IBC Conference Panel: Big Data - Current Issues & Trends Department of Computer Science & Information Systems Saint Leo University 20 February 2015

“If it fits in one computer, then it isn’t ’big data’.” - Klaus K. Obermeier, Business Insights through Big Data; 15 May 2012.

Contents About Schedule Expectations Topics

Contents  About Schedule Expectations Topics

About This panel is being held for the first time at the 2015 International Business Conference (IBC) at Saint Leo University. The intention is to bring the community together and promote data literacy and information security education & awareness Panelists are from different areas of IT (academia, government, industry)

Panel members Mr. Jake Perlman Chief Information Officer BrightHouse Networks Mr. Steven Carroll Associate Vice President and Chief Information Officer Saint Leo University Dr. Michael Moorman Professor of Computer Science Saint Leo University

Contents About  Schedule Expectations Topics

Schedule Panel session Date: Friday Feb 20, 2015 Time: 9: :20 AM Location: Donald R. Tapia School of Business TECO Hall (ground floor)

Contents About Schedule  Expectations Topics

Expectations from Panel Members Saint Leo community has high regard for you and is excited to hear from you! Comments on big data topics from the perspective of your area of work (e.g. academia, government, industry) Efforts in your respective areas of work towards addressing or solving security issues Specific details along with just general observations We like to hear expert comments (from the “horse’s mouth”) Time Maximum 3 min per topic per panelist (comes to 4 topics) 10 min for Questions from audience

Contents About Schedule Expectations  Topics

Big Data Definition – Big Data are assumed to have the following characteristics: High Volume High Velocity High Variety These characteristics were first discussed by Doug Laney in a Garner Group report about e-commerce trends (Laney, D. (2001).

Topic 1: Fundamentals “640K ought to be enough for anybody..” – Bill Gates, 1981 What happened since then? What are the changes to world of computing that paved the way for Zettabytes of “Big Data”? Population? Technology? Two biggest challenges handling big data?

“I think there is a world market for maybe five computers.” - Thomas J. Watson, Chairman and CEO of IBM, 1943

Topic 2: Infrastructures What are the changes in requirements and challenges for networks, devices and apps to cope with big data? (Obviously, every parameter needs increasing, but are any in particular that are most important?) Networking: Speed, QoS, Bandwidth, Reliability? Devices: CPU speed, memory size? Apps: Compatibility (desktop, mobile),...?

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” - E. W. Dijkstra

Topic 3: Management of Frameworks Major changes in frameworks to manage data, especially of DBMS (Federated, Distributed) are obviously necessary along with data and knowledge management models. How do you process and obtain actionable intelligence in real-time from these frameworks? Columnar and key attribute databases: which is better?

“Three may keep a secret, if two of them are dead.” - Benjamin Franklin

Topic 4: - Security & Privacy With rising size and complexity of data, security and privacy concerns also seem to rise. For example, intrusions and DoS attacks using packet flooding are harder to prevent, detect or mitigate. In your line of work, can you state the biggest concern about this and the steps you are taking to address it? How do we balance the economic impacts of big data search: The usefulness of it versus the abuse of it (mining people’s shopping habits to infer product preferences?

Very Large Data Sets By analyzing very large collections of data, correlations and relationships can be found which might otherwise be undetectable. Consider doing market research with a huge number of point of sales receipts. Walmart records over one million (1,000,000) transactions per hour (The Economist, 2010).

Topic 5: Applications of Big Data Big data is now everywhere, virtually in every industry including healthcare, e-government, finance, law, transportation, you name it. In addition, Internet of Things allows prevention of failure through easier detection and optimal performance. In your opinion, what are the most profitable areas where one could offer to provide storage, processing and transmission of big data (in terms of returns, ease of launch, maintenance etc.)?

“ There are three kinds of lies: lies, damned lies, and statistics.” - Mark Twain (Samuel Langhorne Clemens)

Topic 6: Ethical Concerns Eric Schmidt said, "if you have something that you don't want anyone to know, maybe you shouldn't be doing it in the first place". How to detect if someone is doing something wrong in this ocean of data? Considering recent concerns about profiling and civil liberties, what safeguards do you feel are needed to protect individuals from discrimination based on suspected membership in ethnic, religious, political, sexual, or other minority groups based upon analytic profiling?

Audience Turn

Thank You Panelists available for more questions & discussions outside.