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.

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. 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. 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. 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.  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.  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.  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.  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