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defintition of big data essay
defintition of big data essay
defintition of big data essay
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Big Data: A Continuing Evolution
Big Data today is continuing to evolve, and appears to be in the beginning stages of evolution. It will continue to grow and need constant research initiatives to keep up. This paper will look at the definition of Big Data and how it is being used, why the current DBMS is unable to handle Big Data efficiently, what hardware and software solutions are being tested, and what challenges the researchers are facing.
Big Data is a term used today to talk about the vastly growing amounts of data, (mainly unstructured, but can also include structured and semi structured data), out there to be mined [1]. Data mining attempts to derive meaningful information from data. As the amount of data in different varieties keeps increasing, it becomes harder to process useful information at an acceptable return time rate. Current software tools and hardware are failing to keep up with Big Data needs. Big Data requires one to be able to process complex computer data at the Petabyte or Exabyte level. [2].
Big Data is developing from many sources, and with storage capacity has been doubling in size every 14 months for the past 30 years, keeping data has become cheaper and cheaper [3]. Some of the sources of data are social media on the Internet, mobile sensors, astronomy, transaction logs, and many more [4]. Companies today desire to collect mass amounts of data that may not be useful today, but could be later. The popular social media site, Facebook, collects over 500 Terabytes of day a day [4]. The term Big Data is not only defined by its volume, by its ability to retrieve knowledge in a reasonable amount of time. For example, Netflix, a video streaming service, utilizes a machine-learning technique ...
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...the Future," ACM SIGKDD Explorations Newslette, vol. 14, no. 2, pp. 1-5, 2012.
[6] C. Ordonez, "Can We Analyze Big Data inside a DBMS?," in DOLAP '13 Proceedings of the sixteenth international workshop on Data warehousing and OLAP, San Francisco, 2013.
[7] C. Bear, A. Lamb and N. Tran, "The Vertica Database: SQL RDBMS For Managing Big Data," in MBDS '12 Proceedings of the 2012 workshop on Management of big data systems, San Jose, 2012.
[8] N. Tran, S. Bodagala and J. Dave, "Designing query optimizers for big data problems of the future," Proceedings of the VLDB Endowment, vol. 6, no. 11, pp. 1168-1169, 2013.
[9] S. Madden, "From Databases to Big Data," IEEE Internet Computing, vol. 16, no. 3, pp. 4-6, May 2012.
[10] S. W. Cunningham, "Big Data and Technology Readiness Levels," Engineering Management Review, IEEE , vol. 42, no. 1, pp. 8-9, 2014.
Big Data is characterized by four key components, volume, velocity, variety, and value. Furthermore, Big Data can come from an array sources such as Facebook, Twitter, call
The characteristics of this unstructured data are high in volume, high velocity, or high variety and complexity. Big data comes from sensors, devices, video/audio, networks, log files, transactional applications, web, and social media - much of it generated in real time and in a very large scale.
Databases always used to fascinate me from my under graduation with great curiosity to know how large data is managed and queried. This led me to do Masters in computer science concentrating in the field of Data Management. In the course of my study, I understood the concepts of DBMS which provides a robust and efficient way of managing and mining data. Through the courses like Database Systems (ITCS 6160), Knowledge Discovery in Databases(ITCS 6162) and Knowledge Based Systems(ITCS 6155) I gained enough theoretical and practical knowledge about the importance of proper organization of data, good techniques to build an efficient database management system and how well the data can be managed.
At this point, is important to note that Big data itself does not represent more large data set of structured and unstructured data; nowadays bigger than ever and in continuous expansion that can be defined as the "problem of big data" (Cox M. & Ellsworth D., 1997). The ability to organize this "problem" given certain parameters and to be able to build a model or representation of a reality taking care of the existing patterns and relationships to find the true value that lies hidden in data is what can be defined as Data mining (DM) (Kadiyala, S. S., & Srivastava, A., 2011).
In short, the Big Data challenges for organizations and enterprises in today's digital age. Once mastered big data, they will have greater chances of success in today's competitive environment, the world would benefit more from the extracted information more accurately, more useful lower costs. Still the criticism revolves around Big Data, however, the field is still very new and we'll see in future Big Data will evolve like.
Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.
The creativity and ingenious of human beings has enabled the development of technologies that have overall, benefited all of mankind. Arguably one of the most if not the most pivotal man made technological achievement is that of the internet. The internet has allowed for the seeming less transfer of data and information in a matter of seconds. With this innovation has come an increase in communication, enhancement of understanding other cultures, and a mass gathering of data. The amount of data now in existence due to the internet has created the need for big data. Big data has developed as a solution to the traditional computer infrastructure that has become obsolete due to its inability to handle the massive amounts of data now in existence. The benefits of big data are ever expanding and attractive as it can improve the efficiency of companies, research, health sciences yet, the consequences of using big data are just as intensifying and are causing some backlash in many communities. The current issues surrounding big data and the increasingly dependent nature of the world’s people on big data will undoubtedly impact the use of big data in the future.
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]
Evidently, there are many benefits to working with Big Data analytics and procedures, and as computing capabilities continue to advance these benefits are only projected to increase. Data’s value is now more dependent on its cumulative potential uses than its initial use; however it is unlikely that a single firm will be able to unlock all of the dormant value from a given dataset. Therefore, in order to maximize Big Data’s value firms can license their accumulated data to third parties in exchange for royalties. In doing so, all agents have incentive to maximize the value that can be extracted by means of re-using data.
Poor Database Application Design: A poor database design can lead to severe performance issues. An application which uses large tables (e.g. table with 100000 rows and 100 columns), ill-formed and un-optimized queries, improper use of database connections and so on.
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.
[7] Elmasri & Navathe. Fundamentals of database systems, 4th edition. Addison-Wesley, Redwood City, CA. 2004.
A new energy is rising within CNS. Over the past year, many members of our administrative computing team have been developing Oracle applications. It is a new challenge to both CNS and our clients. We journey up the learning curve together and over the trial-and-error hurdles. Each day offers a new opportunity to understand another concept or process.
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.