VBM Portfolio Projects: SQL Data Cleaning (e-commerce data)

This course is built to give you a publishable portfolio project as the end product — a complete SQL data-cleaning and KPI pipeline you can put on GitHub, link on LinkedIn, and confidently talk through in interviews.It’s a real-world simulation built around one messy dataset and a business brief with a clear target: deliver ten KPIs that are trustworthy enough to go on a dashboard.Most SQL “data cleaning” courses either stay at the level of syntax drills, or they use clean toy datasets where nothing breaks. That’s not what you face in real data teams.In this course you’ll work through the same workflow you’d use on a real project:Read the brief properly so you know what “correct” meansExplore the raw schema and spot the mess early (mixed date formats, typos in categories, missing values, duplicates)Build a typed, safer silver layer where errors surface in a controlled wayEnforce the business rules and deduplicate into one trusted clean_tableCompute and standardise all KPI outputs into a consistent results tableValidate results, understand tolerances/rounding, and debug mismatches like a professionalFinish by turning the whole pipeline into a portfolio-ready GitHub project, with a clean repo structure, a strong README, and proof of resultsCourse outline (high level):Section 00: Course IntroductionSection 01: The Verulam Blue Mint EnvironmentSection 02: Understanding the Challenge BriefSection 03: Exploring Source Data SchemaSection 04: Data Cleaning I – Sampling & CompletenessSection 05: Data Cleaning II – Silver Layer & NormalisationSection 06: Data Cleaning III – Business Rules & DeduplicationSection 07: Understanding the KPIsSection 08: Computing KPIsSection 09: ResultsSection 10: Portfolio project deployment (repo + README + LinkedIn-style project story)By the end, you won’t just know “how to clean data using SQL”. You’ll have an end-to-end portfolio project you can explain clearly: what was wrong with the data, what you changed, what rules you enforced, and why your KPIs can be trusted.