Course Overview

Course Description

This course introduces the use of SQL for creating and interacting with relational databases as well as for developing applications using application program interfaces and query programming languages. Students will gain hands-on experience in server level database installation, use of query languages for database creation, manipulation and information retrievals, and web-based applications that would interact with back-end databases for data and information management.

Prerequisites

BCOR 2710 and ISBA 3710 with a grade of C- or higher

Course Learning Outcomes

  • Become a data analyst: use SQL for data exploration and analysis
  • Become a data engineer: use modern technologies to extract, transform, and load data
  • Become a data professional: communicate data findings to both technical and non-technical audiences

ISBA Major Learning Outcomes

  • Utilize competencies gained from hands-on experience in core information technologies including programming languages, database management systems and other software used to create and store data, interact with databases in a SQL environment and develop database applications through web and mobile interfaces
  • Apply critical thinking and problem-solving skills when analyzing business problems
  • Identify problems, structure problems, propose an IT solution, and solve the problem
  • Develop proficiency in one or more mainstream programming language, such as SQL, PHP, JavaScript, and Python
  • Effectively communicate complex technological concepts including oral communications and written communications

Required Materials

No textbook required. Optional references available through the library's O'Reilly subscription:

Software and Tools:

Work Load Expectations

Per LMU's Credit Hour Policy, one credit hour requires a minimum of 3 hours of work per week. For this 4-credit course, expect approximately 12 hours of total weekly effort. With 200 minutes of class time per week, plan for 8-9 hours of outside work.

Instructor

Greg Lontok

Email: gregory.lontok@lmu.edu (Teams preferred)
Office: Hilton 114
Office Hours: Tue, Thu 12:00 pm - 2:00 pm, Fri 10:00 am - 12:00 pm | Schedule via Calendly

Course Schedule

Week Date Topic Due
1 Mon, Jan 12
  • Course Intro
  • SQL Basics
  • 5-Step Analytics Framework
1 Wed, Jan 14
  • Lesson Exercises 01: Diagnostic Analytics
  • Window Functions (LAG)
  • CASE Statements
2 Mon, Jan 19 No Class - MLK Day
2 Wed, Jan 21
  • Lesson Exercises 01: Advanced Window Functions
  • Date Functions
  • Analytics Framework
3 Mon, Jan 26
  • Lesson Exercises 02: Success Analysis
  • Descriptive Analytics
3 Wed, Jan 28
  • Lesson Exercises 02: Diagnostic Analytics
  • WHO, WHEN, WHY Analysis
Lesson Exercises 01
4 Mon, Feb 2
  • Lesson Exercises 02 Continued
  • Data-to-Insight Storytelling
  • Quiz 01 Prep
4 Wed, Feb 4 Quiz 01 (50 min)
  • Quiz 01
  • Lesson Exercises 02
5 Mon, Feb 9
  • Lesson Exercises 03: RFM Analysis
  • Customer Segmentation
  • Subqueries
5 Wed, Feb 11
  • Lesson Exercises 03: SQL JOINs
  • INNER JOIN and LEFT JOIN
  • Product Performance Analysis
6 Mon, Feb 16 JOINs Practice
6 Wed, Feb 18
  • LEFT JOINs
  • Ranking Window Functions
Lesson Exercises 03
7 Mon, Feb 23
  • CTE
  • Window Functions
7 Wed, Feb 25 Window Functions Lesson Exercises 04 (Fri, Feb 27)
8 Mon, Mar 2 No Class - Spring Break
8 Wed, Mar 4 No Class - Spring Break
9 Mon, Mar 9 Data Storytelling
9 Wed, Mar 11 Quiz 02
  • Quiz 02
  • Lesson Exercises 05
Sat, Mar 14 LMU Datathon
10 Mon, Mar 16
  • Assignment 01 Presentations
  • Data Analyst Interview Prep
Assignment 01
10 Wed, Mar 18 Data Analyst Interview (Midterm)
11 Mon, Mar 23
  • Mini-Project 01 Session 01: Cursor, Claude Code, Docker Setup
  • Load CSV into Local PostgreSQL
  • AI Prompting Fundamentals
11 Wed, Mar 25
  • Mini-Project 01 Session 02: Git/GitHub Workflow
  • Query with psql
  • Review AI-Generated Code
12 Mon, Mar 30
  • Mini-Project 02 Session 01: Install Superpowers, Brainstorm Pipeline
  • Extract from Basket Craft MySQL
  • Transform + Load to Local PostgreSQL
Lesson Exercises 06 (MP01 Tutorial)
12 Wed, Apr 1 No Class - Easter Holiday
13 Mon, Apr 6
  • Mini-Project 02 Session 02: AWS Setup + RDS via Console and CLI
  • Load Basket Craft Data to Cloud PostgreSQL
13 Wed, Apr 8
  • Portfolio Project Walkthrough
  • Mini-Project 02 Session 03: Snowflake Setup
  • Load Raw Basket Craft Data from RDS to Snowflake
14 Mon, Apr 13
  • Mini-Project 02 Session 04: dbt Core + Star Schema
  • Staging Models, fct_order_items, Dimensions, dbt Test
Project Proposal
14 Wed, Apr 15
  • Mini-Project 03 Session 01: API Extraction with Python
  • Load to Snowflake
  • GitHub Actions Pipeline
Lesson Exercises 07 (MP02 Tutorial)
15 Mon, Apr 20
  • Mini-Project 03 Session 02: Streamlit Dashboard
  • Basics, Polish, and Deploy
15 Wed, Apr 22
  • Mini-Project 04 Session 01: Web Scraping with Python
  • Spec-Driven Development
Lesson Exercises 08 (MP03 Tutorial)
16 Mon, Apr 27
  • Mini-Project 04 Session 02: Vector Database + Embeddings
  • RAG Architecture
Project Milestone 01
16 Wed, Apr 29
  • Mini-Project 04 Session 03: LangChain + Claude API
  • Build RAG Chatbot in Streamlit
17 Mon, May 4
  • Data Engineer Interview Prep
  • Whiteboard Pipeline Practice
  • Mock Interviews
  • Lesson Exercises 09 (MP04 Tutorial)
  • Project Milestone 02
17 Wed, May 6 Reading Day - No Class
18 Mon, May 11 Finals Week - Data Engineer Interview (25%) Lesson Exercises 10 (Whiteboard Diagram)

Grading

Grade Breakdown

1 Group Assignment 10%
2 Quizzes 10%
10 Lesson Exercises (1% each) 10%
Midterm Interview 15%
Project 30%
Final Interview 25%
Total 100%

Grading Scale

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 60-69
F Below 60

Tips for Succeeding in Class

Stay Present & Engaged

Show up in person, on Teams, and in conversations. The more visible you are, the more I can coach you toward success. Disappearing is the fastest way to fall behind.

Bring Solutions, Not Just Problems

Challenges will come up: a tricky assignment, a group conflict, a late submission. When you reach out, also suggest a possible solution. This shows initiative and makes it easier for us to problem-solve together.

Build a Professional Relationship

Treat this class like a career opportunity. Ask questions, connect with me on LinkedIn, and seek feedback. Faculty often recommend students for jobs, but only if they know and trust you.

Practice Professionalism Daily

How you write emails and Teams messages, present your work, and collaborate with peers reflects directly on your future career. Use this class as a low-risk environment to practice the habits employers value.

Find Your Voice

Speaking up in class isn't the only way to contribute. Use Teams chat, post questions, or share resources. What matters is showing that you are actively learning and thinking, not staying silent.

Course Policies

AI Policy

AI tools like ChatGPT and GitHub Copilot are permitted in this course as learning aids. However, you must understand and be able to explain any AI-assisted work you submit.

Allowed

  • Using AI to brainstorm ideas and explore concepts
  • Getting help understanding error messages or debugging
  • Learning syntax or exploring different approaches
  • Reviewing and improving your own written work

Not Allowed

  • Submitting AI-generated work as your own without understanding it
  • Using AI during exams or interviews unless explicitly permitted
  • Copying AI output directly without review and modification
  • Using AI to complete work that assesses your individual learning

Attendance & Participation

If you feel ill, please stay home to keep others safe and recover. If an unexpected obligation arises that prevents you from attending class, please let me know before class or within 12 hours after the class start time.

I get there are emergencies or things that come up. Do your best to tell me in advance (at least a day before, if possible). I'm most concerned about you communicating and keeping me in the loop.

Each undocumented absence is -2% of your total class grade.

Assignment Submission

All assignments must be submitted through the designated platform (Brightspace) by the specified deadline. Late submissions will be penalized 10% per day unless prior arrangements have been made with the instructor. Technical issues are not valid excuses for late submissions. Plan ahead and submit early. Extensions may be granted in cases of documented emergencies.

Academic Honesty

Academic integrity is fundamental to the mission of Loyola Marymount University. All students are expected to adhere to the LMU Academic Honesty Policy. Violations include but are not limited to: plagiarism, cheating on exams, unauthorized collaboration, and fabrication of sources. Any violation will result in disciplinary action, which may include failure of the assignment, failure of the course, and/or referral to the Dean of Students.

Accommodations

Students with disabilities who require accommodations should contact Disability Support Services (DSS) to establish eligibility and coordinate appropriate accommodations. Please provide the instructor with your accommodation letter as early as possible so we can work together to support your learning. All discussions will remain confidential.

Syllabus Changes

This syllabus is subject to change based on the needs of the class. Any changes will be announced in class and posted on Brightspace. Students are responsible for staying informed of any modifications to the course schedule, assignments, or policies.

Exams & Quizzes

There are no make-up exams or quizzes. If you miss an exam or quiz due to a documented emergency, contact the instructor as soon as possible to discuss options.

Electronic Devices

Laptops and tablets are permitted for note-taking and class activities. Please silence your phone and avoid non-class-related browsing during class time. If device use becomes disruptive, the instructor reserves the right to restrict their use.

Title IX & Reporting

LMU is committed to creating a safe and supportive environment for all students. If you experience or witness sexual harassment, sexual assault, domestic violence, dating violence, or stalking, please know that help is available. You can report incidents and find resources through LMU Cares. Faculty members are required to report incidents to the Title IX office.

Emergency Preparedness

In case of emergency, follow the instructions of your instructor and building emergency personnel. Familiarize yourself with the nearest exits and emergency procedures. For campus emergency information, visit lmu.edu/emergency. Sign up for LMU Alerts to receive emergency notifications.