This repository consists of some of the assignments and project questions I’ve done by taking an advanced online SQL course.

By exploring the database and writing multi-step SQL queries to work on real-world eCommerce use cases, I’ve improved MySQL Workbench Skills, gained a deeper understanding of leveraging SQL data analysis to help shape the performance and direction of business and, solidified digial marketing domain knowledge particuarly Web Analytics.

• Working as an eCommerce Database Analyst for a start-up online retailer.
• Exploring the database with multiple tables containing data about website activity, orders and products.
• Tackling the assignments and projects structured in way that follow the life of the company in chronological order.
• Extracting and analyzing data using SQL to help Marketing and Website Managers to steer the business in:

• Identify top volume and high-converting traffic
• Understand traffic segments to optimize marketing budgets
• Analyze channel mix for cross-channel bid optimization
• Analyze direct, organic, and brand-driven traffic

• Identify top website pages & top entry pages
• Analyze landing page performance & A/B testing
• Analyzing & Testing conversion funnels

• Analyze seasonal trends for demand forecasting and planning
• Analyze hourly and daily volume to support customer service decisions

• Analyze impact of new product launch
• Analyze product-level website pathing
• Cross-sell & product portfolio Analysis
• Product refund analysis

• Identify repeat visitors
• Analyze time to repeat
• Analyze repeat channel

• Think proactively as an analyst to figure out what metrics to use to judge performance for a specific field.
• Use CTEs to perform multi-step “data program” analyses. Map out each step needed to get to the answer.
• Slice data in segments (e.g. desktop vs. mobile) to continue to look for ways for performance optimization.
• Conduct time-series or trend analysis to monitor impact of change (e.g. bid adjust or new page/product launch).
• Use Pageview URL (similar to "Page Title" in GA) to build conversion funnels to analyze CTRs for each step.
• Use Inequality Join and DATEDIFF Function to analyze repeat customer behavior and repeat channel performance.
• Leverage MIN/MAX and Inequality Join to identify the first/most recent data points of auto-increment values.
• For A/B split tests, limit time periods to where both versions were live to ensure fair comparison.

This practice project is part of the Advanced SQL + MySQL for Analytics & Business Intelligence course taught by John Pauler (Analytics Experts with Maven Analytics). The database is owned by the instructor which is not publicly available.