AIT 580-001 Syllabus– v1August 3, 2013Initial Syllabus (DRAFT)
Instructor:Office:
Phone:
E-mail:
Office Hours: / C. Randall Howard, Ph.D., PMP
Volgeneau Engineering Building Room 5323
(703) 899-3608
by appointment / Graduate Assistant:
Office:
Phone:
E-mail:
Office Hours: / TBD
by appointment
TBD
Course #:AIT 580
Section:001
Title:Analytics: Big Data to Information
CRN:77766
Term:Fall 2013
Time: Tuesday, 19:20-22:00
Building:Innovation Hall
Room: 137
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 reference is NOT to be distributed, posted or used outside of the INFS622 session. The material is copyrighted and is Intellectual Property of various parties.
Course Themes:An Overview of Leadership in Big Data
Course Description:
Course provides an overview of Big Data and its use in commercial, scientific, governmental and other applications. Topics include technical and non-technical disciplines required to collect, process and use enormous amounts of data available from numerous sources. Lectures cover system acquisition, law and policy, and ethical issues. It includes brief discussions of technologies involved in collecting, mining, analyzing and using results.
Learning Objectives:
- Gain appreciation for Big Data Intelligence Landscape and Challenges
- Contribute to shape problem & solution space
- Become familiar with using processing and analytic with tools and techniques
Grading
Table 1. Grading Distribution
Item / PercentageIndividual Assignments / 40%
Project / Case Study Work / 45%
Professor's Discretion / 15%
Table 2. Grading Scale
Letter Grade / Numerical RangeA+ / 97-100
A / 92-96
A- / 90-91
B+ / 88-89
B / 82-87
B- / 80-81
C+ / 78-79
C / 72-77
C- / 70-71
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 responsiblefor 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.
Other assignments:
The professor may assign homework for individuals, groups, or the class as a whole.
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.
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All Submissions
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, with the exception of the project that are due before class begins on presentation day. There will be a 10% penalty per day for late submissions unless otherwise specified.
All submissions’ file names need to indicate student or group names.
- For individual submissions, use this format:
LastName_First_Name_AssignmentName
- For group submissions, questions, etc. for the Professor,
- CLEARLY mark the subject of the item as w/ ATTN TO PROFESSOR: subject (I do not monitor group discussion areas)
- Send a follow-up email to the Professor that the item has been posted
- For Submissions, use this format:
Group#_ArtifactName_State (eg.,Initial, Draft, Final), Version (e.g. #)
- Submit on group’s File Exchange area on Blackboard
ALL submissions should be in MS Word, unless otherwise specified. In other words, DO NOT SUBMIT PDF’s – we cannot effectively provide feedback on .PDF’s.
A 10% penalty may be assessed for not following these instructions!
Electronic Devices
Laptops are allowed for the purpose of taking notes during class only. Phone usage is discouraged, and is only allowed in the case of personal or business emergencies. If we suspect that these allowances are being abused, then restrictions will be enforced.
Academic Integrity
The integrity of the University community is affected by the individual choices made by each of us. GMU has an Honor Code with clear guidelines regarding academic integrity. Three fundamental and rather simple principles to follow at all times are that: (1) all work submitted be your own; (2) when using the work or ideas of others, including fellow students, give full credit through accurate citations; and (3) if you are uncertain about the ground rules on a particular assignment, ask for clarification. No grade is important enough to justify academic misconduct. Plagiarism means using the exact words, opinions, or factual information from another person without giving the person credit. Writers give credit through accepted documentation styles, such as parenthetical citation, footnotes, or endnotes. Paraphrased material must also be cited, using MLA or APA format. A simple listing of books or articles is not sufficient. Plagiarism is the equivalent of intellectual robbery and cannot be tolerated in the academic setting. If you have any doubts about what constitutes plagiarism, please see me.
As in many classes, a number of projects in this class are designed to be completed within your study group. With collaborative work, names of all the participants should appear on the work. Collaborative projects may be divided up so that individual group members complete portions of the whole, provided that group members take sufficient steps to ensure that the pieces conceptually fit together in the end product. Other projects are designed to be undertaken independently. In the latter case, you may discuss your ideas with others and conference with peers on drafts of the work; however, it is not appropriate to give your paper to someone else to revise. You are responsible for making certain that there is no question that the work you hand in is your own. If only your name appears on an assignment, your professor has the right to expect that you have done the work yourself, fully and independently.
GMU is an Honor Code university; please see the Office for Academic Integrity for a full description of the code and the honor committee process. The principle of academic integrity is taken very seriously and violations are treated gravely. What does academic integrity mean in this course? Essentially this: when you are responsible for a task, you will perform that task. When you rely on someone else’s work in an aspect of the performance of that task, you will give full credit in the proper, accepted form. Another aspect of academic integrity is the free play of ideas. Vigorous discussion and debate are encouraged in this course, with the firm expectation that all aspects of the class will be conducted with civility and respect for differing ideas, perspectives, and traditions. When in doubt (of any kind) please ask for guidance and clarification.
It is your responsibility to know and to follow Mason’s policy on academic integrity (
The professor utilizes the tools such as SafeAssign (provided as part of Blackboard) to check assignments against published resources AND other students’ work.
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 re-worded easily.
Disability Accommodations
If you have a documented learning disability or other condition that may affect academic performance you should: 1) make sure this documentation is on file with Office of Disability Services (SUB I, Rm. 4205; 993-2474; to determine the accommodations you need; and 2) talk with me to discuss your accommodation needs.
If you are a student with a disability and you need academic accommodations, please see me and contact the Office of Disability Services (ODS) at 993-2474, All academic accommodations must be arranged through the ODS.
If you have a learning or physical difference that may affect your academic work, you will need to furnish appropriate documentation to the Office of Disability Services. If you qualify for accommodation, the ODS staff will give you a form detailing appropriate accommodations for your instructor. In addition to providing your professors with the appropriate form, please take the initiative to discuss accommodation with them at the beginning of the semester and as needed during the term. Because of the range of learning differences, faculty members need to learn from you the most effective ways to assist you. If you have contacted the Office of Disability Services and are waiting to hear from a counselor, please tell me.
Mason Diversity Statement
George Mason University promotes a living and learning environment for outstanding growth and productivity among its students, faculty and staff. Through its curriculum, programs, policies, procedures, services and resources, Mason strives to maintain a quality environment for work, study and personal growth.
An emphasis upon diversity and inclusion throughout the campus community is essential to achieve these goals. Diversity is broadly defined to include such characteristics as, but not limited to, race, ethnicity, gender, religion, age, disability, and sexual orientation. Diversity also entails different viewpoints, philosophies, and perspectives. Attention to these aspects of diversity will help promote a culture of inclusion and belonging, and an environment where diverse opinions, backgrounds and practices have the opportunity to be voiced, heard and respected.
The reflection of Mason’s commitment to diversity and inclusion goes beyond policies and procedures to focus on behavior at the individual, group and organizational level. The implementation of this commitment to diversity and inclusion is found in all settings, including individual work units and groups, student organizations and groups, and classroom settings; it is also found with the delivery of services and activities, including, but not limited to, curriculum, teaching, events, advising, research, service, and community outreach.
Acknowledging that the attainment of diversity and inclusion are dynamic and continuous processes, and that the larger societal setting has an evolving socio-cultural understanding of diversity and inclusion, Mason seeks to continuously improve its environment. To this end, the University promotes continuous monitoring and self-assessment regarding diversity. The aim is to incorporate diversity and inclusion within the philosophies and actions of the individual, group and organization, and to make improvements as needed.
Privacy
Students must use their MasonLive email account to receive important University information, including messages related to this class. See more information.
If you have special circumstances arise that may impede your performance in the class, please let me know. Your situation will be held in the strictest of confidence. It may require informing my TA or administration as needed so that they can also support you as well. Mason offers a great deal of help in many areas, but we cannot help unless we know.
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
- Schedule WILL change as needed to facilitate learning according to personality & makeup of the class
# / Date / Session Topics / Speakers / Reference
1 / 8/ 27 / Course Overview / Howard / Lecture: Howard - Overview v1-2.pptx
Read-aheads:
- Big Data in the US Intel Community 19Feb12 Version.pdf
- What_is_Data_Science.pdf
- emc-data-science-study-wp.pdf
- References in AIT690-001 Overview.pptx
2 / 9/3 / Metadata vs. Meta-Tagging vs. Data / Howard / Howard - So-What, Data vs. Metadata, Big Data Sufficiency
3 / 9/10 / Solving Big Data Problems with Applied Statistics / Forbes / Forbes-Statistics_as_Metadata.pptx
4 / 9/17 / Big Data Intelligence Landscape / Aiken
Mattox / Mattox - Big Data and Massive Analytics3-1.pptx
5 / 9/24 / The Big 3: Intel, Health, Financial / McCormick
Parramore
Quinn / McCormick Pedigree & Lineage in Information Sharing.pptx
Quinn - Leading Sustainable Change.pptx
6 / 10/ 1 / Big, Notional Problem Solving / Sagan / Sagan - We don't know what we're talking about.pptx
7 / 10/ 8 / Big Data Cloud Processing / Curry / Curry-Cloud Lecture (March 3 2013).pptx
-- / 10/15 / No Class
8 / 10/22 / Organizational Values and Decision-Making
Enterprise Architecture Principles & Techniques
Evaluation Criteria / Howard / Howard - Wicked Problems, Learning Organization & Decision Making.pptx
9 / 10/29 / RDBMS’s Journey into Big Data / Foxwell / TBS
10 / 11/5 / Mastering the Bureaucracy / Magee / Magee - Big Data Bureaucracy v2.ppt
11 / 11/12 / Group Project Reviews / Groups / TBS
12 / 11/19 / Securing Data and Privacy / Raines / TBS
13 / 11/26 / Data Quality / Howard / Howard - Big Data Quality.pptx
14 / 12/3 / Case Study Report Day / Team
Howard
Class / TBS
15 / 12/10 / Final Course Reports / TBS