROCRYPT 2013.
C. Chris Erway, Alptekin Küpçü, Charalampos Papamanthou, Roberto Tamassia,[2012]Dynamic Provable Data Possession, Brown University, The 42nd IPP Symposium.
Jinyuan Li, Maxwell Krohn, David Mazieres, Dennis Shasha, Secure Untrusted Data Repository [SUNDR], NYU Department of Computer Science, 6th Symposium on Operating System Design and Implementation.
... that the encoding system by W. K. Wong, D. W. Cheung, E. Hung, B. Kao, and N. Mamoulis in [24] can be broken without using context-specific information. The success of the attacks in [25] mainly relies on the existence of unique, common, and fake items, defined by W. K. Wong, D. W. Cheung, E. Hung, B. Kao, and N. Mamoulis in [24]; our scheme does not create any such items, and the attacks by Y. Lindell and B. Pinkas in [5] are not applicable to our scheme. Tai et al. [9] assumed the attacker knows exact frequency of single items, similarly to us.
Manyika, J. (2011, May 1). Big data: The next frontier for innovation, competition, and productivity. McKinsey & Company. Retrieved May 13, 2014, from http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation
There is no proper definition of big data but after reading literature, The definition of big data tends to refer to the use of behavioral analytics and predictive analytics or other advanced data analytics methods to extract value from data.[1]
Attracting focus from firms in all industries, Big Data offers many benefits to those companies with the ability to harness its full potential. Firms using small data derive all of the data’s worth from its primary use, the purpose for which the data was initially collected. With Big Data, “data’s value shifts from its primary use towards its potential future uses” (Mayer-Schonberger & Cukier, 2013, p.99) thus leading to considerable increases in business efficiency. Employing Big Data analytics allows firms to increase their innovative capacity, and realize substantial cost reductions and time reductions. Moreover, Big Data techniques can be applied to support internal business decisions by identifying complex relationships within data. However, it is also important to recognize that much of Big Data’s value is “largely predicated on the public’s continued willingness to give data about themselves freely” (Brough, n.d., para. 11). As previously discussed, much of the content of Big Data is unstructured data from social media sites etc., and so if such data were to no longer be publically available due to regulation etc. the value of Big Data would be significantly diminished.
Big Data is a term used to describe the large volume of data whether structured or unstructured that inundates a given operation on a daily basis (http://www.SAS.com). Big Data consists of data sets that are so huge and complex that the customary data processing applications would not adequately handle them. Of late, the concept of Big Data has been used to describe the use of predictive analysis, user behaviour analytics and other complex data analytics techniques for the extraction value from data. The concept of Big Data can be understood through the description of the three V’s as advanced by Doug Laney, who is an industry analyst. First, Big Data can be understood in terms of Volume, whereby organizations collect large data from a variety
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
In today’s society, technology has become more advanced than the human’s mind. Companies want to make sure that their information systems stay up-to-date with the rapidly growing technology. It is very important to senior-level executives and board of directions of companies that their systems can produce the right and best information for their company to result in a greater outcome and new organizational capabilities. Big data and data analytics are one of those important factors that contribute to a successful company and their updated software and information systems.
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.
[6] O’Leary. Knowledge discovery as a threat to database security. In G. Piatetsky-Shapiro & W. J. Frawley, ‘Knowledge discovery in databases’, AAAI Press, page 507-516, 1991.
A data warehouse comprised of disparate data sources enables the “single version of truth” through shared data repositories and standards and also provides access to the data that will expand frequency and depth of data analysis. Due to these reasons, data warehouse is the foundation for business intelligence.
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 will then be defined as large collections of complex data which can either be structured or unstructured. Big data is difficult to notate and process due to its size and raw nature. The nature of this data makes it important for analyses of information or business functions and it creates value. According to Manyika, Chui et al. (2011: 1), “Big data is not defined by its capacity in terms of terabytes but it’s assumed that as technology progresses, the size of datasets that are considered as big data will increase”.
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.
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.