Syllabus
CS 451/651: Data-Intensive Distributed Computing (Fall 2025)
Schedule
| Week | Description | Dates | Assignments | |
| 1 | The Data Flywheel | Sep 4 | A1 Released: 9/4 | |
| 2 | Data Warehouses, Data Lakes, and Lakehouses | Sep 9, 11 | A2 Released: 9/11 | A1 Due: 9/11 |
| 3 | Batch Processing I | Sep 16, 18 | ||
| 4 | Batch Processing II | Sep 23, 25 | A3 Released: 9/25 | A2 Due: 9/25 |
| 5 | Rubber, Meet Road | Sept 30, Oct 1 | ||
| 6 | Data Infrastructure for Machine Learning | Oct 7, 9 | A4 Released: 10/9 | A3 Due: 10/9 |
| 7 | Reading Week: No Classes! | |||
| 8 | Midterm Exam | Oct 21, 23 | ||
| 9 | Text Processing I | Oct 28, 30 | A5 Released: 10/30 | A4 Due: 10/30 |
| 10 | Text Processing II | Nov 4, 6 | ||
| 11 | Clustering | Nov 11, 13 | A6 Released: 11/13 | A5 Due: 11/13 |
| 12 | Graph Processing | Nov 18, 20 | ||
| 13 | Stream Processing | Nov 25, 27 | A6 Due: 11/27 | |
| 14 | LLMs | Dec 2 | ||
| Final Exam | TBD |
Week 1: The Data Flywheel Sep 4
Key Questions
- What does it mean to be an AI-first or data-driven company?
- What's the data flywheel?
- What's data engineering?
- What are data platforms?
- What are the 4 V's of data?
- What is this course about? And what is it not about?
Readings
- Fundamentals of Data Engineering:
- Designing Data-Intensive Applications, 2nd Edition:
- Chapter 1. Trade-offs in Data Systems Architecture — Intro section and "Analytical versus Operational Systems" (stop at "Cloud versus Self-Hosting")
The above readings are available for free online through the university's library. The links above point directly to Waterloo proxied content, but if you're having trouble accessing the content (e.g., due to VPN settings), you might have go through the library's portal (i.e., search for the book title and follow the appropriate link).
Slides
Week 2: Data Warehouses, Data Lakes, and Lakehouses Sep 9, 11
Key Questions
- What are the main differences between operational and analytical infrastructure?
- What are data warehouses? What problems did they evolve to solve?
- What are data lakes and lakehouses? What problems did they evolve to solve?
- What are the components of modern data platforms?
- How do operational and analytical data models differ?
- What goes on in ETL/ELT?
- How do different physical representations of data affect storage, compute, and other tradeoffs within data platforms?
Readings
- Designing Data-Intensive Applications, 2nd Edition:
- Chapter 3. Data Models and Query Languages — Intro section and "Relational Model versus Document Model" (stop at "Graph-Like Data Models")
- Chapter 4. Storage and Retrieval — Intro section and "Data Storage for Analytics" (i.e., skip "Storage and Indexing for OLTP" and "Multidimensional and Full-Text Indexes")
- Chapter 5. Encoding and Evolution — Intro section and "Formats for Encoding Data" (stop at "Modes of Dataflow")
- (Optional) Fundamentals of Data Engineering (These readings covers similar content as above, but offer a complementary perspective to enrich your perspective):
- Chapter 3. Designing Good Data Architecture — Discussion of data warehouses, ETL, etc.
- Chapter 8. Queries, Modeling, and Transformation — Discussion of data modeling, star and snowflake organizations, etc.
The above readings are available for free online through the university's library. The links above point directly to Waterloo proxied content, but if you're having trouble accessing the content (e.g., due to VPN settings), you might have go through the library's portal (i.e., search for the book title and follow the appropriate link).
- What Goes Around Comes Around... And Around... by Michael Stonebraker and Andrew Pavlo (2024). Answers the question: Why relational?
- What Goes Around Comes Around by Michael Stonebraker and Joseph M. Hellerstein (2005). Optional reading, but provides nice historical historical perspective, written 20 years ago.
- Introduction to Data Lakes from Databricks.
- What is a Data Lake? from Microsoft. (It's helpful to get multiple perspectives, even if some aspects are repetitive)
- What Is a Lakehouse? from Databricks.
- What is a medallion architecture? from Databricks.
Slides
PDF slides for Sept 9 (v1.01) PDF slides for Sept 11 (v1.00)