Syllabus for COMPSCI 445: Information Systems Spring 2025
Admin details
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Prerequisites: COMPSCI 220 (or 230) and COMPSCI 311 and COMPSCI 345
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Credits: 3
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Contacts:
- Instructor: Trek Palmer (palmer@umass.edu)
- TA(s): TBD
- Grader(s): TBD
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Time and Location: Monday and Wednesday @ 4PM in AgEng 119
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Online Resources:
- Canvas: URL TBA
- Piazza: By Invitation (from enrollment)
- Gradescope: URL TBA
Course Objectives
This course is an introduction to the efficient management of large-scale data. Data has become more central to many computer systems and applications. This course will provide a foundation for building, managing, and constructing systems that handle large quantities of complex data. The course will focus on understanding the internals of the data management systems, to give students insight into how to structure the data itself and how to efficiently query large sets of data. As part of this course, you will be exposed to:
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Principles for representing information as structured data
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Query languages for analyzing and manipulating structured data
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Core systems principles that enable efficient computation on large data sets
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Data modeling, SQL, query optimization, concurrency control in relational databases
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Semi-structured data (XML, JSON)
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Distributed data processing paradigms such as MapReduce and Spark
Course Activities
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Lectures
The class will be lectures with the occasional quiz. Please bring your laptops
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Exams
There will be a midterm and a final exam
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Assignments
Homework problems and programming tasks will be given as assignments. Unless otherwise notified, homework will be due at 11:59PM on the Tuesday after it is assigned. Programming tasks will be given in Java and Python. Unless otherwise noted, homework should be submitted via GradeScope.
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Course Text and Materials
Database Management Systems by Ramakrishnan and Gehrke. 3rd edition. Any other materials will be on canvas. Piazza will be used for Q+A and is monitored regularly by the TAs and Instructor
Expectations and Outcomes
A student who completes this course with a grade of C or better will:
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Understand how SQL queries map to relational operators and the cost of those operations
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Recognize the challenges and trade-offs that a DBMS makes when evaluating queries efficiently
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Investigate a query's cost, and know how to optimize it
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Know how DBMS's store and index data efficiently
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Investigate the problems of concurrent data access in a database
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Understand privacy and security of the database and the data it stores
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Topics Covered
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The Relational Data Model and Relational Operators
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Query languages (SQL) and query optimization
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Semi structured data (XML, JSON)
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Record storage
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Indexing
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Concurrency around data
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Big data (TM) processing systems
Requirements
Students will be expected to install and run a DBMS (PostgreSQL) on their laptop. They should be familiar with using command line interfaces and navigating the file system.
Grading
Your final grade will be composed as follows:
- Homework 60%
- Midterm Exam 15%
- Final Exam 25%
The final score [0-100] will be converted to letter grades using the following brackets. There will be no curving.
- A (93-100),
- A- (90-92),
- B+ (87-89),
- B (83-86),
- B- (80-82),
- C+ (77-79),
- C (73-76),
- C- (70-72),
- D+ (67-69),
- D (60-66),
- F (0-59)
TA and instructor availability
The instructor will have office hours in LGRC A246 in the 90 minutes before class meets (modulo walking time to class). Zoom meetings and in-person meetings can be scheduled via email. TA's will have office hours with the intent to cover most (preferably all) work days of the week (Monday through Friday). The instructor and TAs will also monitor piazza, however it is not expected that they be monitoring after 6PM or before 8AM, or on weekends. If you ask a question at midnight on friday, it might not be answered until monday morning. Students and TAs who answer questions in off hours are to be commended.
Make Up or Rescheduling Policies
Late homework submissions must be authorized by the instructor or TA before the deadline expires. They will result in a penalty of 30% of the score except in exceptional circumstances, which will have to be documented. Late submissions due to events that are known in advance must be requested at least one week before the deadline.
Weekly course and examination schedule
The course meets Monday and Wednesday from 4-5:15 in AgEng 119, with the following exceptions:
Exams:
- Midterm: Date and location TBD
- Final: (location TBD)
Academic honesty policy
It is very important in all courses that you be honest in all the work that you complete. In this course you must complete all assignments, quizzes, exams, etc. on your own unless otherwise specified. If you do not, you are doing a disservice to yourself, the instructors for the course, the School of Computer Science, the University of Massachusetts, and your future. We design our courses to provide you the necessary understanding and skill that will make you an excellent computer scientist. Assignments and exams are designed to test your knowledge and understanding of the material. Plagiarism and academic honesty of any sort may seem like an easy way to solve an immediate problem (which it is not), however, it can have a substantial negative impact on your career as a computer science student. There are many computing jobs out there and many more people working hard to get those positions. If you do not know your stuff you will have a very difficult time finding a job. Please take this seriously.
We will carefully review your submissions automatically and manually to verify that "cheating" has not taken place. If you are suspected of plagiarism we will follow an informal path to determine if academic dishonesty has taken place. If you are found guilty you will receive an F for the course and it will go on your permanent record at UMass. This will disrupt your schedule for completing courses and may lead to you not completing your degree in a timely fashion. You should carefully review the
Academic Honesty Policy,
Avoiding Plagiarism, and the
Academic Honesty Flowchart
to understand what academic honesty is, how you can avoid it, and the procedure we will follow if you are under suspicion. In general, you should review all documentation described by the UMass
Academic Honesty Policy and Procedures. The use of ChatGPT and similar AI text generators is prohibited according to the Academic Honesty Policy.
Attendance policy
Attendance is strongly recommended. There is no Zoom option for this class. If you have to miss a class for health reasons, you need to provide evidence to the TA by midday before the class. If you test positive to covid, you will be justified for as long as you need to quarantine (typically 5 days).
Accommodation statement
Accommodations are collaborative efforts between students, faculty, and Disability Services (DS). Students with accommodations approved through DS are responsible for contacting the faculty member in charge of the course prior to or during the first week of the term to discuss accommodations. Students who believe they are eligible for accommodations but who have not yet obtained approval through DS should contact DS immediately. If you are a student with a documented disability and are registered with Disability Services, please contact me immediately to facilitate arranging academic accommodations. Reasonable arrangements will be made in accordance with your accommodations provided by DS in the context of this course.
For midterm and final exams, students who need accommodations are responsible for contacting DS well before the exam. DS will then reach out to the instructor to get a copy of the exam. Failure to contact DS in a timely manner will result in missing the chance to give the exam.
Inclusivity statement
We celebrate the diversity in our community and actively seek to include and listen to voices that are often silenced in the computing world. We welcome all individuals regardless of age, background, citizenship, disability, sex, education, ethnicity, family status, gender, gender identity, geographical origin, language, military experience, political views, race, religion, sexual orientation, socioeconomic status, and work experience.
Names and pronouns
Everyone has the right to be addressed by the name and pronouns that they use for themselves. You can indicate your preferred/chosen first name and pronouns on SPIRE, which appear on class rosters. I am committed to ensuring that I address you with your chosen name and pronouns. Please let me know what name and pronouns I should use for you if they are not on the roster. Please remember: A student’s chosen name and pronouns are to be respected at all times in the classroom.
To learn more read: Intro Handout on Pronouns
Title IX statement
UMass is committed to fostering a safe learning environment by responding promptly and effectively to complaints of all kinds of sexual misconduct. If you have been the victim of sexual violence, gender discrimination, or sexual harassment, the university can provide you with a variety of support resources and accommodations
If you experience or witness sexual misconduct and wish to report the incident, please contact the UMass Amherst Equal Opportunity (EO) Office (413-545-3464 | equalopportunity@admin.umass.edu) to request an intake meeting with EO staff. Members of the CICS community can also contact Erika Lynn Dawson Head, director of diversity and inclusive community development (erikahead@cics.umass.edu | 860-770-4770).
Learning support
There are a range of resources on campus, including: