EECS 447 (3 credit hours): Introduction to Database Systems -- Fall 2025
Meets in person, Monday, Wednesday, Friday, 1:00 pm - 1:50 pm,
LEAP2 2425
Teaching website: people.eecs.ku.edu/~saiedian/Teaching
Professor Hossein Saiedian
Office: Eaton Hall 3012
Telephone: 785-864-8812
E-Mail: saiedian AT ku.edu
WWW: people.eecs.ku.edu/~saiedian
Office hours: Monday and Wednesdays, 2:00-3:00 PM (and by appointment)
EECS 447 Introduction to the concept of databases and their operations. Basic concepts, database architectures, storage structures and indexing, data structures: hierarchical, network, and relational database organizations. Database design and normalization: ER model, candidates keys, functional dependencies, normal forms, decomposition. Emphasis on relational databases, relational algebra, and SQL. Introduction to views, transactions, and database access control. Introduction to database security, big data, NoSQL, CAP theorem, key-value stores. Prerequisite: Upper-level EECS eligibility or departmental consent.
Database concepts mastery. Understand and apply key database concepts, including conceptual modeling, data models, relational schemas, and normalization techniques, to create scalable database systems.
SQL query proficiency. Develop proficiency in writing and optimizing SQL queries for data manipulation, retrieval, and reporting, ensuring high performance and data accuracy.
Database security and transactions. Understand best practices for database security, backup, recovery, and transaction management to protect data integrity, maintain system reliability, and ensure consistent, secure handling of data operations.
Databases in big data and cloud. Understand the role of databases in big data ecosystems and cloud platforms, and apply database management techniques to support data science applications and large-scale data processing.
Project management and teamwork.
Learn essential project management skills like planning,
scheduling, and communication. Work effectively in team
and contribute to successful database projects.
The following are a couple of the most popular database systems
textbooks:
Recommended textbooks
A. Elmasri, H. Navathe,
Fundamentals of Database Systems, 7th edition,
Pearson, 2016
The textbook's
table of contents.
A. Silberschatz, H. Korth, S. Sudarshan
Database System Concepts, 7th edition
McGraw-Hill, 2020
The textbook's
table of contents.
Students are responsible for lecture slides, topics discussed in the classroom, reading assignments, as well as items distributed during the classroom sessions. Important reading materials as well as lecture slides will be placed on Canvas:
Lecture notes (Canvas)
Readings (Canvas)
Project resources (Canvas)
Evaluation criteria. Students will be evaluated as follows:
Assignments: 10%Term project. The term project in this course is team-based, with teams consisting of 5--6 members. During class discussions, we’ll cover project requirements, and detailed descriptions of project components will be available on Canvas. Teams will need to choose a computing platform, and all projects must be implemented in a SQL-based relational database. Finally, project artifacts should be placed on GitHub for easy collaboration, version control, and grading.
Exams and quizzes Exams and quizzes will be conducted in-person, in the classroom, and will be closed book and notes, administered through Canvas. Always bring a device that can connect to Canvas for taking exams or quizzes. During an exam or quiz, no other devices should be used, and no other files or apps should be open except for Canvas. If using a browser to connect to Canvas, only one tab should be open.
Grading scale The final course grade will be assigned based on the total points earned, using the following standard scale:
• A (Excellent): 90–100%
• B (Good): 80–89%
• C (Satisfactory): 70–79%
• D (Poor): 60–69%
• F (Failing): below 60%
All written work must be typeset and submitted on Canvas. Please note that typesetting means handwritten work will not be accepted.
iClicker is an interactive classroom response system that
allows students to engage actively by answering questions
and participating in polls. The University of Kansas has
secured an iClicker subscription for classroom use, and the
EECS department is incorporating this system into its courses
to boost student engagement. Participation in the iClicker
community is mandatory for this course.
Responding to iClicker notifications when not physically
present in the classroom is strictly prohibited.
It constitutes a deliberate act of academic dishonesty
and a direct violation of the University of Kansas code of
conduct. Logging attendance or submitting responses while
absent undermines the integrity of our learning environment
and disrespects both the instructor and fellow students who
are fully participating. Your presence in the classroom is
not just expected—it is essential.
Classroom engagement via
Week 1: August 18, 20, 22
Course syllabus and course overview
-- Striving for successful teams
Introduction to database management system
-- Why a database system?
-- Three-schema architecture and data independence
-- Database languages
Week 2: August 25, 27, 29
Requirements engineering
-- Why modeling, domain modeling
Conceptual modeling
-- Data entities, relationships
Get acquainted with your team members and discuss team member roles
Week 3: September 1, 3, 5
Conceptual modeling (continued)
Introduction to the relational model
Week 4: September 8, 10, 12
Mini-Exam 1 (intro topics & conceptual modeling)
Relational data model
Due: Vision statement and project plan
Week 5: September 15, 17, 19
Manipulating relational databases
-- Integrity constraints
-- Relational algebra expressions
Week 6: September 22, 24, 26
Relational algebra (continued)
Building logical models from ER diagrams
Introduction to SQL
-- SQL structure & constructs
Due: Project requirements
Week 7: September 29, October 1, 3
Introductory SQL (continued)
Mini-Exam 2 (relational model)
Week 8: October 6, 8, 10
Intermediate SQL
Due: Project conceptual model
Week 9: October 13, 15, 17
Intermediate SQL (continued)
Due: Logical relational model
Week 10: October 20, 22, 24
Relational database design
-- Definition of good relations and
functional dependencies
Mini-Exam 3 (SQL)
Week 11: October 27, 29, 31
Relational database design (continued)
-- Definition of normal forms with examples
Week 12: November 3, 5, 7
Relational database design (continued)
-- Decomposition techniques (lossless, preserving
FDs)
Week 13: November 10, 12, 14
Database transactions and ACID properties
Concurrency control and recovery algorithms
Due: Physical design + data population
Mini-Exam 4 (database design)
Week 14: November 17, 19, 21
Database security and privileges
Database architectures: centralized, distributed, cloud
Due: Project demonstrations
Week 15: November 24, 26, 28
Complex data types and big data
Data lifecycle
Non-SQL databases
November 26, 28: Thanksgiving break
Week 15: December 1, 3, 5
Data analytics and data science
Course review
Friday December 5: Stop day
Week 16: December 8
December 8: Comprehensive Final Exam @ 10:30-1:00pm
Date | Event/Assessment |
---|---|
September 1 (Mon) | Labor Day – No class |
September 6 (Fri) | Mini-Exam 1 – Intro topics & conceptual modeling |
October 4 (Fri) | Mini-Exam 2 – Relational model |
October 11–14 (Sat–Tue) | Fall Break – No class on Mon, Oct 13 |
October 24 (Fri) | Mini-Exam 3 – SQL |
November 14 (Wed) | Mini-Exam 4 – Relational design |
November 26, 28 (Wed, Fri) | Thanksgiving Break – No class |
December 5 (Fri) | Stop Day – No class |
December 8 (Mon) | Final Comprehensive Exam – 1:30 PM–4:00 PM |
Attendance expectation. Regular attendance is essential for
success in this course and its lab components. Attendance will be
be recorded throughout the semester via iClicker. Three or more unexcused
absences will result in a one-letter grade reduction in the
final course grade, reflected when grades are posted at the
end of the term.
Excused absence requests. Requests for excused absences must be
submitted in advance and approved by the instructor, except in
cases of emergency. For emergencies, notify the instructor as
soon as possible following the absence. Supporting documentation
must be included with the request.
Examples of excusable absences are listed below.
Responsibility for missed work.
Students who miss class without a valid excuse are responsible
for obtaining missed materials. The instructor or the TAs
will not provide individual makeup lectures or one-on-one
instruction. It is the student's responsibility to stay informed
about course content and course updates.
Late-work, makeup policy.
Late work will not be accepted under any circumstances. Make-up
options for labs, quizzes, and exams are unavailable except
in cases of excused and verified absences.
Exceptions will be made for
excusable absences.
Timing of make-up assessments.
Make-up quizzes and exams for excused absences must be completed
before the class session in which the quiz or exam content will
be reviewed or its answer key released. Make-up labs must be
completed within one week of the excused absence.
Make-up assessment integrity statement.
ff granted permission to take a quiz or exam at a later time
due to an officially excused absence, the student must affirm
the following: “I acknowledge that I have been granted
the opportunity to complete this assessment as a result of an
officially excused absence from its original administration. I
hereby affirm—without reservation—that I have not sought,
received, or accessed any information regarding the content,
structure, or subject matter of this quiz or exam from
any individual who previously completed it. This includes,
but is not limited to, verbal conversations, written notes,
online discussions, messaging apps, shared files, or any
other form of communication. I understand that violating
this pledge constitutes academic misconduct and will result
in immediate disciplinary action, including a failing grade
on the assessment and referral to the School of Engineering
disciplinary committees.”
Technical problems. If you experience technical problems
with your EECS account or the EECS servers or the lab
equipment, please submit a support request help at:
https://tsc.ku.edu/request-support-engineering-tsc.
Inside classroom policy.
Students are expected to come to the class on time, be
attentive and engaged, conduct themselves professionally, and
avoid anything that could cause a distraction or detrimental
either for other students learning or for the instructor's
presentations. Profanity and swearing is not allowed.
Students are expected to actively participate in all classroom
presentations and discussions, ask questions, and regularly
make contributions such as offering comments, responding with
good answers, and providing feedback.
Canvas announcements.
Announcements is a Canvas tool to post important
information and updates to all members of a course. It is your
responsibility to regularly check your Canvas account for such
announcements (students may also receive an email notification
when a new announcement is posted).
Email communications
E-mail communication is fast, flexible, and effective. You have an
@ku.edu email account and you are expected to regularly check
it. Important information may also be communicated via email.
You are a student registered in a course offered by
the School of Engineering at the University of Kansas, a top regional
and a nationally ranked institution. Your communications, especially
written communications (composition, grammar, spelling, punctuation,
etc), should reflect that status.
Please follow these email guidelines and etiquettes.
Send text-only emails in text-only format. All classroom
assignments, labs, or projects should be typeset and submitted
on Canvas.
Other documents (e.g., documents for an excusable
absence) shoud be emailed in PDF or a well-known image format (e.g.,
JPG or PNG). See the Guidelines for submitting electronic documents.
Grade and absence clarification or correction.
If you believe your grades on an assignment, lab, quiz, or
exam are incorrect, you should formally submit a grade appeal
via email to the instructor within one week of receiving the
graded work. Similarly, if you have an excusable absence, and
you did not provide documentation prior to the absence, submit
relevant documentation within one week of the absence. Failure
to address concerns within these timeframes will result in
the decision becoming final. This timeline ensures timely
resolution and fairness for all parties involved.
Cell phone policy. Cell phones
should be turned off before coming to the classroom.
Cell phone use for the purposes of texting, email
or other social media should be avoided. Earphones
for music are OK during lab work or individualized
problem solving, as long as the volume allows you to
hear announcements. Also cell phone or other cameras
may be used to photograph projects and the whiteboard
but avoid shots that include the presenter or other students. Laptop/electronic device policy. The use of laptops,
tablets or similar devices is common for taking notes
but turn off audio and avoid any possible uses
that could cause distraction for others
(e.g., Web surfing or social media visits).
Incomplete grade policy. "Incomplete
(I) grades are used to note, temporarily, that students
have been unable to complete a portion of the required
course work during that semester due to circumstances
beyond their control. Incomplete work must be completed
and assigned an A-F or S/U grade within the time
period prescribed by the course instructor. After
one calendar year from the original grade due date,
an Incomplete (I) grade will automatically convert
to a grade of F or U, or the lapsed grade assigned by
the course instructor."
Also please review change of grade policy
here and
here.
Accommodations for students with disabilities.
The University of Kansas is committed to providing
equal opportunity for participation in all programs,
services and activities. Requests for special
accommodations may be made thru the
KU Student Access Services.
The Provost's freedom of expression statement .
"Our IRISE values will guide us and our students as we all
engage with each other in respectful freedom of expression.
In a setting as diverse as KU, we will inevitably encounter
ideas, opinions and philosophies that are different than
our own and which some personally find uncomfortable or
offensive. To be clear, threats, incitement of violence and
targeted harassment are not protected speech under the First
Amendment. Offensive speech, although it can be painful, is
generally considered protected speech. We need to strongly
encourage and facilitate civil and respectful discussion and
interaction. We simply must not inhibit or penalize expression
protected by the First Amendment."
KU's diversity policy statement.
"As a premier international research university, the University of
Kansas is committed to an open, diverse and inclusive learning
and working environment that nurtures the growth and development
of all. KU holds steadfast in the belief that an array of
values, interests, experiences, and intellectual and cultural
viewpoints enrich learning and our workplace. The promotion
of and support for a diverse and inclusive community of mutual
respect require the engagement of the entire university..."
Please also see:
KU's statement on diversity and inclusion.
KU's nondiscrimination, equal opportunity.
"The University of Kansas prohibits discrimination on the
basis of race, color, ethnicity, religion, sex, national
origin, age, ancestry, disability, status as a veteran,
sexual orientation, marital status, parental status, gender
identity, gender expression, and genetic information in the
University's programs and activities."
Please also see:
KU's statement on nondiscrimination and on
racial and ethnic harassment policy.
KU's sexual harassment policy.
"The University of Kansas prohibits sexual harassment and
is committed to preventing, correcting, and disciplining
incidents of unlawful harassment, including sexual harassment
and sexual assault."
Please also see
KU's statement on sexual harassment.
KU's mandatory reporter statement.
"The University of Kansas has decided that all employees, with
few exceptions, are responsible employees or mandatory reporters
who must report incidents of discrimination, harassment, and
sexual violence that they learn of in their employment at KU
to the Office of Civil Rights and Title IX. This includes
faculty members. As such, if you share information about
discrimination, harassment, or sexual violence with me, I
will have to relay that information to the Office of Civil
Rights and Title IX. I truly value your trust in me to share
that information and I want to be upfront about my requirement
as a mandatory reporter. If you are interested in contacting
KU’s confidential resources (those who do not have to make
disclosures to OCRTIX), there are: the Care Coordinator,
Melissa Foree; CAPS therapists; Watkins Health Care Providers;
and the Ombuds Office."
Please see
KU's statement on mandatory reporting.
KU's commercial note-taking ventures.
"Pursuant to the University of Kansas’ Policy on Commercial
Note-Taking Ventures, commercial note-taking is not permitted
in this course. Lecture notes and course
materials may be taken for personal use, for the purpose of
mastering the course material, and may not be sold to any person
or entity in any form. Any student engaged in or contributing
to the commercial exchange of notes or course materials will be
subject to discipline, including academic misconduct charges,
in accordance with University policy. Please note: note-taking
provided by a student volunteer for a student with a disability,
as a reasonable accommodation under the ADA, is not the same
as commercial note-taking and is not covered under this policy."
Please see
KU's statement on commercial note-taking.
Concealed handguns.
"Individuals who choose to carry concealed handguns are solely responsible to do
so in a safe and secure manner in strict conformity with state and federal laws
and KU weapons policy. Safety measures outlined in the KU weapons policy
specify that a concealed handgun:
Generative AI tools—such as ChatGPT, GitHub Copilot, Gemini ,
and others—can be valuable resources for learning. When used
appropriately, they may assist in brainstorming, exploring
ideas, and refining drafts. However, they must never
replace your own intellectual work.
These tools are akin to writing center consultants, lab
aides: they can guide and support but must not generate final
submissions. Submitting content primarily generated by
AI is a violation of academic integrity, comparable
to submitting work completed by someone else.
Unless explicitly permitted, all coursework must reflect
your original understanding, reasoning, and
expression. If you use AI tools at any stage of an
assignment, you are required to disclose that use via a brief
reflection, which must include:
Attendance, late work, and makeup policies
Examples of excusable absences include:
Common policies
LLM and generative AI tools
Failure to disclose use of AI tools or submitting AI-generated work as your own will be treated as academic misconduct. Minimum consequences include a zero on the assignment. Depending on severity, further penalties may include failure in the course and formal referral to the School of Engineering disciplinary committee.
This course is designed to build your skills—not evaluate the performance of generative tools. Authentic engagement with course challenges leads to meaningful growth. Overreliance on AI undermines both your learning and the integrity of our academic community.
Intellectual honesty is not optional—it defines your
identity as an engineer, a scholar, and a professional.
.
The University of Kansas, the School of Engineering, and the Department of Electrical Engineering & Computer Science (EECS) maintain a zero-tolerance policy toward academic dishonesty and misconduct. All students enrolled in this course are expected to uphold the highest standards of integrity and professionalism in their academic work.
Academic dishonesty includes, but is not limited to:
The minimum consequence for an academic integrity violation is a zero on the item in question (e.g., lab, assignment, quiz, or exam). Depending on severity, penalties may include a grade reduction, a failing grade for the course, and formal referral to the School of Engineering's disciplinary committee for further review and sanctions.
All definitions and procedures follow institutional policy and guidance outlined by the University of Kansas Office of Student Affairs and the EECS Department. Students are expected to be familiar with and adhere to these standards at all times.
Please also see KU's academic misconduct policy
LMS features. During exams or quizzes, only one device should be used, with solely the Canvas app or a single browser tab for Canvas open. Having any other app or file open will be considered a violation of academic integrity. To further facilitate academic integrity, the following features of Canvas will be utilized:
Code of student rights and responsibility: Code of Student Rights and Responsibilities
Keep in mind that when a person signs up to participate by either uploading, and/or downloading, and/or using posted material from these sites, the “terms of service” that are agreed to do not protect the person when KU and/or the School of Engineering decide to conduct investigations related to academic misconduct (e.g., plagiarism and/or cheating).
In fact, EdTech services, like Chegg, retain contact information of students who use their services and will release that information, which is traceable, upon request. Using these services constitutes academic misconduct, which is not tolerated in the School of Engineering. It violates Article 3r, Section 6 of its Rules & Regulations, and may lead to grades of F in compromised course(s), transcript citations of academic misconduct, and expulsion from the University of Kansas.
If unsure about assignments, it is important that students use the allowable available resources, such as instructor office hours, graduate teaching assistants, and/or tutoring. The School of Engineering wants students to be successful; cheating is not the way to attain that success."
The ACM's and IEEE's code of ethics. As IT and computing professionals and/or as engineers, you should be familiar with the ACM's (IT, computing) and IEEE (engineering) codes of ethics and apply them during your academic and professional careers. These are lifelong commitments to integrity and professional conduct.
We will review these during the first class session, but you are strongly encouraged to review these codes in detail:
From the ACM's preamble: Computing professionals' actions change the world. To act responsibly, they should reflect upon the wider impacts of their work, consistently supporting the public good. The ACM Code of Ethics and Professional Conduct ("the Code") expresses the conscience of the profession.
From the IEEE's preamble: We, the members of the IEEE, in recognition of the importance of our technologies in affecting the quality of life throughout the world, and in accepting a personal obligation to our profession, its members and the communities we serve, do hereby commit ourselves to the highest ethical and professional conduct and agree.
Professor Hossein Saiedian
Electrical Engineering & Computer Science
Eaton Hall 3012
University of Kansas
1520 W 15th St
Lawrence, KS 66045-7621
+1 785 864-8812
saiedian at eecs.ku.edu