Abstract
The word Big Data is commonly used and it is not new today. Large, medium and small companies are starting to use Big Data to obtain their customers insight in order to serve them in a better way. The use of Big Data has become quite a crucial way for businesses to compete with their competitors. Also not only companies gain from the value of Big Data, it is also the customer’s hugely benefit from its usage. In association with Big Data’s real time information, which is one of the most heavily used application of personal and location data. As there is a significant growth in the use of smart phones and the use of GPS services from the phones and other devices, the use of smart traffic routing will definitely grow and in turn it will hugely benefit the customers. Big Data is not a single packaged technology, it is in general a platform consists of usage of various components to achieve a common goal. There are plenty of components available in the market for the businesses to customise their Big Data platform. The utilization of Big Data is becoming more and more essential to businesses and it is even more important for them to adopt the right Big Data platform to accomplish their goals. The main aim of this study is to propose a framework for building a Big Data platform for publishing industry. The proposed framework was validated in an UK based news publishing organisation to find out the suitability and adoptability of the framework for their Big Data platform.
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References
Architecting a Big Data Platform for Analytics: Architecting a Big Data Platform for Analytics (2015). http://www-01.ibm.com/common/ssi/cgi-bin/ssialias?infotype=SA&subtype=WH&htmlfid=IML14333USEN. Accessed 13 April 2015
AWS|Amazon Elastic Compute Cloud (EC2) - Scalable Cloud Hosting: AWS|Amazon Elastic Compute Cloud (EC2) - Scalable Cloud Hosting (2015). http://aws.amazon.com/ec2/. Accessed 20 February 2015
Big data: the next frontier for innovation, competition, and productivity|McKinsey & Company: Big data: The next frontier for innovation, competition, and productivity (2015). http://www.mckinsey.com/insights/business_technology/big_data_the_next_frontier_for_innovation. Accessed 18 January 2015
Dumbill, E.: Planning for Big Data: A CIO’s Handbook to the Changing Data Landscape. O’Reilly Media, Sebastopol (2012)
Eight Lessons from the Financial Times’ Digital Success|Mediashift|PBS: 8 Lessons from the Financial Times’ Digital Success|Mediashift|PBS (2015). http://www.pbs.org/mediashift/2014/05/8-lessons-from-the-financial-times-digital-success/. Accessed 10 February 2015
DeCandia, G., et al.: Dynamo: amazon’s highly available key-value store. In: SOSP 2007, Proceedings of Twenty-First ACM SIGOPS, New York, USA, pp. 205–220 (2007)
Han, J., Haihong, E., Le, G., Du, J.: Survey on NoSQL database. In: 2011 6th International Conference on Pervasive Computing and Applications (ICPCA), pp. 363–366. IEEE, October 2011
IBM big data platform - Bringing big data to the Enterprise: IBM big data platform - Bringing big data to the Enterprise (2015). http://www-01.ibm.com/software/data/bigdata/. Accessed 16 January 2015
Dean, J., Ghemawat, S.: MapReduce: simplified data processing on large clusters. Commun. ACM 51(1), 107–113 (2008)
Steele, J., lliinsky, N.: Beautiful Visualization: Looking at Data through Eyes of Experts. O’Reilly Media Inc., Sebastopol (2010)
Konstantinou, I., Angelou, E., Boumpouka, C., Tsoumakos, D., Koziris, N.: On the elasticity of NoSQL databases over cloud management platforms. In: Proceedings of the 20th ACM International Conference on Information and Knowledge Management, pp. 2385–2388. ACM, October 2011
Tewari, K.: Leveraging Big Data Opportunities For Growth – Keynote (2013). Online Video, 22 April. http://www.frequency.com/video/krishna-tewari-leveraging-big-data/92326953/-/5-1519156. Accessed 21 February 2015
McLaren Uses Racing Expertise in Data-Driven Consulting – Businessweek: McLaren Uses Racing Expertise in Data-Driven Consulting – Businessweek (2015). http://www.bloomberg.com/bw/articles/2014-10-02/mclaren-uses-racing-expertise-in-data-driven-consulting. Accessed 10 February 2015
Padhy, R.P., Patra, M.R., Satapathy, S.C.: RDBMS to NoSQL: reviewing some next-generation non-relational databases. Int. J.Adv. Eng. Sci. Technol. 11(1), 15–30 (2011)
Pethuru, R.: Handbook of research on cloud infrastructures for big data analytics (2014). Information Science Reference (an inprint of IGI Global)
Thomas, R.: Big Data Revolution: What Farmers, Doctors and Insurance Agents Teach Us About Discovering Big Data Patterns, 1st edn. Wiley, New York (2015)
Russom, P.: Big data analytics. TDWI best practices report, 4th Quarter 2011 (2011)
Ghemawat, S., Gobioff, H., Leung, S.T.: The Google file system. In: ACM SIGOPS Operating Systems Review, vol. 37, pp. 29–43. ACM (2003)
Vilas, K.S.: Big data mining. Int. J. Comput. Sci. Manage. Res. 1(1), 12–17 (2012)
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Kumaresan, A. (2015). Framework for Building a Big Data Platform for Publishing Industry. In: Uden, L., Heričko, M., Ting, IH. (eds) Knowledge Management in Organizations. KMO 2015. Lecture Notes in Business Information Processing, vol 224. Springer, Cham. https://doi.org/10.1007/978-3-319-21009-4_29
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DOI: https://doi.org/10.1007/978-3-319-21009-4_29
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