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Leveraging Service Computing and Big Data Analytics for E-Commerce

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Panel discussions on Leveraging Service Computing and Big Data Analytics for E-Commerce at the Workshop on e-Business (WeB) 2015 held on December 12, 2015 at Fort Worth, Texas, USA.

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Leveraging Service Computing and Big Data Analytics for E-Commerce

  1. 1. Karthikeyan Umapathy School of Computing University of North Florida Workshop on e-Business (WeB) 2015 Panel Discussions on Fort worth,TX December 12, 2015 http://www.unf.edu/~k.umapathy/ http://web2015.isy.vcu.edu/
  2. 2. Volume Variety Velocity Value  Big Data technologies describe a new generation of technologies and architectures designed to economically extract value from very large volumes of a wide variety of data by enabling high-velocity capture, discovery, and/or analysis. 2 Source: EU Data Market study by Gabriella Cattaneo, IDC Europe, May 27, 2014 Taken from http://www.slideshare.net/kszkuta/nessi-european-data-market-presentation-30/3
  3. 3. Source: EU Data Market study by Gabriella Cattaneo, IDC Europe, May 27, 2014 Taken from http://www.slideshare.net/kszkuta/nessi-european-data-market-presentation-30/3
  4. 4. Financial services Healthcare Discrete manufacturing Top 3 sectors by Investment Plans by 2015 Sectors Ranking by % enterprises users of Big Data Source: EU Data Market study by Gabriella Cattaneo, IDC Europe, May 27, 2014 Taken from http://www.slideshare.net/kszkuta/nessi-european-data-market-presentation-30/3
  5. 5.  Organizations have been gathering and analyzing data to make process improvements and increase profits  Moving from operational data focus to contextual data  Organizations have gone beyond collecting sales/transactional data and customer information (name and address) onto  Location-based data  Customer behavioral data  Apart from web, data are being captured from electronic devices such as smartphones and tablets  In the big data era, organizations focus more on  Creating new products and services  Predicting customer demands and needs  Responding to customer complaints in real time  Data monetization  Data is valuable not only for organizations but also for partners and other constituents Source: http://www.sas.com/news/intelligence_quarterly/q413.pdf
  6. 6.  Integrating online experience and in-store experience  Individualized and targeted marketing campaigns  Integrating multi-dimensional data  Locational data  Customer information  Customer purchase history  Social media data  Use real time data to create value and revenue via marketing, messaging, display advertising, loyalty services and point-of-sale payment options  FIS GenNOW™ Financial Services  https://www.youtube.com/watch?v=37jQZO-wshs
  7. 7.  Mobile services for offering location-based content delivery, entertainment, and advertisements  Cloud services (application Software as a Service (SaaS)) are key for providing mobile services  In upcoming years, as focus changes from mobile devices to other interconnected devices – cars, refrigerators, and TVs – Big Data as a Service will play major role  Big Data as a Service (BDaaS) is service applications offerings on the cloud catering to on-demand fulfillment model  Big data consumption services to gather data  Big data analytics services to analyze data for specific need  Big data analytics access services to retrieve results  Big data QoS services for security, validation, and audit
  8. 8.  Web Services will play key role in improving online customer experience  Gathering data on customer browsing behavior globally and providing localized navigational suggestions Current Process of Changing Site experience Proposed Framework

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