AIT 690-001 Syllabus – v1 January 1, 2013 Initial Syllabus (DRAFT)
C. Randall Howard, Ph.D., PMP
Instructor:
Graduate
Volgeneau Engineering Building Room 5323 Assistant:
Office:
(703) 899-3608
Phone:
Office:
choward@gmu.edu
E-mail:
Phone:
by appointment
Office Hours:
E-mail:
Office Hours:
TBD
by appointment
TBD
Course #:
AIT 690-001
Section:
001
CRN:
20863
Catalog Title: AIT 690 - Adv Topics Applied Technology
Course Title: Leadership in Big Data Intelligence with Small Details and Time
Term:
Time:
Building:
Room:
Spring 2013
Tuesday, 19:20-22:00
Planetary Hall
126
Pre-Requisites: Admission to Mason’s Applied IT program, or permission of instructor.
Course Readings:
 Designated w/ session topics below
 IMPORTANT NOTE: The material posted for reading and is NOT to be distributed, posted or used outside of the
AIT690-001 session. The material is copyrighted and is Intellectual Property of the individuals or companies
who have allowed Mason to use it for the Big Data Intelligence topic.
Course Themes:
Leadership in Big Data Intelligence with Small Details and Time
Exploring Metadata in Big Data Intelligence
Course Description:
Explore leadership, management, technical and analytical issues, solutions and associated gaps in processing an everincreasing volume of data (Big Data) by leveraging meta-tags and metadata (Small Details). The end-goal is to increase
the throughput of finding credible “facts of interest” (Intelligence) that represent threats to, or even opportunities for, a
given industry or domain (e.g. insurance, financial, national security, etc.) where frequently there is only a limited
window of time (Small Time) to avert an undesirable event or seize the opportunity.
OR:
“What are we learning”, “What do we know so far” and “We don’t know what we are doing” about Big Data
Intelligence (BDI).
Learning Objectives:
 Gain appreciation for Big Data Intelligence Landscape and Challenges
 Understand metadata's role and gain insights in Big Data Intelligence Systems (BDIS)
 Contribute to shape problem & solution space
 Become familiar with using processing and analytic with tools and techniques
Grading
Table 1. Grading Distribution
Item
Percentage
Individual Assignments
45%
Project / Case Study Work
40%
Professor's Discretion
15%
Table 2. Grading Scale
Letter Grade
Numerical
Range
A+
97-100
A
92-96
A90-91
B+
88-89
B
82-87
B80-81
C+
78-79
C
72-77
C70-71
Individual Assignments:
The individual assignment focus on the problem-solving aspects related to the processing and analytics within
BDIS. The assignment entails using tools and developing a report with observations, assessments, lessons
learned, etc.
Each student is allowed to gain assistance from other students or outside assistance on the “tool” aspect; however,
the report MUST be each students’ individual and independent work.
Group Project &/or Case Study Reports:
There will be a group exploration project. Each team is responsible for examining key industries or domains that
are facing big data challenges, such as major brick-and-mortar retail (e.g. Walmart), web-based companies(e.g.
Facebook, Groupon), banking, insurance, national security, etc.
The teams should examine, analyze and report on both the risks and opportunities as separate aspects. The major
facets of bureaucracy, technology and analytics should be included in the assessment. Strategic and operational
considerations should also be considered. Alternatives, tradeoffs and recommendations need to be reported.
Each group will select a team coordinator or leader who will help coordinate the overall progress of the team.
Additionally, the group makeup will need to have at least one technically-capable person to help support the team
with the course lab. Each team member's individual contribution to the final documents must be clearly
identified. Each group will be called on to present material throughout the semester.
Professor’s Discretion:
Participation is a portion of both the group project and individual grades. This has been a particular
challenge that we will be addressing throughout the semester in various, ad-hoc manners – depending on
how proactive the class is in averting “ad-hoc manners”.
Warning: “ad-hoc” manners are not necessarily the preferable option either.
All Sumissions
All work must be submitted at the scheduled time and place unless prior arrangements are made. Missed reports cannot
be made up without these prior arrangements.
All assignments will be graded on correctness as well as style and presentation. Each assignment is due on the
announced date before 12 midnight. There will be a strictly enforced 10% penalty per day for late submissions unless
otherwise specified.
IMPORTANT NOTES:
1. All submissions’ file names need to indicate student or group names.
a. For individual submissions, use this format:
LastName_First_Name_AssignmentName
b. For group submissions, questions, etc. for the Professor,
i. CLEARLY mark the subject of the item as w/ ATTN TO PROFESSOR: subject (I do not
monitor group discussion areas)
ii. Send a follow-up email to the Professor that the item has been posted
iii. For Submissions, use this format:
Group#_ArtifactName_State (eg.,Initial, Draft, Final), Version (e.g. #)
iv. Submit on group’s File Exchange area on Blackboard
2. ALL submissions should be in MS Word, unless otherwise specified. In other words, DO NOT submit .PDF’s
– I cannot provide feedback easily w/ .PDF’s.
3. A 10% penalty may be assessed for not following these instructions!
MORE IMPORTANT NOTES:
Academic Integrity. It is your responsibility to know and to follow Mason’s policy on academic integrity
(http://oai.gmu.edu/honor-code/masons-honor-code/).
SafeAssign. The professor utilizes the tool provided as part of Blackboard to check assignments against published
resources AND other students’ work.
Honor Code Statement:
As with all GMU courses, INFS 622 is governed by the GMU Honor Code. In this course, all assignments, exams, and
project submissions carry with them an implicit statement that it is the sole work of the author, unless joint work is
explicitly authorized. Help may be obtained from the instructor or other students to understand the description of the
problem and any technology, but the solution, particularly the design portion, must be the student's own work. If joint
work is authorized, all contributing students must be listed on the submission. Any deviation from this is considered an
Honor Code violation. (© Jeff Offutt).
To stay safe:
 Provide citations for your work – group and individual – even if it is “adapted from”.
 Do not work in groups to complete individual work.
 Do not copy and paste material from the text except for short, pithy definitions that cannot necessarily be reworded easily.
ODS Statement. If you have a disability and wish academic accommodations, please see the Professor and contact the
Office of Disability Services (703) 993-2474, (http://www2.gmu.edu/depts/unilife/ods//).
AIT690-001 Class Schedule
V0.01: Session 0 Adjustment
Schedule Notes:
 Order is (re-)arranged to facilitate more time to apply the discussion to the project artifacts
 Project Artifacts w/in Lectures are highlighted in yellow.
 Schedule WILL change as needed to facilitate learning according to personality & makeup of the class
 Items marked w/ a “[D] party:” indicate a deliverable from the party: listed (e.g., Students, Groups, Professor)
 Color Legend:
Red:
Changed / Changing Items
Yellow:
Project Artifacts
Version 1.0: Initial Session
Session
#
Date
Session Themes
Mauve:
Items are due
Pale Blue:
Milestones or Events
AIT690-001 Fall 2012 Schedule
Session Topics
Speakers
Case Study Time Allowed
in Class
March 24, 2016
Learning & Leadership Details
Course Foundations


1
Jan
22
Course Overview
 Introductions
 Roster & Profiles
 Genesis of Course
 Course Overview
 Students’ Objectives?
--------------------------------- The Tools & “Lab
Supplies”
Howard

Lecture Slides:AIT690-001 Overview.pptx
Read-Aheads:
o Big Data in the US Intel Community 26Dec
Large-1
o What_is_Data_Science.pdf
o emc-data-science-study-wp.pdf
o References in AIT690-001 Overview.pptx
Reference:
o Lecture_Series_I_Material/Gus Hunt
GMU_Big_Data_Course-final.ppt
o Big Data Intelligence Systems Leadership &
Operation Executive Lecture Series I.pdf
o http://isrc.gmu.gmu
o http://isrc.gmu.edu/ExecLectureSeries/ExecLect
ureSeries.html
Version 1.0: Initial Session
Session
#
Date
AIT690-001 Fall 2012 Schedule
Session Themes
Session Topics


2
Jan
29
Metadata vs.
Meta-Tagging vs.
Data



3
Feb 5
Data Science Solving Big Data
Problems with
Applied Statistics





Big Data “So-What”
What is Metadata?
"Meta-tagging"?
What is the difference
between Meta-tagging,
Metadata and data
How can metadata help?
(Big-Data Metadata)
Sufficiency Principle
Major types of statistics
Major types of problems
Applying data science &
statistics to solve the
problems
Incremental Problem
Solving (Hypothesis,
Implement, Revise)
Lab Assignment
Speakers
Learning & Leadership Details


Howard

Forbes
4
Feb
12
Big Data
Intelligence
Landscape

Data Basics: What makes
data so gnarly?
What makes Big Data so
challenging?


Aiken
Mattox
AIT690-001 So-What, Data vs. Metadata, Big Data
Sufficiency.pptx
Read-Aheads:
o Finkelstein&Aiken for AIT690-001.pdf
o Big Data Principles of Sufficiency v1-1.pdf
Reference:
o TBS



[D] Lab Work Assigned
Lecture Slides: To be supplied
Read-Aheads:
o To be supplied
 Reference:
o To be supplied


March 24, 2016
Lecture Slides:
o DMP Appraisal Instructions.key (Aiken)
o Big Data and Massive Analytics Short Class
(Maddox)
 Read-Aheads:
o Practicing Data Management - Chapter 6.pdf
 Reference:
o “Mythical Man Month” Posted
o “Sliver Bullet”: To be supplied
o DM Problems:
http://blog.tonybain.com/tony_bain/2008/12/top-10data-management-issues-for-2009.html
Version 1.0: Initial Session
Session
#
Date
AIT690-001 Fall 2012 Schedule
Session Themes
Session Topics



5
Feb
19
Pedigree &

Lineage (P&L)'s
role in Information
Sharing

6
Feb
26
Big, Notional
Problem Solving



7
Big Data Cloud
Mar 5 Processing (Small
Time)
Mar
12
Spring Break


Political Architectures
How is metadata vital in
Information Sharing?
Why is Pedigree &
Lineage so important?
How can metadata (e.g.
P&L or traceability) in
transitioning from
strategy to tactical
operations have an
important and vital role?
Thinking outside of the
box
We don't know what we
are doing?
Leveraging Conflict &
"Masterminding"
Thinking outside of the
box
We don't know what we
are doing?
Leveraging Conflict &
"Masterminding"
Speakers
March 24, 2016
Learning & Leadership Details


McCormick
Lecture Slides: To be supplied
Read-Aheads:
o DNI Material on Info Sharing
o P&L Slides (To be supplied)
 References:
o To be supplied


Sagan
Lecture Slides: To be supplied
Read-Aheads:
o Conflict material?
o Sagan's Material
 Reference
o To be supplied


Hughes
Lecture Slides: To be supplied
Read-Aheads:
o To be supplied
 Reference:
o To be supplied
Version 1.0: Initial Session
Session
#
Date
AIT690-001 Fall 2012 Schedule
Session Themes
Session Topics


8
Mar
19


Organizational
Values and
DecisionMaking
Enterprise
Architecture
Principles &
Techniques
Evaluation
Criteria





9
Mar
26
Mastering the
Bureaucracy
(Part 1)
[Being Rescheduled]


Speakers
March 24, 2016
Learning & Leadership Details

Why is Big Data
Intelligence a "Wicked
Problem"?
How can business basics
in Engineering &
Operations determine the
important metadata
What is Enterprise
Architecture? How do the
principles apply?
How can we harness
uncertainty by dealing w/
the predictable aspects?
How can metadata
facilitate Risk Mitigation?
Howard
Understanding purpose
and power of bureaucracy
How bureaucracy effects
choosing which metadata Magee
Howard
should be used?
How metadata can
facilitate multiple
disciplines?
Lecture Slides:
o AIT690-001 Wicked Problems, Learning
Organization & Decision Making.pptx
 Read-Aheads:
o http://www.infed.org/thinkers/senge.htm
o http://www.infed.org/biblio/learningorganization.htm
o TEN#38 Enterprise Architecture as Strategy.pdf
 Reference:
o FSAM_Complete_v1_1.pdf(http://www.fsam.gov/fe
deral-segment-architecture-methodology-toolkit/)
o ValueMeasuring_Methodology_HowToGuide_Oct_
2002.pdf(http://www.cio.gov/documents/ValueMe
asuring_Methodology_HowToGuide_Oct_2002.pdf)
o introduction-to-vmm-bah-0ct2004.pdf((http://www.fgdc.gov/policyandplanning/
50states/introduction-to-vmm-bah-0ct-2004.pdf)


Lecture Slides: Big Data Bureaucracy
Read-Aheads:
o To be supplied
 Reference:
o To be supplied
Version 1.0: Initial Session
Session
#
Date
AIT690-001 Fall 2012 Schedule
Session Themes
Session Topics
March 24, 2016
Speakers
Learning & Leadership Details

10
Apr 2
Mastering the
Bureaucracy
(Part 2)
Strategic
Leadership &
Planning
11
Apr 9
Group Project
Reviews
12
Apr
16
Securing Data and
Privacy
Why are Politics & Laws,
Contracts & Ethics so
vital?
 What effect do politics,
laws, contracts, ethics
play on which metadata
should be used?
 Leadership & Change in
Culture
 How can we transition
culture to accept:
o Change is imperative
o Learning gap is not
trivial
o Business as normal
will not suffice



Groups


Data Encryption
Key Management


Latiff
Quinn
Augie L.
Vasic,
eruces.com
Lecture Slides: To be supplied
Read-Aheads:
o Harvard Business Studies: 606003-VW of AmericaManaging IT Priorities
(http://hbr.org/search/vw%252520managing%2525
20it%252520priorities/
 Reference:
o Strategic Planning Research Cutouts.docx
o


Lecture Slides: To be supplied
Read-Aheads:
o To be supplied
 Reference:
o To be supplied
Version 1.0: Initial Session
Session
#
13
Date
Apr
23
AIT690-001 Fall 2012 Schedule
Session Themes
Data Quality
Session Topics





Grasping Data Fitness
Measuring Quality
Performance &
Throughput
Course Wrap-up
Course Evaluations
14
Apr
30
Case Study Report
Day

15
May
7
Final Course
Reports
Extended due to 10/30
Cancellation
Case Study reports
Speakers
March 24, 2016
Learning & Leadership Details


Howard
Team
Howard
Class
Lecture Slides: AIT690-001 Data Quality.pptx
Read-Aheads:
o Talburt’s Slides References
o Get w/ Talburt
 Reference:
o Data quality:
http://robertlambert.net/2011/11/the-gnarlysubtle-seeming-data-quality-question/



[D] Teams: Case Study Reports & Presentations
Lecture Slides: AIT690-001 Wrapup.pptx
Read-Aheads:
o To be supplied
 Reference:
o To be supplied
[D]: Students: Final “Lab” Reports Due