IST359 INTRODUCTION TO DATABASE MANAGEMENT SYSTEMS

Transcription

1 IST359 INTRODUCTION TO DATABASE MANAGEMENT SYSTEMS 1. COURSE DETAILS COURSE (SECTION): IST359 (M005) TERM: Fall 2012 INSTRUCTOR: Yang Wang PHONE: (Office) OFFICE: Hinds OFFICE HOURS: Tu/Th 11:00am 12:00pm HOME PAGE: MEETING TIME: Tu/Th 9:30a - 10:50a LOCATION: Class (Tu): Hinds 117 Lab (Th): Hinds 010 PREREQUISITE: IST352: Information Systems Analysis of Organizational Systems COURSE MATERIALS: Databases Demystified: A Self- Teaching Guide, 2 nd Edition, Oppel ISBN: Murach s SQL Server 2008 for Developers, Syverson & Murach, ISBN: On- line class materials, posted to the learning management system (LMS). COURSE DESCRIPTION: This course examines data structures, file organizations, concepts and principles of database management systems (DBMS); as well as, data analysis, database design, data modeling, database management and database implementation. More specifically, it introduces hierarchical, network and relational data models; entity- relationship modeling; the Structured Query Language (SQL); data normalization; and database design. Using Microsoft s SQL Server DBMSs as implementation vehicles, this course provides hands- on experience in database design and implementation through assignments and lab exercises. Advanced database concepts such as transaction management and concurrency control, distributed databases, multi- tier client/server architectures and Web- based database applications are also introduced. COURSE OBJECTIVES: Like any introductory class, we will be exploring a wide array of topics, rather than a detailed drill- down. It is the primary objective of this class to expose you to the various ideas of databases and database design, with a major focus on the relational model and SQL (Structured Query Language). With that in mind, the outcomes of this course are to: 1. Describe fundamental data and database concepts 2. Compare and contrast the relational database model with other database models Page 1/1

2 3. Explain and use the database development lifecycle 4. Design databases using data modeling and data normalization techniques 5. Create databases using popular database management system products 6. Solve problems by constructing database queries using the Structured Query Language 7. Develop insights into future data management tool and technique trends 8. Recommend and justify strategies for managing data security, privacy, audit/control, fraud detection, backup and recovery 9. Critique the effectiveness of Database Management Systems in computer information systems 2. METHODS OF EVALUATION This table outlines each method by which you will be evaluated in this class. ASSESSMENT QTY NOTES PTS EACH PTS TOTAL Quizzes (Q01- Q11) quizzes total; Lowest grade dropped; Conducted at the start of class on Tuesdays. Labs (L01- L11) labs total; Lowest grade dropped; Conducted Thursdays, due the following Tuesdays by 9am Assignments (A01- A04) 4 All assignments are required Dates: 9/20, 10/11, 11/8, 11/29 Exams (E01, E02) 2 In- class hands- on exams Dates: 10/18, 12/6 GRADE EXPECTATIONS: TOTAL 500 Your grade in this class is based on the quality and accuracy of your submitted work. At any given point in time in this class, your grade can be calculated as the ratio of points you ve earned to points issued, based on the following scale: GRADE EXPECTATION OF THAT GRADE A A: [.93, 1.00] A- : [.90,.93) Your work is outstanding and exceeds expectations. B B+: [.87,.90) B: [.83,.87) B- : [.80,.83) Your work meets expectations; on par with the average student. C C+: [.77,.80) C: [.73,.77) C- : [.70,.73) Your work is adequate but could be better. F D: [.60,.70) F: [0,.60) Your work is inadequate and needs substantial improvement. When it comes to your final grade in the course, the grade you've earned is the grade you get: for example, an 86.9% is a B, not a B+. I will not curve final grades or round up (or down) your final grades, so don t ask. Page 2/2

3 3. COURSE SPECIFIC POLICIES Participation: You are expected to participate in every class. If you fail to contribute to class discussion, use computers for non- class work during class time, or show tardy (up after attendance is taken) you will be marked absent. Attendance: Attendance will be taken randomly throughout the semester. If you arrive to class after attendance is taken, then you are absent. There are no excused absences unless documented by the university. If you have 4 or more absences, your final grade will be dropped one level down the grade scale. (B+ becomes a B, for example) Blackboard: Weekly course content will be posted to Blackboard.This includes textbook readings, additional readings, multimedia (video clips, podcasts), class notes, slides, and labs. Readings and Class Materials: All assigned readings (textbook chapters and online supplemental materials) should be completed prior to the class day where they are posted. I expect you will come to class prepared ready to ask questions and comment on class materials. Submission of work: All work must be submitted as per the instructions to be eligible for credit. Due Dates: All due dates for quizzes, labs, and exams are clearly posted on the final syllabus. All dates are firm so please plan accordingly. No make- ups are allowed. Quizzes: Quizzes will be handed out on Tuesday s at the beginning of class. They are simple timed, closed- book assessments designed to make sure you re keeping pace with your studies. Labs: Lab dates are posted on the course schedule of the syllabus. Labs are always due on or before the following Tuesday at 9:00AM. Labs are graded on a pass (full credit) / fail (half credit) zero (no credit) scale. No late labs will be accepted. Exams: There are 2 hands on lab exams issued in the course. Dates are firm and posted on the final syllabus. Because these are timed, in- class exams, no make- ups are allowed. Assignments: Assignments are instruments which gauge your ability to apply the concepts we ve learned throughout the course. Students get different problem sets selected from a random pool. Assignments are always due on the due date at 9:00AM. No late assignments will be accepted. Late Work: Late work will not be accepted. No exceptions. If it is not on time, it does not count. Group Work: All work is individual effort unless specified otherwise. Academic Integrity: All work should be your own effort. To be safe, do not assist other students without clearing it with me first. Violators of academic integrity will receive an F in the course, and an incident report will be filed with the office of academic integrity. Page 3/3

4 4. UNIVERSITY AND SCHOOL POLICIES ACADEMIC INTEGRITY The academic community of Syracuse University and of the School of Information Studies requires the highest standards of professional ethics and personal integrity from all members of the community. Violations of these standards are violations of a mutual obligation characterized by trust, honesty, and personal honor. As a community, we commit ourselves to standards of academic conduct, impose sanctions against those who violate these standards, and keep appropriate records of violations. The academic integrity statement can be found at: STUDENT WITH DISABILITIES If you believe that you need accommodations for a disability, please contact the Office of Disability Services (ODS), located in Room 309 of 804 University Avenue, or call (315) for an appointment to discuss your needs and the process for requesting accommodations. ODS is responsible for coordinating disability- related accommodations and will issue students with documented disabilities Accommodation Authorization Letters, as appropriate. Since accommodations may require early planning and generally are not provided retroactively, please contact ODS as soon as possible. OWNERSHIP OF STUDENT WORK This course may use course participation and documents created by students for educational purposes. In compliance with the Federal Family Educational Rights and Privacy Act, works in all media produced by students as part of their course participation at Syracuse University may be used for educational purposes, provided that the course syllabus makes clear that such use may occur. It is understood that registration for and continued enrollment in a course where such use of student works is announced constitutes permission by the student. After such a course has been completed, any further use of student works will meet one of the following conditions: (1) the work will be rendered anonymous through the removal of all personal identification of the work s creator/originator(s); or (2) the creator/originator(s) written permission will be secured. As generally accepted practice, honors theses, graduate theses, graduate research projects, dissertations, or other exit projects submitted in partial fulfillment of degree requirements are placed in the library, University Archives, or academic departments for public reference. ATTENDANCE POLICY Regular class attendance is obligatory. An instructor may recommend that a student be dropped from a course for poor achievement due to excessive absence. A student who is dropped after the deadline for dropping courses may be assigned a grade of F. Students who have two unexcused absences during the first two class meetings of the semester may be dropped from the course at the discretion of the instructor. The instructor or the department offering the course will notify the Registrar of this action. However, students should not assume that they have been dropped from a class just because the first two classes were missed. It is ultimately the responsibility of the student to drop a course that they are not planning to attend by the deadline published in the College calendar. For more information about the Syracuse University Attendance Policy, please see the following web site: Page 4/4

5 ADD/DROP PROCESS AND COURSE WITHDRAWAL POLICY It is the responsibility of the students to be fully informed of the college catalog policies regarding course add, drop and withdrawal policies. For more information about the Syracuse University Add/drop Process and Course Withdrawal Policy, please see the following web site: FAITH- BASED OBSERVANCES Syracuse University recognizes the diversity of faiths represented among the campus community and protects the rights of students, faculty, and staff to observe according to these. A more detailed student policy can be found at: Page 5/5

6 5. COURSE CALENDAR The following course calendar lists all reading assignments, lecture topics, labs, and exams. All additional reading and class materials can be accessed from our course Blackboard site. You should plan on reading the materials associated with the learning unit prior to the date posted on the syllabus. All dates are firm, so please use this schedule to plan accordingly. WEEK# DATE CLASS SUBJECT READ CHAPTERS T 8/28 Intro to the course Oppel 1 / Murach 1 H 8/30 Unit 0: The database environment and development process T 9/4 Unit 1: The relational database model Oppel 2 / Murach 11,2 H 9/6 Lab: Intro to a DBMS and the relational model T 9/11 Unit 2: Intro to Structured Query Language (SQL) Oppel 4 / Murach 10,7 H 9/13 Lab: Intro to SQL (DDL and DML) T 9/18 Unit 3: The SQL SELECT statement / Table Joins Oppel 4 / Murach 3,8 H 9/20 Lab: SQL SELECT statement joins more DML T 9/25 Unit 4: Advanced SQL SELECT, aggregates, sub- selects, views Oppel 4 / Murach 4,5,12 H 9/27 Lab: SQL SELECT aggregates, sub- selects, views T 10/2 Unit 5: SQL programming: stored procedures, functions Oppel 8 / Murach 13,14 H 10/4 Lab: SQL programming: stored procedures, functions T 10/9 Unit 6: Data and database administration Oppel 10,11/Murach 16,17 H 10/11 Lab: Transaction management, DBMS security T 10/16 Unit A: Client/Server, distributed DBMSs, review for Exam 1 Oppel 9 H 10/18 Lab: Exam (E01) T 10/23 Unit 7: Database analysis data modeling Oppel 5 H 10/25 Lab: Conceptual modeling in Visio T 10/30 Unit 8: Logical database design, mapping complex data models Oppel 7 H 11/1 Lab: Mapping to the logical model T 11/6 Unit 9: Logical database design - normalization Oppel 6, Murach 9 H 11/8 Lab: Data normalization T 11/13 Unit 10: Data migration Oppel 8 H 11/15 Lab: Data migration T 11/20 No Classes Thanksgiving Break H 11/22 No Classes Thanksgiving Break T 11/27 Unit 11: Physical database design, performance Oppel 8 H 11/29 Lab: Performance tuning T 12/4 Unit B: NoSQL database, review for Exam 2 H 12/6 Lab: Exam 2 (E02) 6. ACKNOWLEDGEMENT The instructor thanks Prof. Michael Fudge Jr. and Prof. Deborah Nosky for generously sharing their course materials. This course is heavily based on past IST359 courses taught by Prof. Fudge and Prof. Nosky. Page 6/6