Revised: September 24, 2014Stevens Institute of Technology

Howe School of Technology ManagementSyllabus

MIS 630 AData and Knowledge Management

Fall 2014 Tuesdays 6:15-8:45PM, BC320Hani SafadiOffice: Babbio 630Tel: 201-216-3391Fax: hsafadi@stevens.edu

Office Hours: Mon 3:30-4:30PM and Tue 4:30-5:30PMAlso by appointmentCourse Room/Web Address: http://www.stevens.edu/moodle

OverviewThis course will This course focuses on the design and management of data in the organization. Data form

the basis of modern business analytics and decision making in organizations. This course will explore all aspects of data, including strategic planning, modeling and representation, semantics, quality, and other related issues.

Prerequisites: Admission requirements for the MIS program.

Course ObjectivesThis course will provide a basis for data and database management in today’s enterprise. It will focus on the relational database model using MySQL. It will present the student with many key concepts relating to database technology, how database technology is being used, and the opportunity to put these concepts to practice. This course will cover database management system (DBMS) concepts, database architecture, data design using entity-relationship (ER) modeling, data storage, file organization, the SQL language, normalization, data integrity, database security, data warehousing, and related emerging technologies.

Additional learning objectives include the development of:

Written and oral communications skills: students will write a project report and present their projects at the end of the course.

Team skills: The final project for the course will involve student teams; an online survey instrument will be used to measure individual contributions to team performance.

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List of Course Outcomes:

After taking this course, students will be able to: Understand the role of data in the competitiveness of organizations Elucidate on the various data management functions and strategies Describe and elucidate on the various types of database schemas Analyze functional dependencies and normalize data Design relational databases Build SQL queries Develop and critique entity-relationship (ER) data models Describe systems theory and layered models. Build information and object-oriented

models Elucidate advanced data modeling issues- e.g., temporal data modeling, meta-data,

etc. Identify and analyze data quality in a business context Develop and evaluate strategic data plans; e.g., Master data management plan and

Enterprise data strategy & models Understand the growing importance and issues associated with data warehousing,

business intelligence and analytics, and big data.

PedagogyThe course will employ lectures, class discussion, in-class individual assignments, individual homeworks and a team project. In the team project, students will analyze a real industrial problem, formulate a model, collect data, solve the problem using one or more of the techniques discussed in class, and interpret the solution for management.

ReadingsRequired Text

Richard T Watson. Data Management. eGreen Press; 6th edition (December 27, 2013).

Available through Amazon http://www.amazon.com/Data-Management-Richard-Watson-ebook/dp/B00E8HS8N2

Book website http://www.richardtwatson.com/dm6e/

Extra Articles

Goodhue, D. L., Quillard, J. A., & Rockart, J. F. (1988). Managing the data resource: a contingency perspective. MIS quarterly, 373-392.

Goodhue, D. L., Wybo, M. D., & Kirsch, L. J. (1992). The impact of data integration on the costs and benefits of information systems. MISQ, 293-311.

Earl, M. J. (1993). Experiences in strategic information systems planning. Mis Quarterly, 1-24.

Morabito, Sack & Bhate (IEEE 2000). The Architectural Continuum and an Introduction to Knowledge Binding.

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AssignmentsINDIVIDUAL HOMEWORKS (5%)There are two individual homeworks each worth 3%. Homeworks are intended to help students apply concepts to practice and develop analytical and communication skills. Assignment analyses and discussions will be a critical part of the course. Good discussions and learning are founded on adequate preparation. All individual homeworks are to be done independently. Homeworks are announced at the end of the class and are due before the next class.

Homework Submission. All homeworks must be submitted through the MIS 630 Moodle web site. Each class assignment should be included in ONE Word file; the file name should include “HWK class #”, your last name, and the date of submission in that order. Do not forget to include and sign the honor code.

TEAM PROJECT REPORT (20%)A major objective of the course is to develop an understanding of designing information system applications correctly, with a focus on the database component. Project teams will consist of five students. Each team will identify the requirements of a specific application, then design and develop a relational database, queries and visual interfaces to support this application. Ideally, I would like you to pick an application that is relevant to your work and experience.

The deliverables include a project presentation in addition to a written report. The project grade is a team grade. In addition, there will be a peer review process through which individual grades may be adjusted. The detailed description of the project will be released in the first month.

TEAM PROJECT PRESENTATION (10%)One of the deliverables for the project is a team oral presentation, which should last twenty minutes and will be worth 10% of your final grade.

Note: Online tutorials on oral presentations are available at: Part 1 - http://vimeo.com/54537755 Part 2 - http://vimeo.com/54537939

TEAM HOMEWORKS (30%)To enhance the learning experience and encourage class participation, there will be six team homeworks at 5% each. Team homeworks are case based and require writing a short report in addition to doing a short presentation in the class.

MIDTERM (35%)There is one in-class closed book midterm. The format of the exam is a mix of multiple choice and problem solving questions to test your understanding of the material presented in the first half of the course.

All assignments are due as noted below. In fairness to others, late work will be penalized 10% per week overdue.

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Ethical Conduct

The following statement is printed in the Stevens Graduate Catalog and applies to all students taking Stevens courses, on and off campus.

“Cheating during in-class tests or take-home examinations or homework is, of course, illegal and immoral. A Graduate Academic Evaluation Board exists to investigate academic improprieties, conduct hearings, and determine any necessary actions. The term ‘academic impropriety’ is meant to include, but is not limited to, cheating on homework, during in-class or take home examinations and plagiarism.“

Consequences of academic impropriety are severe, ranging from receiving an “F” in a course, to a warning from the Dean of the Graduate School, which becomes a part of the permanent student record, to expulsion.

Reference: The Graduate Student Handbook, Academic Year 2003-2004 StevensInstitute of Technology, page 10.

Consistent with the above statements, all homework exercises, tests and exams that are designated as individual assignments MUST contain the following signed statement before they can be accepted for grading. ____________________________________________________________________

I pledge on my honor that I have not given or received any unauthorized assistance on this assignment/examination. I further pledge that I have not copied any material from a book, article, the Internet or any other source except where I have expressly cited the source.

Signature _________________________ Date: _____________

Please note that assignments in this class may be submitted to www.turnitin.com, a web-based anti-plagiarism system, for an evaluation of their originality.

Course/Teacher Evaluation

Continuous improvement can only occur with feedback based on comprehensive and appropriate surveys. Your feedback is an important contributor to decisions to modify course content/pedagogy which is why we strive for 100% class participation in the survey. 

All course teacher evaluations are conducted on-line.  You will receive an e-mail one week prior to the end of the course informing you that the survey site (https://www.stevens.edu/assess) is open along with instructions for accessing the site.  Login using your Campus (email) username and password. This is the same username and password you use for access to Moodle. Simply click on the course that you wish to evaluate and enter the information. All responses are strictly anonymous.  We especially encourage you to clarify your position on any of the questions and give explicit feedbacks on your overall evaluations in the section at the end of the formal survey which allows for written comments.  We ask that you submit your survey prior to end of the examination period.  

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COURSE SCHEDULE

Note: Homework exercises are due the class after they are listed below.

1. Introduction—Tuesday, August 26Overview: ✤ introduction ✤ course logistics ✤ understand the key concepts of data management; ✤ recognize that there are many components of an organization’s memory; ✤ understand the problems with existing data management systems; ✤ realize that successful data management requires an integrated understanding of organizational behavior and information technology.Readings: Watson Ch 1Individual homework for next class:From http://dev.mysql.com/downloads download and install:

MySQL Community Server MySQL Workbench

2. Information, Data, and Knowledge—Tuesday, September 2Overview:✤ understand the importance of information to society and organizations; ✤ be able to describe the various roles of information in organizational change; ✤ be able to distinguish between soft and hard information; ✤ know how managers use information; ✤ be able to describe the characteristics of common information delivery systems; ✤ distinguish the different types of knowledge.Readings: Watson Ch 1 & Ch2Individual homework for next class:2.22, 2.24, 2.26

3. The Single Entity—Tuesday, September 9Overview: ✤ model a single entity; ✤ define a single database; ✤ write queries for a single-table database.Readings: Watson Ch 3Team homework for next class:Team homework 1

4. The One-to-Many Relationship—Tuesday, September 16Overview: ✤ model a one-to-many relationship between two entities; ✤ define a database with a one-to-many relationship; ✤ write queries for a database with a one-to-many relationship.Readings: Watson Ch 4Team homework for next class:Team homework 2

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5. Practice Session—Tuesday, September 23Overview:Practice the single entity and one-many relationships on ClassicModels caseReadings: Team homework for next class:Team homework 3

6. The Many-to-Many Relationship—Tuesday, September 30Overview:✤ model a many-to-many relationship between two entities; ✤ define a database with a many-to-many relationship; ✤ write queries for a database with a many-to-many relationship.Readings: Watson Ch 5Team homework for next class:Team homework 4

7. One-to-One and Recursive Relations—Tuesday, October 7Overview:✤ model one-to-one and recursive relationships; ✤ define a database with one-to-one and recursive relationships; ✤ write queries for a database with one-to-one and recursive relationships.Readings: Watson Ch 6Team homework for the class after midterm (28 October):Team homework 5

8. Midterm Tuesday, October 21No homework for next class

9. Data Modeling —Tuesday, October 28Overview: create a well-formed, high-fidelity data model.Readings: Watson Ch 7Team homework for next class:Team homework 6

10. Normalization Theory—Tuesday, November 4✤ understand the process of normalization; ✤ be able to distinguish between different normal forms; ✤ recognize that different data modeling approaches, while they differ in representation methods, are essentially identical.Readings: Watson Ch 8No homework for next class

11. Advanced SQL—Tuesday, November 11Overview: advanced SQL commands for indexing, stored procedures, triggers, system catalog, and securityReadings: Watson Ch 10

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No homework for next class

12. XML and Data Exchange —Tuesday, November 18Overview:✤ define the purpose of XML; ✤ create an XML schema; ✤ code data in XML format; ✤ create an XML stylesheet; ✤ discuss data management options for XML documents.Readings: Watson Ch 12No homework for next class

13. Advanced Topics: Data Warehousing, Data Mining, Big Data, and NoSQL—Tuesday, November 25Overview:✤ understand the principles of organizational intelligence; ✤ decide whether to use verification or discovery for a given problem; ✤ select the appropriate data analysis technique for a given situation.✤ Understand the paradigm shift in decision-oriented data processing; ✤ Understand the new wave of DB technologyReadings: Watson Ch 13 & 17No homework for next class

14. Project Presentations—Tuesday, December 2Overview: Each team presents their term project: written report plus oral presentation

15. Project Report Due—Saturday, December 20

AcknowledgmentsI would like to thank Prof. Joseph Morabito and Prof. Ted Lappas, the previous instructors of this course at Stevens, who graciously offered me their materials to help me design this course. In addition, I want to thank Prof. Animesh Animesh and Dr. Saeed Akhlaghpour who helped me design my database course I taught at McGill University.

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