Processing Algorithm Developed by Google for Big Data - Essay Example

Processing algorithm developed by Google for Big Data 1. What storage system and processing algorithm were developed by Google for Big Data? The storage system and processing algorithm developed by Google for Big Data is known as the Bigtable (Chang, et al., 2006). As described, “Bigtable is a distributed storage system for managing structured data that is designed to scale to a very large size: petabytes of data across thousands of commodity servers” (Chang, et al., 2006, p. 1). 2. A scenario is a statement of assumptions about the operating environment of a particular system at a given time; that is, it is a narrative description of the decision-situation setting. What does a scenario describe, and what may it also provide? According to Sharda, Delen, & Turban (2014), “a scenario describes the decision and uncontrollable variables and parameters for a specific modeling situation. (Likewise), it may also provide the procedures and constraints for the modeling” (p. 57). 3. According to Kassam (2002), business metadata comprise information that increases our understanding of traditional (i.e., structured) data. What is the primary purpose of metadata? The primary purpose of metadata should be “to provide context to the reported data; that is, it provides enriching information that leads to the creation of knowledge” (Sharda, Delen, & Turban, 2014, p. 46). 4. What are the three nonfinancial objectives of the balanced scorecard? The three nonfinancial objectives of the balanced scorecard are as follows: (1) to improve customer value, (2) to intensify internal business processes, and (3) for organizational learning and growth (Schmarzo, 2013). 5. Describe the role of the simple split in estimating the accuracy of classification models. Simple split reportedly “partitions the data into two mutually exclusive subsets called a training set and a test set” (Olson & Delen, 2008, p. 140). 6. Define the term sensitivity analysis as it relates to ANNs. The term sensitivity analysis is defined as “a way to predict the outcome of a decision if a situation turns out to be different compared to the key prediction(s)” (Definition of Sensitivity Analysis, 2015, p. 1). 7. Sentiment analysis has many names. Which other names is it often known by? Sentiment analysis is also known as opinion mining (Sharda, Delen, & Turban, 2014). 8. What is the difference between white hat and black hat SEO activities? The difference between white hat and black hat search engine optimization (SEO) lies “within how an SEO expert conducts his back linking strategy. Black Hat SEO look for the quick and always wrong approach that gets you penalized. White Hat SEO approach looks at the long term approach that doesn`t get you penalized” (Goulart, 2014, p. 1). 9. What is the most common method for treating risk in decision trees and tables? The most common method for treating risk in decision trees and tables include simulation, use of certainty factors, and fuzzy logic (Sharda, Delen, & Turban, 2014, p. 165). 10. List four key terms related to genetic algorithms. Four key terms related to genetic algorithms are as follows: population, search space, chromosome, and genome (Harrim, n.d.). Population is defined as a group of individuals. Search space means all potential solutions to a problem. Moreover, chromosome was described as the blueprint for an individual. Finally, another key term, genome means a “collection of all chromosomes for an individual” (Harrim, n.d., p. 7). 11. What is knowledge engineering? Knowledge engineering is defined as “an engineering discipline that involves integrating knowledge into computer systems in order to solve complex problems normally requiring a high level of human expertise” (Feigenbaum & McCorduck, 1983; cited in Falquet, 2013, p. 1). 12. The two fundamental approaches to knowledge management are the process approach and the practice approach. Explain the differences between them. As the term implies, the process approach in knowledge management “puts emphasis on ways to promote, motivate, encourage, nurture or guide the process of knowing, and abolishes the idea of trying to capture and distribute knowledge” (Mentzas, n.d., p. 2). On the other hand, the practice approach reportedly “attempts to build social environments necessary to facilitate the sharing of tacit knowledge” (Kock, 2009, p. 17). 13. Define MapReduce. MapReduce is defined as “a software framework that allows developers to write programs that process massive amounts of unstructured data in parallel across a distributed cluster of processors or stand-alone computers” (Rouse, 2015). 14. How do the traditional location-based analytic techniques using geocoding of organizational locations and consumers hamper the organizations in understanding "true location-based" impacts? As learned, geocoding is a complex process where mistakes could significantly impact various facets of the organization’s performance; including risk management, as well as strategies contributing to financial success (Pitney Bowes Software, 2012). Too much reliance and dependence on traditional location-based analytic techniques using geocoding could hamper the organization’s understanding of “true-location-based” impacts, which could include disadvantages in potential intrusion of privacy as well as loss of personal identification and confidentiality issues, among others. 15. What is mobile social network and how does it extend the reach of popular social networks? Mobile social network is defined as a “group of mobile marketing applications that allow the creation and exchange of user-generated content” (Kaplan, 2012, p. 131). By virtue of its definition, it extends the reach of popular social networks through the utilization of digital technology and the Internet. References Definition of Sensitivity Analysis. (2015). Retrieved February 18, 2015, from Investopedia: http://www.investopedia.com/terms/s/sensitivityanalysis.asp Chang, F., Dean, J., Ghemawat, S., Hsieh, W., Wallach, D., Burrows, M., et al. (2006). Bigtable: A Distributed Storage System for Structured Data. Retrieved February 18, 2015, from googleusercontent.com: http://static.googleusercontent.com/media/research.google.com/fil//archive/bigtable-osdi06.pdf Falquet, G. (2013, February 19). Knowledge Engineering: Some Definitions. Retrieved February 18, 2015, from cui.unige.ch: http://cui.unige.ch/isi/icle-wiki/_media/cours:mttsd:knowledge_engineering_and_representation.pdf Feigenbaum, E. A., & McCorduck, P. (1983). The fifth generation (1st ed.). Reading, MA: Addison-Wesley. Goulart, M. (2014, September 18). Black Hat vs. White Hat SEO – Everything You Need To Know. Retrieved February 18, 2015, from Business2Community: http://www.business2community.com/seo/black-hat-vs-white-hat-seo-everything-need-know-01011885 Harrim, M. (n.d.). Genetic Algorithms. Kaplan, A. (2012). If you love something, let it go mobile: Mobile marketing and mobile social media 4 x 4. Business Horizons, Vol. 55, 129-139. Kock, N. (2009). Virtual Team Leadership and Collaborative Engineering Advancements: Contemporary Issues and Implications: Contemporary Issues and Implications. IGI Global. Mentzas, G. (n.d.). The two faces of Knowledge Management. Retrieved February 18, 2015, from imu.ntua.gr: http://imu.ntua.gr/sites/default/files/biblio/Papers/the-two-faces-of-knowledge-management.pdf Olson, D., & Delen, D. (2008). Advanced Data Mining Techniques . Springer Science & Business Media. Pitney Bowes Software. (2012). Business-strength Geocoding. Retrieved February 18, 2015, from mapinfo.com: http://www.mapinfo.com/wp-content/uploads/2013/05/business-strength-geocoding-whitepaper.pdf Rouse, M. (2015). MapReduce. Retrieved February 18, 2015, from techtarget.com: http://searchcloudcomputing.techtarget.com/definition/MapReduce Schmarzo, B. (2013, December 16). Big Data and The Balanced Scorecard Framework – Part I & II. Retrieved February 18, 2015, from InFocus: https://infocus.emc.com/william_schmarzo/big-data-and-the-balanced-scorecard-framework-part-i-ii/ Sharda, R., Delen, D., & Turban, E. (2014). Business Intelligence and Analytics: Systems for Decision Support. Prentice Hall. Read More