SQL Challenges from Data Lemur
SQL is often the foundational skill for extracting data used in other processes. I aim to improve my SQL skills by completing the challenges from Data Lemur that range in difficulty, industry, and techniques.
Project Introduction
SQL remains a staple of the data community. From engineers to analysts, scientists to visualizers, a foundation of interacting with databases is paramount.
SQL is also such a core focus in jobs that individuals and companies are offering training and practice with SQL in preparation for that dream job.
"I regret learning SQL. - said no one ever."
One such organization is Data Lemur, the brain child of Best-Selling Author Nick Singh. He built a resource of more than 50 SQL scenarios and an interactive tool to practice.
I aim to enhance my SQL skills by solving all 50 and documenting my approach and solutions in a Git Hub repo.
Situation
I work with SQL daily. At my current employer, we have a handful of MySQL databases and our BI tool uses PostgreSQL for transformation.
Despite this experience, I want to learn more and document my abilities in a more comprehensive manner. I believed Data Lemur's 50 exercises fit the bill.
Task
I aim to complete all 50+ SQL exercises on Data Lemur. They range from Easy to Hard and are inspiried from various industries.
They derive from companies like Facebook, Uber, Robinhood, Amazon, Google, LinkedIn, and much more. They allow practice with aggregation, filtering, joining, window functions, subqueries, CTEs, and more.
Data Lemur leverages PostgreSQL RDBMS for the exercises which affords me additional practice with their syntax and functions.
Action
I've documented all the approaches, solutions, and learning I've accomplished in my Git Hub repo. You'll find explanations about the problem and links to the exercise as well.
I've approached each problem with my current knowledge first. Should I get stuck, I've searched the web and tried new angles. Upon completing the exercise, I always look at the official solution to learn new approaches.
Result
I successfully completed all 54 free SQL challenges offered by Data Lemur:
Despite writing SQL with my current employer and creating my own database to track my wardrobe, I'm astounded by how much my skills have grown!
I was able to practice novice to advanced techniques, specifically developing great intuition and application of window functions and CTEs. Data Lemur tagged most of the challenges and you can see the frequency techniques practiced in these challenges.
- Calculate Rates: 10
- Array Functions: 3
- Minimum/Maximum: 2
- Date-Time Operations: 22
- Mathematical Functions: 1
- Aggregations: 37
- Type Conversion: 15
- Categorize Data: 27
- WIndow Functions: 16
- Top X: 5
- Existence Check: 3
- Cumulative Sums: 2
- Conditional Aggregation: 13
- Unique Results: 12
- User Behavior: 10
I was also so impressed with how the structure of my queries improved to enhance readability and efficiency. I feel far more equipped with the available techniques and features of SQL to solve data transformation and extraction problems.
I'm also very impressed with PostgreSQL. I always considered MySQL as the gold standard open source RDBMS but after creating a wardrobe database from scratch in MySQL and gaining extensive experience with PostgreSQL, I'll be looking for a new project requiring a database in which I can deploy PostgreSQL.
Project Components
View all of the exercises and my solutions in Git Hub. You'll find brief summaries of the challenge, my solution, and a link to the official problem in the README.md file. The .sql files contain my solution code.