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Project Overview
Project Overview
Aurora is an end-to-end data analytics capstone project focused on evaluating business performance and customer retention. Using SQL and Power BI, the project explores revenue performance, budget comparisons, regional and sales-channel contributions, profitability, and customer churn.
The workflow includes data cleaning, data validation, SQL-based analysis, financial calculations, and interactive dashboard development. The objective is to transform raw business data into meaningful insights that support informed decision-making and help identify opportunities to improve business performance and customer retention.
Tools & Skills Demonstrated
Tools & Skills Demonstrated
SQL (SQLite): Data querying, aggregation, validation, and business analysis.
Microsoft Power BI: Data modeling, calculated metrics, dashboard development, and visualization.
Data Cleaning: Preparing the dataset and checking data quality.
Business Intelligence: Comparing performance against budgets and examining regional, channel, and customer-segment trends.
Analytical Communication: Translating findings into actionable business recommendations.
Business Questions
Business Questions
How does actual revenue compare with budgeted revenue?
Which regions contribute most to total revenue?
How do sales channels compare in revenue and profitability?
How has revenue changed over time?
Which customer segments have the highest churn rates?
What actions could improve financial performance and customer retention?
Figure 1: SQLite query and customer churn rates by segment.
SQL Case Study: Customer Churn Analysis
SQL Case Study: Customer Churn Analysis
Business Question: Which customer segments experience the highest churn rates?
SQL Approach: Using SQLite, I grouped customers by segment, identified churned customers, and calculated the churn rate as a percentage of each segment's customer population. The query uses conditional aggregation and grouping to produce comparable results.
Key Findings:
Enterprise: 32.86% churn (23 of 70 customers).
Consumer: 29.31% churn (17 of 58 customers).
SME: 23.44% churn (15 of 64 customers).
Business Recommendation: Enterprise has the highest observed churn rate among the three segments. The business should investigate potential causes of customer attrition in this segment and evaluate targeted retention strategies.
Skills Demonstrated: SQL aggregation, conditional logic, customer segmentation, percentage calculations, and business insight generation.
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