
Apply Pareto analysis to reveal that a few causes drive most effects under the 80-20 rule, guiding data-driven prioritization of issues, products, or customers.
Build a Pareto analysis in Google Cloud BigQuery using views and CTE methods, detailing project and dataset setup, data upload, and revenue insights from customers.
Open Google Cloud and access BigQuery Studio in the sandbox environment. Sign in to cloud.google.com, navigate to BigQuery, and start learning with zero billing costs.
Create a new BigQuery project with a unique project ID, then create a dataset and upload the PetShopSales.csv as the Sales table with an auto-detected schema in London.
Perform a Pareto analysis on sales by customer, computing total sales as quantity times unit price, and count customers (261) to identify which customers contribute to the majority of sales.
Create a view to compute revenue as quantity times unit price, exposing customer_id and sales, and prepare to group by customer for per-customer totals.
Create a second view to group by customer ID and sum sales from the first view, producing customer revenue and enabling Pareto analysis with ranked, cumulative totals and percentages.
Learn to build view three with columns—customer id, customer revenue, cumulative and total customers, and cumulative and total revenue—using window functions for a Pareto analysis that identifies 80% of revenue.
Build and analyze a Pareto distribution by creating view four to compute cumulative sales shares and cumulative percent customers, enabling threshold-based insights like 80% of sales from 57% of customers.
Learn how to manage views with create or replace, save and recover views in a sandbox BigQuery environment, and prepare for custom user-defined SQL queries for dynamic Pareto analysis.
Please only attempt this after you've finished the analysis with views.
The most hands-on SQL portfolio project on the internet — built by a seasoned Data & Analytics Manager and community leader with 50K+ LinkedIn followers and 200K+ YouTube subscribers.
This isn’t your average SQL tutorial with dry theory and generic examples. The goal here is to build a SQL project in the cloud in under 2 hours.
This project is not about stretching out every piece of theory to make a course that is 10+ hours; this project is about helping you build a project in the most efficient and fastest way.
This is a fully guided, project-first bootcamp where you’ll build a real-world Pareto analysis from scratch using Google BigQuery — seeing every step, from data upload to advanced query-writing, with clear screen shares and code breakdowns to make advanced concepts click instantly.
This course draws from my years of professional experience in data analytics and stakeholder-facing projects at top organizations. Every query, technique, and insight comes straight from enterprise challenges I've solved — like pinpointing top customers driving the majority of revenue — not textbook fluff.
Whether you're an absolute beginner dipping your toes into SQL or a professional polishing your portfolio, this project takes you from zero knowledge to a recruiter-impressing deliverable in just a few hours.
No prior SQL coding, BigQuery setup, or analytics experience needed.
What makes this course truly unique:
Project focus: Upload data, write SQL queries, and create a custom Pareto analysis — all in one standout portfolio piece.
Beginner-friendly from minute one: Free BigQuery setup, no-cost tools, and plain-English explanations of every concept.
Real business impact: Learn the 80/20 principle through a practical example like identifying customers who drive revenue.
Portfolio perfection: Showcase this SQL project on LinkedIn, GitHub, or your resume.
Built by a practicing data expert: Learn only real-life, applicable SQL skills.
Topics covered in this portfolio project:
BigQuery Setup: Create a free account, upload datasets effortlessly, and navigate the interface like a pro.
Core SQL Fundamentals: Master SELECT, aggregations (SUM, COUNT), GROUP BY, ORDER BY — all explained from using simple, plain English.
Advanced Pareto Queries: Dive into window functions (ROW_NUMBER, SUM OVER partitions), cumulative percentages, ranking, CTEs, views and declaring variables to build your custom Pareto analysis.
Hands-On Project for Real Experience:
Theory alone won't land jobs — that's why this course centers on one high-impact project mirroring real-life workflows. You'll analyze a sales dataset to uncover the customers generating the most revenue, writing every SQL line in BigQuery, building the Pareto analysis, and packaging it as a portfolio ready project.