605.641.81 - Principles of Database Systems

Course Structure

The course materials are divided into modules which can be accessed by clicking Course Modules on the course menu. A module will have several sections including the overview, summary, objectives, lectures, readings, discussion, suggested database project milestones, and assignments. Most modules run for a period of seven (7) days. You should regularly check the Calendar, Course Session Important Dates document and Announcements for assignment due dates as well as office hours sessions.

Course Topics

The course will cover the following topics:

• Introduction to Databases: This module provides an overview of database usages, evolution, technology, and various types of database management systems (DBMSs) and their strengths and weaknesses, and today's common DBMS trends.
• Data Modeling Using the Entity-Relationship (ER) Model, Conceptual Database Design, Part I: This module is the first half of conceptual database using the Entity-Relationship (ER) Model and provides an overview of database design in various phases, the process of data modeling and why it is most important part of a database system lifecycle. The two modules cover the important skills needed for designing databases at the conceptual level using entity relationship diagrams. Common best practice and various designs and implementations based on user requirements are also discussed.
• Data Modeling Using the Entity-Relationship (ER) Model, Conceptual Database Design, Part II: This module is the second half of conceptual database using the Entity-Relationship (ER) Model and provides an overview of database design in various phases, the process of data modeling and why it is most important part of a database system lifecycle. The two modules cover the important skills for designing databases at the conceptual level using entity relationship diagrams. Common best practices and various designs and implementations based on user requirements are also discussed.
• Enhanced Entity-Relationship (EER) Model: This module covers additional data modeling concepts called Enhanced Entity-Relationship (EER) model to support the requirements of representing more complex business data models. With the additional concepts and symbols in the EER model, the traditional ER diagrams can be refined and enriched. This module covers special types of entities called superclass and subclasses; specialization and generalization; and union types using categories. Another diagrammatic technique using Unified Modeling Language (UML) class diagram is also reviewed.
• The Relational Data Model, Relational Database Constraints, and Relational Algebra: This module discusses the terminology, and structural components of relational data models. In addition, relational constraints critical for maintaining data quality and consistency in the relational databases are introduced. Query languages for data retrievals and manipulations on relational databases based on relational algebra are reviewed in detail. Relational algebra demonstrates the concept of original and additional relational operations and outlines the foundations of standard relational database structural query language (SQL) used by Relational Database Management Systems (RDBMSs).
• Functional Dependencies and Normalization for Relational Databases: This module discusses informal design guidelines for relation schema and identifies the problems associated with bad relations, the important concept about functional dependencies between the primary key and other non-key attributes in a relation. In addition, the module covers an overview of normalization involving the most commonly used normal forms, namely, First Normal Form (1NF), Second Normal Form (2NF), Third Normal Form (3NF), and Boyce/Codd Normal Form (BCNF) as well as the steps for converting relations in compliance with most common normal forms.
• Relational Databases Design Algorithms and Further Dependencies and ER- and EER-to-Relational Mapping: This module discusses Relational Databases Design Algorithms and Further Dependencies with different types of dependencies associated with higher normal forms – Fourth Normal Form (4NF) and Fifth Normal Form (5NF). In addition, the module covers logical database design that translates the conceptual data model into a logical data model. This process requires relational mapping to derive relations from a conceptual data model with either entity-relationship model or enhanced entity-relationship model. The goal is to create relations, relationships, and attributes that can be implemented in a RDBMS as a part of database implementation.
• Structured Query Language (SQL), A Standard Relational Database Language, Part I: This module discusses a Standard Relational Database Language – Structured Query Language (SQL). The module covers a brief introduction of the history of SQL and various versions of SQL standards. Then, SQL data definition language is introduced as a basis for creating, altering, and removing database objects such as tables including column definitions as well as table constraints as a part of database implementation using a relational database management system (RDBMS). In addition, SQL data retrieval language notation is examined in detail as the basis for inserting, updating and deleting rows into tables. Many SQL query statements are given to illustrate how to retrieve data from a sample database.
• Structured Query Language (SQL), A Standard Relational Database Language, Part II: This module continues to discuss Structured Query Language (SQL) on various join operations, data manipulation languages, views, dynamic SQL, SQL injection, and the needs for advanced SQL programming languages to support complex business rules. It also covers SQL Persistent Stored Modules as an extension of SQL to include flow of control, condition handling, and statement conditions, cursors and local variables, and assignment of expressions to variables and parameters. The module explains how commercial relational database management systems (RDBMS) support the needs for SQL with the features of modular programming. In addition, this module also provides a brief review of Object-Relational features supported by Object-Relational DBMSs.
• File Structures and Indices: This module provides an overview of a physical database design with important types of file organization, how the data is stored in the files, and how to improve performance on databases from hardware technology, as well as using indices. The module also reviews the important considerations in selecting appropriate columns in a database with appropriate indices to optimize performance with a balance of an index overhead.

Course Goals

To master the important fundamental concepts, theory of data modeling and design, the languages and facilities provided by database management systems, and techniques for implementing relational database systems, and apply the database knowledge to practices in a real world.

Textbooks

Elmasri, Ramez; Navathe, Shamkant. Fundamentals of Database Systems; 7th Edition; The Addison Wesley Publishing Company, Inc., ISBN-10: 0133970779 | ISBN-13: 978-0133970777, Hardcover, Published Date: 06/18/2015.

Textbook information for this course is available online through the appropriate bookstore website: For online courses, search the MBS website at http://ep.jhu.edu/bookstore.

Other Materials & Online Resources

Students should refer to Support & Help on the left menu for a general listing of all the course technical requirements.

Required Software

Students are responsible for obtaining their own relational database management systems (RDBMS, e.g., MySQL, PostgreSQL, MS Access, SQL Server, Oracle, and others) and working on SQL exercises and a database project.

Individual projects will focus on database design and implementation with a proper document. A design document template with instructions will be provided to all students in Module 13: Database Project. The database project including ERD must be done using a CASE tool or diagramming tool, e.g., MySQL Workbench, Visio, Erwin, draw.io and Access. You can find relevant tutorials on using these tools from YouTube or the vendors’ sites.

Students do not need to purchase RDBMS or database design software for this course.  Students can choose free and open-source software like PostgreSQL, MySQL, and MySQL Workbench database design tools.

Student Coursework Requirements

It is expected that the class will take approximately 8-11 hours per week: reading the assigned sections of the texts (approximately 2–3 hours per week) as well as some outside reading, listening to the audio annotated slide presentations (approximately 2 hours per week), and writing assignments (approximately 4–6 hours each of four assignments).

This course will consist of four basic student requirements:

1. Preparation and Participation (Class Discussions) (10% of Final Grade Calculation)

Each student is responsible for carefully reading all assigned material, doing all assigned exercises, and being prepared for discussion. The majority of readings are from the assigned chapters of the required course text. Each student also can conduct a research via internet search for additional references.

Post your initial response to the weekly discussion questions by Saturday evening of that module week. Each module may have one to two topics, and you need to answer all of them. Posting a response to the discussion question is part one of your grade for class discussions (i.e., Timeliness). In order to accommodate students' unexpected work, travel, and other personal issues.  The students have two weeks to post comments on the module starting on the module available date.

Part two of your grade for class discussion is your interaction (i.e., responding to classmate postings with thoughtful responses) with at least one classmate (i.e., Critical Thinking). Just posting your response to a discussion question is not sufficient; I would like to see you to interact with your classmates. Be detailed in your original postings and in your responses to your classmates' postings. Feel free to agree or disagree with your classmates. Please ensure that your postings are civil and constructive.

You will use Preparation and Participation (Blackboard Discussions).docx template (see Blackboard > Syllabus & Course Information) to fill in your discussion comments. Evaluation of preparation and participation are based on contribution to discussions.

Preparation and participation are evaluated by the following grading elements:

• Timeliness (50%)
• Critical Thinking (50%)

Preparation and participation are graded as follows:

100 – 90 = A — Timeliness [regularly participates; all required postings; early in discussion; throughout the discussion]; Critical Thinking [rich in content; full of thoughts, insight, and analysis].

89 – 70 = B — Timeliness [frequently participates; all required postings; some not in time for others to read and respond]; Critical Thinking [substantial information; thought, insight, and analysis has taken place].

69 – 60 = C — Timeliness [infrequently or rarely participates; all required postings; most at the last minute without allowing for response time]; Critical Thinking [generally competent or rudimentary and superficial; information is thin and commonplace].
< 60 = F — Timeliness [infrequently or rarely participates; all required postings; most at the last minute without allowing for response time]; Critical Thinking [generally less competent or rudimentary and superficial; information is thin and commonplace].

2. Assignments (10% of Final Grade Calculation)

Reading assignments as well as readings from the texts and other outside sources will be important sources of material for your four assignments, class project and examinations.

In preparing your written assignments, please put the class assignment number and your name on each assignment, even though it will also be submitted electronically. The purpose of the assignment is to give the students the opportunity to demonstrate their understanding of the course concepts.

Four assignments will be given during a semester. Each assignment is worth at least 20 points. All assignments are due according to the dates in the corresponding module. Students will normally have two weeks to complete an assignment and turn it in via Blackboard module.  The filename for the assignment should include assignment#, your last name, first name (e.g., HW# Lastname, Firstname like HW1 Smith, John).

Late submissions will be reduced by 50% of points of each assignment (no exceptions without prior coordination with the instructors). Therefore, it is strongly recommended that students submit their assignments on time.

3. Database Project (40% of Final Grade Calculation)

A database project will be assigned at the beginning of the course. The class project is evaluated by the following grading elements:

• Student technical understanding of the database project requirements, a sound database design with data validation and constraints, and implementation. (50%)
• Student documentation on project requirements, database design, database schema and implementation (50%)

Midterm Exam (20%) The exam covers Introduction to databases, conceptual database design, Enhanced Entity-Relationship modeling, relational data model, relational database constraints, and relational algebra. The exam is open book and open notes.  The filename for your midterm submission should be “Midterm Lastname, Firstname”.  The file format can be docx or pdf.

Final Exam (20%) The exam covers normalization, ER and EER to relational mapping, SQL for data definition, data manipulation, file structure and indices. The exam is open book and open notes.  The filename for your final submission should be “Final Lastname, Firstname”.  The file format can be docx or pdf.

Exams are graded as follows:

100–90 = A — All parts of question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [rich in content; full of thought, insight, and analysis].

89–70 = B — All parts of the question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [substantial information; thought, insight, and analysis has taken place].

69–60 = C — Majority of parts of the question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [generally competent; information is thin and commonplace]. 
<60 = F — Some parts of the question are addressed; Writing Quality/ Rationale/ Examples/ Outside References [rudimentary and superficial; no analysis or insight displayed].

Grading Policy

Student assignments are due according to the dates in the Calendar and Assignments items in the corresponding modules. The instructor will post grades one week after assignment due dates.

I generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability that may detract from your grade.

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week.

A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work. These criteria apply to both undergraduates and graduate students taking the course.

100–90 = A
89–70 = B
69–60 = C
<60 = F

Final grades will be determined by the following weighting:

Course Evaluation

Course Policies

Artificial intelligence (AI) has become increasingly prevalent in academic environments. It is important to maintain academic integrity when using AI. We need to know the consequences of academic misconduct through the unauthorized use of AI tools, as outlined in the Graduate Academic Misconduct Policy. This includes AI-generated plagiarism.

The goal of this class is to develop your own database knowledge, analytical and critical thinking skills, and abilities. I would like to give you guidelines for acceptable and unacceptable uses of AI tools:

• Weekly Discussion Topics: Yes, you can use generative AI to improve your learning experience. Please include a paragraph at the end of any discussion post or parts of your database projects that used AI, explaining what you used the AI for and what prompts you used to get the results. Failure to do so violates academic honesty policies.
• HW Assignments: No
• Midterm and Final Exams: No
• Database Project: No
  

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.