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MGSC 7100 SQL Data Fundamentals and Business Intelligence
创建日期：2024-09-04 17:38:45
标签： MGSC 7100
SQL Data Fundamentals and Business Intelligence

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MGSC 7100


SQL Data Fundamentals and Business Intelligence

Course Description:

This course is designed for the Master of Business Analytics as a core course. The effective use of data across firms to deliver fast and intelligent services presents a critical challenge to today’s business leaders. This course is designed to introduce students to basic concepts and techniques in the theory, design, implementation and administration of relational databases. Topics to be covered include, the database design process, MS Access, the Entity Relationship (ER) model, retrieval queries in Structured Query Language (SQL), distributed and client-server databases, and building a database system from scratch. This course focuses on the skills and concepts needed to design and query databases and therefore contribute to companies’ competitive positions.

Course Goals: This course focuses on helping students develop database design and retrieval skills needed to effectively work in a business environment. We will devote a substantial amount of time to mastering technical database skills. The deeper issues surrounding SQL must be addressed through a broad and conceptual approach. Hence, this course will provide a mix of qualitative and quantitative treatments of the subject using lectures, projects, assignments, and exercises.

Student learning Objectives:

As the result of this course, students should be able to:

1.   use relational database management systems; work with entity relationship diagrams,

2.   create, access, read, manage, and modify working databases in Access and SQL Server,

3.   run advanced queries for business intelligence and visualization.

Course Structure:

We will cover 12 modules in Canvas - roughly one module per week. There will be two review sessions. You have to complete reading assignments and watch the lecture videos before coming to class. Your attendance and participation are required and essential.

Course Material:

Required Text                SQL Tutorial – A pdf file will be provided.

Recommended Text       1. Modern Database Management, 12/E (or higher) by Hoffer, Venkataraman,

and Topi 2015 Prentice Hall, ISBN-10: 0133544613.

2. Database Management Systems, 3rd Edition (or higher) by Raghu

Ramakrishnan, Johannes Gehrke, McGraw Hill, ISBN-10: 0072465638

These books are not required, but they are good reference books.

Software                        Microsoft Access,SQL Server Management Studio(SSMS),

andSQL Server 2019 Express. Installation guidelines will be provided. You don’t need to buy any software for this course.

Online Resources datacamp.com ,w3schools.com,Razor SQL for MAC,SQL Fiddle(for testing

queries online) andLinkedIn Learning.

VDI for Tulane Lab https://horizon.tulane.edu/. Click on the right menu: VMware Horizon HTML

Access. Then, login with your Tulane username and password.

Ealuation Procedures and Grading Criteria:

Component

Percentage

Attendance, Participation, Discussions

5+

Quiz and Individual Assignments (Datacamp, LinkedIn, etc.)

15

Team Assignments

15

Exam 1 (Midterm)

15

IT Startup Team Project (2 parts)

25

Exam 2

25

Grade Symbols:

This course and all graduate program courses in the Freeman School use a letter grade system with the following quality point equivalents:

A

=

4.00

C

=

2.00

A-

=

3.67

C-

=

1.67

B+

=

3.33

D+

=

1.33

B

=

3.00

D

=

1.00

B-

=

2.67

D-

=

0.67

C+

=

2.33

F

=

0.00

The quality point total for each course is computed by multiplying the numerical value of the grade received by the course credit hours.

Grading Guidelines:

As approved by the Freeman School faculty, this course follows the recommended grading policy for a class GPA by program. 6000-level courses are expected to have a mean class GPA in the range of 3.00 to 3.33 and 7000-level courses are expected to have a mean class GPA in the range of 3.33 to 3.67. All sections will be pooled into one list and one class GPA will be computed.

Team Assignments and Project:

Skill-building exercises will be assigned throughout the semester. A team of three will submit an assignment. The grade will be shared. Your submission is your team’s submission. You’re supposed to work together. I will not mediate team disputes. I have a right to change team structures.

•    Each assignment must be submitted on time. Late assignments will not be accepted. A grade of zero will be assigned if you do not turn in the assignment.

•    Answers to assignment problems should be submitted though Canvas under the Assignments folder. Please make sure that your submission is successful. No credit will be given to unsuccessful or incomplete submissions.

•    Although exchange of ideas is encouraged, don’t forget that there are some boundaries not to be crossed that are defined by the Tulane Honor Code. Examples of the violations of the Tulane Honor Code include, but are not limited to,

1.   Handing in another team’s work as your own. This constitutes plagiarism.

2.   Providing your work for someone else to hand in as their own. This includes e-mailing your file to someone just so they can “see what you did” .

3.   Explicitly telling another student how to do the assignment in away that hinders their learning of the material.

Additional Notes:

•    Attendance will often betaken. Be on time! No disrupting classmates, no surfing the net, reading  news, updating profiles, ringing phones, or working on that assignment due in another course. We will have a short breakin the middle of every class.

•    You need to create an SQL ecosystem in your machines. This course is designed for Windows PC’s. An installation tutorial will be provided later in the class.

•    Running Windows in parallel or installing Docker for MAC almost always created some problems. No help will be provided to the MAC users.

•    You must have your computer for every class. You will need to use SQL Server during the quizzes and assignments; you maybe asked to turn in your SQL scripts.

•    You will learn SQL by doing cases/questions. Your close attention in-class is essential.

•    The course content: quizzes, assignments, and the project will make you ready for the job market. My recommendation for a successful completion is: study the module, do the scripts, try to create your own challenges, solve practice examples, watch video recordings, and ask questions.

Office Hours Policy:

Office hours will be done virtually throughZoom. It is on a first-come first served basis. If another student (or a team) is waiting inline after 6 minutes, I will ask you to go to the end of the queue.

Recording of Class Sessions:

Sessions will not be recorded. No Zoom access will be provided. If you miss a session, you can catchup through the contents in Canvas.

Tentative Class Schedule (I reserve the rights for possible changes)

Module

Dates

Topic

Assignment/Quiz

1

Aug 20, 22

Introduction: Syllabus, Rules, Policies Introduction to RDBMS and MS Access


2

Aug 27, 29

SQL Server Express and the Management Studio (SSMS), Import from Access to SQL Server


3

Sep 3, 5

Create and Populate Databases


4

Sep 10, 12

Initial Retrieval Queries

Assignment 1

5

Sep 17, 19

Joins

Quiz 1

6

Sep 24, 26

Set Operators and Built-in Functions

Assignment 2


Oct 1, 3

Fall Break


7

Oct 8, 10

Advanced Queries



Oct 15

Oct 17

Review Session

Exam 1 (Midterm)

Assignment 3

8

Oct 22, 24

Team Project: IT Startup Case


9

Oct 29, Oct 31

Stored Procedures

Assignment 4

10

Nov 5, 7

SQL Scripts



Nov 12, 14

Project Guidance, Review Session

Assignment 5


Nov 19, 21

SQL Practice in Industry

Quiz 2

11

Nov 26, 28

Thanksgiving Break


12

Dec 3

Dec 5

Practice & Course Wrap-up

Exam 2

Team Project

Canvas Use and Requirements:

Modules will be posted on Canvas prior to your class. Reviewing modules before the class is your responsibility. Keep in mind that Canvas displays the average grade for assignments based on the information it has. However, these averages may not accurately reflect the true average.

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