Lectures

 

In-Class Activity - SQL Joins Practice with Bend Blockbuster Database

DATA 351: Data Management with SQL

Lecture 00: Course Mechanics

DATA 351: Data Management with SQL

This lecture covers the course mechanics for DATA 351: Data Management with SQL.

Jan 12, 2026
Lucas P. Cordova, Ph.D.

Lecture 01:Introduction to Data Management with SQL

DATA 351: Data Management with SQL

This lecture covers the introduction to data management with SQL.

Jan 12, 2026
Lucas P. Cordova, Ph.D.

Lecture 02: Being Selective with SQL

DATA 351: Data Management with SQL

This lecture covers the SELECT, WHERE, ORDER BY, and LIMIT clauses of SQL.

Jan 14, 2026
Lucas P. Cordova, Ph.D.

Lecture 03: Data Types

DATA 351: Data Management with SQL

This lecture covers the data types.

Jan 26, 2026
Lucas P. Cordova, Ph.D.

Lecture 04: Importing and Exporting Data

DATA 351: Data Management with SQL

This lecture covers the importing and exporting data.

Jan 26, 2026
Lucas P. Cordova, Ph.D.

Lecture 05: Math Operators and Functions

DATA 351: Data Management with SQL

This lecture covers the math operators and functions.

Jan 26, 2026
Lucas P. Cordova, Ph.D.

Lecture 06: SQL Joins

DATA 351: Data Management with SQL

This lecture covers SQL joins using the Blockbuster Bend database. We explore inner joins, outer joins, cross joins, and self joins with real examples from film rental data.

Feb 2, 2026
Lucas P. Cordova, Ph.D.

Lecture 07: Normalization and Data Modeling

DATA 351: Database Design

This lecture covers database normalization and data modeling fundamentals. We explore the normalization process from messy flat files to well-structured relational schemas, practice with the Dunder Mifflin employee dataset, explore database design for the Oregon Turtle Conservation project, and learn to create Entity-Relationship diagrams using draw.io.

Feb 2, 2026
Lucas P. Cordova, Ph.D.

Lecture 08: Creating Tables and Constraints

DATA 351: Data Management with SQL

This lecture covers how to build database tables with proper constraints in PostgreSQL. After learning normalization, we now implement those designs with CREATE TABLE, primary keys, foreign keys, CHECK, UNIQUE, and NOT NULL constraints. We also cover ALTER TABLE for evolving schemas and indexes for query performance. A music catalog dataset serves as the running example.

Feb 16, 2026
Lucas P. Cordova, Ph.D.

Lecture 09: Inspecting and Modifying Data

DATA 351: Data Management with SQL

This lecture covers how to inspect raw data for quality issues and modify it using SQL. We continue with our music catalog dataset, finding duplicates, missing values, inconsistent casing, and typos in a staging table, then fixing them with UPDATE, ALTER TABLE, DELETE, and transactions before migrating data into normalized tables.

Feb 25, 2026
Lucas P. Cordova, Ph.D.

Lecture 10: Modifying Data and Migrating Tables

DATA 351: Data Management with SQL

This lecture covers how to modify data in PostgreSQL using ALTER TABLE, UPDATE, DELETE, and transactions. Building on Chapter 10 of Practical SQL, we apply these techniques to a Gen-Z pop music catalog (2015-2025) with intentional data quality issues. Students will clean a messy staging table and migrate the cleaned data into a 3NF normalized schema of artists, albums, and tracks. This is a hands-on, interactive session where students build their own SQL cleanup script to turn in.

Mar 10, 2026
Lucas P. Cordova, Ph.D.
 

Lecture 11-1: Statistical Functions in SQL

DATA 351: Data Management with SQL

This lecture covers statistical functions built into PostgreSQL. We explore correlation, linear regression, variance, standard deviation, ranking with window functions, rate calculations, and rolling averages. Based on Chapter 11 of Practical SQL, 2nd Edition.

Mar 4, 2026
Lucas P. Cordova, Ph.D.
 

Lecture 11: Advanced Statistics with Flight and Weather Data

DATA 351: Data Management with SQL

This lecture introduces advanced SQL statistics using real flight and weather data collected over Portland, Oregon. We transform raw JSON data into clean relational tables, then use correlation, ranking, window functions, and CASE statements to answer a simple question: do more planes fly over Portland when the weather is nice? Based on Chapter 11 of Practical SQL, 2nd Edition.

Mar 12, 2026
Lucas P. Cordova, Ph.D.
 

Lecture 12: Working with Dates and Times

DATA 351: Data Management with SQL

This lecture covers working with dates, times, and time zones in PostgreSQL. We explore date/time data types, extraction functions, time zone handling, date math, and interval calculations. We then apply these concepts to real-world datasets: NYC yellow taxi trip data and Amtrak train schedules. Based on Chapter 12 of Practical SQL, 2nd Edition.

Mar 19, 2026
Lucas P. Cordova, Ph.D.
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