Interested in increasing your knowledge of the Big Data landscape? This seminar is designed for those who are new to data science and interested in learning what is the Big Data Era. It is for those who want to understand and converse with the terminology and comprehend the fundamental concepts behind the problems, applications, and systems of big data. This session is will help you to start thinking about how Big Data might be useful in your business or career. At the end of this seminar, participants will be able to: a. Describe the Big Data landscape using examples of real world big data problems including people, organizations, and sensors. b. Explain the V’s of Big Data (volume, velocity, variety, veracity, valence, and value) and how they impact data collection, monitoring, storage, analysis and reporting. c. Get value out of Big Data to structure your analysis. d. Identify what are/what are not big data problems and how to reformat big data problems into data science questions.

1. Introduction to the Big
Data Landscape: Creating
Real World Solutions -
(BEYA 2439)
Washington Marriott Wardman
Park 2660 Woodley Road NW
Washington DC, 20008
Room: Wilson C
Saturday, 2/10/2018
12:00 pm. - 1:30 p.m.

2. Our Team
Stacey Dixon, Ph.D
Colonel Terrance Adams
Lanae Wheeler
Aaron J. Ferguson, Ph.D
Ernest L. Smiley

3. Introduction to the Big Data Landscape:
Creating Real World Solutions
• Interested in increasing your knowledge of the Big
Data landscape? This seminar is designed for those
who are new to data science and interested in learning
what the Big Data Era is. It is for those who want to
understand and converse with the terminology and
comprehend the fundamental concepts behind the
problems, applications, and systems of big data. This
session will help you to start thinking about how Big
Data might be useful for your business or career.

4. Introduction to the Big Data Landscape:
Creating Real World Solutions
• At the end of this seminar, participants will be
able to:
• Describe the Big Data landscape using
examples of real-world big data problems
including people, organizations, and sensors.
• Explain the V’s of Big Data (volume, velocity,
variety, veracity, valence, and value) and how
they impact data collection, monitoring,
storage, analysis, and reporting.

5. Introduction to the Big Data Landscape:
Creating Real World Solutions
• Get value out of Big
Data to structure your
analysis.
• Identify what are/what
are not big data
problems and how to
reformat big data
problems into data
science questions.

6. Panel Moderator – Stacey Dixon, Ph.D.
Current employer: Intelligence Advanced Research Projects Activity
(IARPA), Office of the Director of National Security, Deputy Director
Previous employers and roles:
National Geospatial-Intelligence Agency (NGA), Deputy Director of
Research and Office Director
NGA, Congressional and Intergovernmental Affairs, Chief
U.S. House of Representatives Permanent Select Committee on
Intelligence (HPSCI), budget director and professional staff.
Central Intelligence Agency (CIA), National Reconnaissance Office,
Advanced Systems and Technology Directorate, Engineer.
Education:
Ph.D. and M.S., Mechanical Engineering, Georgia Tech.
B.S. M.E., Stanford University.
Post-doctoral fellow in Chemical Engineering, University of Minnesota.
Hometown: Washington, DC

7. Panel Member – Colonel Terrence A. Adams
Current employer: United States Air Force (USAF), Headquarters Air
Mobility Command, Scott Air Force Base, IL; Director of
Communications & Chief Information Officer.
Previous employers and roles:
USAF: squadron, group, wing, major command, air staff and joint
levels.
Education:
MBA, Troy State University.
M.S. Military Operational Art & Science, Air Command and Staff
College, Maxwell AFB.
Air War College (correspondence), Air University, Maxwell AFB.
M.S. National Security Strategy, National War College, Ft. McNair.
B.S. Information Systems, Auburn University at Montgomery.
Hometown: Tuskegee, AL

8. Panel Member – LaNae Wheeler
Current employer: Leidos Global Services Group, an Information
Technology company, Principal Systems Engineer.
Previous employers and roles:
Defense Information Systems Agency (DISA)
Headquarters, Unite States Marine Corps.
Lockheed Martin Corporation.
Education:
B.S. Computer Science, Hampton University, Hampton, VA.
M.S. Information Management, Marymount University.
Certificate of Knowledge Management Engineering, The George
Washington University.
Advanced Management Program Certificate, National Defense
University.
Hometown: Suffolk, VA

9. Panel Member – Aaron J. Ferguson, Ph.D
Current employer: National Security Agency, Deputy Technical Director
(TD), Enterprise Discovery Operations Group, Directorate of Operations.
Adjunct faculty member, Howard University and University of Maryland
University College (UMUC)
Previous employers and roles:
Deputy TD; Analysis and Mitigations Directorate, IAD.
NSA TD, Joint Mitigation Strategy Planning Division, NTOC
NSA TD of the Analytic Tradecraft Office (ATAO), IAD
2006 Technical Leader, Office of Advanced Network Operations, IAD
2003-2006 NSA Visiting Professor at the United States Military
Academy at West Point.
Education:
M.A. and Ph.D. Applied Math and Statistics, University of Delaware.
M.S. Operations Research University of New Haven, CT.
B.S. Electrical Engineering, Howard University.
Hometown: Brooklyn, NY

10. Panel Member – Ernest L. Smiley
Current employer: Founder and the Managing Director of Georgetown
Analytics and Technology.
Previous employers and roles:
National Geospatial-Intelligence Agency (NGA), Chief Data Scientist.
National Aeronautics and Space Administration (NASA), Deputy
Director, Senior Engineering Manager, Chief Architect, Senior
Information Technology Security Manager and Program Manager.
Office of the Secretary of Defense (OSD), Central Intelligence Agency
(CIA), Department of Energy (DOE), General Dynamics, Sprint and
Lockheed Martin.
Education:
M.S. Technology Management, Georgetown University.
MBA in Finance and Accounting, University of Maryland (UMD).
B.S., University of Maryland. Graduate Certificate in Data Science,
Georgetown University.
Hometown: Alexander City, AL

11. What is Big Data?
• “Big data is data sets that are so voluminous
and complex that traditional data processing
application software are inadequate to deal
with them. Big data challenges include
capturing data, data storage, data analysis,
search, sharing, transfer, visualization,
querying, updating and information privacy.”
(https://en.wikipedia.org/wiki/Big_data)

12. The Five Vs of Big Data
• Volume - The quantity of generated and stored
data. The size of the data determines the value
and potential insight- and whether it can
actually be considered big data or not.
• Variety - The type and nature of the data. This
helps people who analyze it to effectively use
the resulting insight.

13. The Five Vs of Big Data cont.
• Velocity - In this context, the speed at which
the data is generated and processed to meet
the demands and challenges that lie in the path
of growth and development.
• Variability - Inconsistency of the data set can
hamper processes to handle and manage it.
• Veracity - The data quality of captured data
can vary greatly, affecting the accurate
analysis.

14. Data Science
• “Data science, also known as data-driven
science, is an interdisciplinary field of scientific
methods, processes, and systems to extract
knowledge or insights from data in various
forms, either structured or unstructured, similar
to data mining.” https://en.wikipedia.org/wiki/Data_science