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There are 4 modules in this course
SQL for Problem Solving is designed for learners who already understand the basics of SQL and are ready to apply their skills to real-world data problems. In this hands-on course, you’ll move beyond textbook queries to tackle the challenges data analysts face every day. From diagnosing data quality issues to building rolling metrics and interpreting event data, this course gives you the toolkit to write powerful, efficient SQL queries across different dialects and complex datasets.
You’ll learn:
- Problem-solving strategies used by data professionals
- Techniques for debugging, improving data quality, and building complex queries
- How to work with modern data environments, from event logs to denormalized schemas
- How to communicate business-relevant insights through SQL-based analysis
Whether you're preparing for a data job interview, building dashboards for stakeholders, or leveling up your data chops, this course empowers you with the skills to make SQL your go-to tool for data analysis and problem-solving.
After this module, you will be able to navigate the course environment and datasets, recall and apply key SQL concepts including joins, CTEs, and aggregation. You will be able to identify and resolve common SQL errors. You will also be able to apply structured approaches to SQL problem-solving and use diagnostic techniques to evaluate data quality. Finally, you'll be able to simplify queries using CTEs, subqueries, and pivot logic.
Solution: SQL Clauses & Functions - Part 1•5 minutes
Solution: SQL Clauses & Functions - Part 2•7 minutes
Review Joins, Subtables and CTES•4 minutes
Solution: Review Joins, Subtables and CTES - Part 1•7 minutes
Solution: Review Joins, Subtables and CTES - Part 2•5 minutes
Review by Troubleshooting Errors•4 minutes
Solution: Troubleshooting Errors•7 minutes
Spreadsheets vs. SQL•3 minutes
Introduction to SQL Problem Solving Techniques•1 minute
Quick Tricks to Check Data Quality•3 minutes
Coalesce to Improve Data Quality•6 minutes
Pivot and Roll-Up Data - Part 1•3 minutes
Pivot and Roll-Up Data - Part 2•4 minutes
Using a Backbone Table for Structure•4 minutes
Use CTEs and Subqueries to Reduce Complexity•2 minutes
Can You Do Loops in SQL? - Part 1•4 minutes
Can You Do Loops in SQL? - Part 2•5 minutes
2 readings•Total 11 minutes
Course Navigation and Safety Statement•1 minute
Course Dataset•10 minutes
6 assignments•Total 55 minutes
Review: Entity Diagrams•3 minutes
Review: Clauses and Functions•7 minutes
Review: Joins and Subtables•4 minutes
Review: Troubleshooting Errors•4 minutes
Review: Spreadsheets vs. SQL•7 minutes
SQL Problem Solving Techniques Quiz•30 minutes
The Modern Data Environment
Module 2•2 hours to complete
Module details
After this module, you will be able to describe how data flows to analysts in modern stacks. You will be able to write SQL queries on event and JSON-based data. You will be able to evaluate the trustworthiness of different data sources.
What's included
15 videos1 assignment1 discussion prompt
Show info about module content
15 videos•Total 64 minutes
Introduction to the Modern Data Environment•1 minute
Where Does the Data Come From Anyway? - Part 1•4 minutes
Where Does the Data Come From Anyway? - Part 2•6 minutes
Production Databases + SQL Dialects + History•6 minutes
Solution: Exploring the Events Table - Part 1•5 minutes
Solution: Exploring the Events Table - Part 2•2 minutes
All About Event Data - Part 1•5 minutes
All About Event Data - Part 2•5 minutes
Deep Dive - How to Use Field History Table•4 minutes
Solution: Evaluate AI Generated Code - Part 1•3 minutes
Solution: Evaluate AI Generated Code - Part 2•6 minutes
Data Pipelines - Part 1•3 minutes
Data Pipelines - Part 2•6 minutes
SQL Style Guide•7 minutes
Reminders Of Where To Be Skeptical•2 minutes
1 assignment•Total 30 minutes
The Modern Data Environment Quiz•30 minutes
1 discussion prompt•Total 5 minutes
Events•5 minutes
Using Data to Drive Business Decisions
Module 3•3 hours to complete
Module details
After this module, you’ll be able to design SQL queries to support reporting, metrics, and goal tracking. You'll be able to analyze data for executive dashboards, funnels, and retention. Finally, you'll be able to translate business questions into SQL-based investigations.
What's included
22 videos2 assignments1 discussion prompt
Show info about module content
22 videos•Total 93 minutes
Introduction to Business Focused Case Studies•1 minute
Applications of SQL Data Analysis•6 minutes
Normalized vs. Denormalized Data•7 minutes
Denormalized Line Items Table - Part 1•4 minutes
Denormalized Line Items Table - Part 2•4 minutes
BONUS: Keyboard Shortcuts•2 minutes
What Makes a Good Executive Metric?•3 minutes
Defining Good Metrics•6 minutes
Item_View Metric•5 minutes
Reporting Basics - Part 1•7 minutes
Reporting Basics - Part 1 Example•5 minutes
Reporting Basics - Part 2•3 minutes
Reporting Basics - Part 3•4 minutes
Reporting Basics - Part 3 Example•1 minute
Funnels and How They Extend to Retention - Part 1•5 minutes
Funnels and How They Extend to Retention - Part 2•6 minutes
Deep Dive: Retention & LTV•4 minutes
Retention Example: Period Over Period (PoP)•3 minutes
AB Testing•3 minutes
Example of AB Testing•5 minutes
Going Beyond SQL•2 minutes
Exploratory Analysis & Case Studies•6 minutes
2 assignments•Total 90 minutes
Business Focused Case Studies Quiz•30 minutes
From Question to Insight — The SQL Problem-Solving Mindset•60 minutes
1 discussion prompt•Total 10 minutes
Normalized & Denormalized Data•10 minutes
From Query to Insight - Solving Real Problems with SQL
Module 4•3 hours to complete
Module details
After this final module, you will be able to tackle open-ended SQL challenges with limited guidance. You'll be able to construct queries to support forecasting and recommendation systems. You'll also be able to communicate insights through effective SQL design and visualization prep.
What's included
23 videos1 reading2 assignments
Show info about module content
23 videos•Total 82 minutes
Introduction to Data Science in the Wild•1 minute
Triage a Business Question•2 minutes
Scenario: Sloppy Question Clinic•3 minutes
Example: Descriptive Statistics for Design•2 minutes
Another Example: Which Segment is the Biggest?•2 minutes
Investigating a Drop•7 minutes
Mix Shift•2 minutes
Problem Solving: Getting Un-Stuck•3 minutes
Test As You Go•2 minutes
Collaborative Filtering Recommender•6 minutes
Item Recommender: Start Coding - Part 1•5 minutes
Item Recommender: Start Coding - Part 2•4 minutes
Data Preparation•3 minutes
Create Data to Feed a Forecast•6 minutes
Just For Fun: How to Forecast in Python•5 minutes
Define a Metric: Activation•1 minute
Funnel Skill - Part 1•5 minutes
Funnel Skill - Part 2•6 minutes
Funnel Skill - Part 3•5 minutes
Visualization Clinic•5 minutes
Remove Distractions•3 minutes
Interview Mindset and Tools•5 minutes
Course Summary•0 minutes
1 reading•Total 10 minutes
Interview Question Bank•10 minutes
2 assignments•Total 75 minutes
Data Science in the Wild Quiz•30 minutes
From Data to Decision: Analyzing Insights with SQL•45 minutes
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