Free Coupon VBM Portfolio Projects: SQL Data Cleaning (e-commerce data) [100% OFF]

Portfolio Case Study: Data Engineering, Analytics & Data Science — Dashboard Metrics, KPI Calcs, SQL Reporting Queries

Free Coupon VBM Portfolio Projects: SQL Data Cleaning (e-commerce data) [100% OFF]

Take advantage of a 100% OFF coupon code for the 'VBM Portfolio Projects: SQL Data Cleaning (e-commerce data)' course, created by Matthew Barr, available on Udemy.

This course, updated on January 31, 2026 and it is expired on February 01, 2026.

This course provides 1 hour(s) 49 minute(s) of expert-led training in English , designed to boost your Other IT & Software skills.

Highly rated at 5.0-star stars from 20 reviews, it has already helped 3,817 students.

This exclusive coupon is shared by Anonymous, at the price 14.99 $ 0 $

Don’t miss this opportunity to level up your skills!

You can find the discounted coupon code for this course at the end of this article

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” means

  • Explore 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 way

  • Enforce the business rules and deduplicate into one trusted clean_table

  • Compute and standardise all KPI outputs into a consistent results table

  • Validate results, understand tolerances/rounding, and debug mismatches like a professional

  • Finish by turning the whole pipeline into a portfolio-ready GitHub project, with a clean repo structure, a strong README, and proof of results

Course outline (high level):


  • Section 00: Course Introduction

  • Section 01: The Verulam Blue Mint Environment

  • Section 02: Understanding the Challenge Brief

  • Section 03: Exploring Source Data Schema

  • Section 04: Data Cleaning I – Sampling & Completeness

  • Section 05: Data Cleaning II – Silver Layer & Normalisation

  • Section 06: Data Cleaning III – Business Rules & Deduplication

  • Section 07: Understanding the KPIs

  • Section 08: Computing KPIs

  • Section 09: Results

  • Section 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.


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