CIS 4400 Data Warehousing for Analytics Syllabus

Zicklin School of Business – Baruch College
City University of New York

CIS 4400 Data Warehousing for Analytics

DRAFT Syllabus

Fall 2025 Section CMWA – Monday/Wednesday 10:45 am – 12:00 pm – Hybrid

Professor Dr. Richard Holowczak
Phone: 646-312-3371
Office Hours: Monday and Wednesday, 9:30am – 10:30am, or by appointment
E-Mail: [email protected] (Preferred)
Please put the following in the Subject line for any e-mail to me: CIS 4400 followed by the specific subject of your e-mail.
Instructional Modality Section CMWA will be Hybrid.
Monday Lectures will be In-Person on campus.
Wednesday Lectures will be On-Line Synchronous.
Course Objectives This advanced course will provide students with an in-depth understanding of the design and implementation of database warehousing and analytics database systems.
Specific topics include data warehouse modeling and architecture, the ETL process, administration, security, column-store, streaming and NoSQL databases, and complex event processing. Students develop a complete data warehouse system including implementation of a business intelligence suite.

Topics Include:

  • Review of Relational Design and Analytical SQL
  • Data Warehouse modeling and Architecture
  • Extraction, Transformation and Loading (ETL and ELT)
  • Query Processing and Optimization
  • Data Warehouse Technical Architectures
  • NoSQL Databases
  • Big Data Processing: Hadoop/Spark
  • Commercial and Open Source BI Tools
  • BI Application Design and Development
Learning Goals Upon successful completion of this course, students will be able to:

  • Translate business needs and drivers into IT requirements for business intelligence systems.
  • Use the supporting technologies and data models for business intelligence including the process of and techniques for transforming business transaction data into appropriate analytic structures
  • Explore state-of-the-art solutions for building and managing large data warehouse systems
  • Discuss appropriate modeling approaches for a variety of industry specific requirements such as healthcare, banking, insurance, on-line advertising, and others.
  • Develop a complete business intelligence system in a team setting using all of the tools and techniques presented during the course.

Upon successful completion of this course, students will have advanced skills to effectively design, develop, implement and manage medium to large-scale data warehouse systems.

  • Technology Literacy: Students will master technologies used to develop and deploy data warehouses and analytics systems.
  • Knowledge Integration: Students will be able to analyze business requirements across multiple industries and address these requirements with appropriate data warehousing and analytics technologies.
  • Written communication: Students will analyze a business and develop and write a business analytics proposal that will be implemented during the semester.
  • Oral communication: Students will present their business analytics solution
  • Teamwork and Leadership: Students will work in groups to analyze a business and develop and write a business analytics proposal that will be implemented during the semester.
  • Ethical Awareness: Students will discuss issues of privacy, customer data collection and management, energy use by data centers, and ethical concerns when collecting, analyzing and presenting analytical data.
Prerequisites CIS 3400 Database Management Systems AND ZICK OR ZKTP Student Group
Students must have a firm understanding of topics covered in CIS 3400 including the relational model, E-R diagraming, normalization and SQL. Students who received less than a “B” in CIS 3400, or students who have taken CIS 3400 more than 1 year ago should consult with the instructor prior to continuing on in CIS 4400.
Textbooks / Materials / Resources
Course Content In addition to required reading in the textbook, there will be 3 to 4 homework assignments including implementations using Google Cloud Platform, Google BigQuery, Github, dbt and Tableau.
Examinations will consist of a Mid-term exam and a Final exam (both in-person).
Students are expected to spend a significant amount of time outside the classroom meeting in groups and learning to use Google BigQuery, dbt and Tableau.
Group Project A semester-long Group Project will provide students the experience of developing a working data warehouse using a commercial database management system and development tools. Students will be assigned to a group and will submit project milestones throughout the semester:
– Milestone 1 (10%): Group Project Proposal
– Milestone 2 (10%): Documenting KPIs and Data Sources
– Milestone 3 (20%): Dimensional Model
– Milestone 4 (10%): Technology selection (ETL Tools and target DBMS)
– Milestone 5 (20%): ETL Programming
– Milestone 6 (30%): Analytics, Visualization and Final Project Report
Each milestone is graded according to: On-Time Submission, overall completeness and amount of revisions required to complete.
Grading
  • Mid term Exam
    		•  20%
  • Final Exam
    		• 25%
  • Homework (average)
    		• 20%
  • Data Warehouse Group Project
    		•  35%

    This is a tentative grading schedule and is subject to change. Homework assignments are due at the beginning of the class period. Late assignments will be graded down 5% per day late.
    Credit will not be given for assignments submitted after homework solutions are discussed.
    There will be no extra credit assignments.

    Final Letter Grades Letter grades are calculated according to the Official Grading System of Baruch College. The instructor reserves the right to curve the scale when computing final grades, if deemed necessary.

    Grade Grade Point Equivalent Score
    A 4.0 93 – 100
    A- 3.7 90 – 92.9
    B+ 3.3 87.1 – 89.9
    B 3.0 83 – 87
    B- 2.7 80 – 82.9
    C+ 2.3 77.1 – 79.9
    C 2.0 73 – 77
    C- 1.7 70 – 72.9
    D+ 1.3 67.1 – 69.9
    D 1.0 60 – 67
    F 0.0 below 60
    Grade Distribution The Paul H. Chook Department of Information Systems and Statistics expects to see a reasonable distribution of grades in each class. For undergraduate courses this distribution is:

    A and A- 30% or less
    B+, B & B- 30% or less
    C+, C & C- 30% or less
    D & F any students who have earned these grades

    Due to these guidelines, the professor reserves the right to curve final letter grades up or down.
    Topics / Schedule (Tentative) The following table gives a tentative lecture schedule for the course.

    WeekTopicsChapter in BI Guidebook
    1 Course Introduction and Review of E-R Model
    Relational Model and SQL    		 Chapter 8
    Notes/Handouts
    2 Data Warehouse Project Planning Chapters 1, 2, 3
    3 Data Warehouse Architecture
    		 Chapters 4, 5, 6 and 7
    4 Dimensional Modeling Chapters 9 and 10
    5 Dimensional Modeling (Continued) Chapters 9 and 10
    6 Extract-Transform-Load (ETL) and ELT 11 and 12
    7 Extract-Transform-Load (ETL) and ELT (Cont.) 11 and 12
    8 Extract-Transform-Load(ETL) and ELT (Cont.) 11 and 12
    9 Review for Mid Term Exam
    Mid term exam (Estimate) 10/27/2025
    10 Data Warehouse Technical Architecture Chapter 7
    11 Scalability: Clustering and Distributed DBMS
    CAP Theorem    		 Notes/Handouts
    12 NoSQL Databases Notes/Handouts
    13 Big Data Processing Architectures
    HADOOP and Spark    		 Notes/Handouts
    14 Web Applications Integration, XML and semi-structured data analytics Notes/Handouts
    15 BI Application Design and Development 13 and 14
    16 Final Exam Review
    Final Exam to be held during 2 hour final exam period.

    Please note that this schedule is subject to change. Students are expected to come to class prepared and ready to participate. The associated chapters should be read ahead of time.

    Academic Integrity Statement I fully support Baruch College’s policy on Academic Honesty, which states, in part:
    “Academic dishonesty is unacceptable and will not be tolerated. Cheating, forgery, plagiarism and collusion in dishonest acts undermine the college’s educational mission and the students’ personal and intellectual growth. Baruch students are expected to bear individual responsibility for their work, to learn the rules and definitions that underlie the practice of academic integrity, and to uphold its ideals. Ignorance of the rules is not an acceptable excuse for disobeying them. Any student who attempts to compromise or devalue the academic process will be sanctioned.”

    Academic sanctions in this class will range from an F on the assignment to an F in this course. A report of suspected academic dishonesty will be sent to the Office of the Dean of Students. Additional information and definitions of Academic Honesty can be found at https://provost.baruch.cuny.edu/teaching-learning-student-success/academic_honesty/

    The use of AI (ChatGPT and similar) for coursework and assignments is strictly prohibited. This includes, but is not limited to, the use of AI-generated text, speech, programming code or images, as well as the use of AI tools or software to complete any portion of a project, assignment or exam. Any use of AI tools to complete your work or a portion of your work will result in a grade of 0.

    Baruch College Counseling Center At Baruch, we acknowledge that as a student, you are balancing many demands. During the semester, if you start to experience personal difficulties or stressors that are interfering with your academic performance or day to day functioning, please consider seeking free and confidential support at the Baruch College Counseling Center. For more information or to make an appointment, please visit their website at studentaffairs.baruch.cuny.edu/counseling/ or call 646-312-2155. If it is outside of business hours (Monday-Friday 9-5pm) and you need immediate assistance, please call 1-888-NYC-WELL (888-692-9355). If you are concerned about one of your classmates, please share that concern by filling out a Campus Intervention Team form at studentaffairs.baruch.cuny.edu/campus-intervention-team.
    Students with Disabilities Students with disabilities may receive assistance and accommodation of various sorts to enable them to participate fully in courses at Baruch. To establish the accommodations appropriate for each student, please alert me to your needs and contact the Office of Services for Students with Disabilities, part of the Division of Student Development and Counseling. For more information contact the Director of this office in NVC 2-271 or at (646) 312 4590.
    Additional Notes
    • No makeups will be given for missed quizzes or exams.
    • The instructor retains all midterm and final exams.
    • The final exam must be taken by all students in the time slot posted in the college bulletin.

      Please make your business and travel plans to accommodate this schedule.

    • Grades will not be given out via e-mail under any circumstances.
    • If you miss class, it is your responsibility to find out about any announcements or assignments you may have missed.
    • Cell phones etc. should be turned off or muted during class. No cell phones permitted during exams.
    • In general, the time to let me know about any problems or issues concerning missing class, long term illnesses, job related problems, academic probation, etc. is before you have missed a week or two of classes.
    • All homework assignments are to be done individually. Students handing in similar work will both receive a 0 and face disciplinary actions.
    • The instructor reserves the right to give unannounced quizzes if it appears students are not putting the time in to prepare for class.
    • Students are expected to spend time outside of the classroom learning to use BigQuery, dbt and Tableau.
    • Other helpful software tools to have include a decent word processor (e.g., MS Word) and a drawing tool. MS PowerPoint or Visio can be used for the latter.
    • Assignments will be turned in to BrightSpace. Please carefully follow all formatting guidelines and file naming patterns.
    • Make backups of all of your work! This includes any assignment and project materials you produce. I reserve the right to ask you to resubmit any assignment at any time.
    • You may wish to join a Student Club at Baruch:
      – Student chapter of Association for Information Systems   https://baruchais.com/
      – ISACA Cybersecurity Club    https://linktr.ee/isgbaruch
      – Machine Learning and Data Science (MLDS) Club    https://linktr.ee/baruchmlds
      – ColorStack at Baruch https://linktr.ee/colorstackbaruch
      – Girls who code  https://forms.gle/ycVzWZKA9hdWP1zT6
      – Baruch Full Stack (BFS)  https://forms.gle/HTXztE8FqVh3VSJ9A
    Important Dates for this Course Baruch Academic Calendar for Fall 2025

    August 26      Tuesday    - First day of the Fall 2025 Semester
August 27      Wednesday  - First day of class for CIS 4400 (on-line)
August 30-31              - No Classes
September 1    Monday     - No Classes
September 22   Monday     - No Classes
September 23   Tuesday    - No Classes
September 24   Wednesday  - No Classes
October 1      Wednesday  - No Classes
October 2      Thursday   - No Classes
October 13     Monday     - No Classes
October 14     Tuesday    - Follows a Monday Class Schedule
October 20     Monday     - No Classes
October 24     Friday     - Follows a Monday Class Schedule
November 27    Thursday   - No Classes
November 28    Friday     - No Classes
December 16-22 Final Exam Period
    BBA Program Learning Goals
    Goals Significant
    Part of the
    Course    		 Moderate
    Part of
    Course    		 Minimal
    part of
    Course    		 Not Part of
    Course
    Analytical Skills    X
    Technological Skills   X
    Communication Skills: Oral    X
    Communication Skills: Written    X
    Civic Awareness and Ethical
    Decision-Making     		   X
    Global Awareness    X