This project showcases my skills in SQL, Power BI, Data Analytics, Python through a real-world ecommerce dataset sourced from Google BigQuery (bigquery-public-data.thelook_ecommerce). It simulates a scenario where I work as a data analyst for an ecommerce brand to analyze trends, customer behavior, and forecast future revenue.

Dataset Source: bigquery-public-data.thelook_ecommerce
Tables Used:

• orders
• order_items
• users
• products

• What is the total revenue generated by completed orders?
• How has monthly revenue trended over time?
• What product categories contribute the most to revenue?
• How can we forecast future revenue trends?

| Google BigQuery | SQL querying and data exploration | | Python (Prophet) | Time-series revenue forecasting | | Power BI | Data modeling, visualization, and dashboard creation

• Monthly Revenue Trend (line chart with forecast)
• Total KPIs: Revenue, Orders, Customers, Avg. Order Value
• Revenue by Product Category
• Forecasted Revenue (Python

• Revenue is growing steadily month over month.
• Top 3 product categories generate over 70% of sales.
• A small group of loyal customers drive a large portion of revenue.
• Next 3 years’s revenue is forecasted to increase by ~X% based on current trends.

This project demonstrates the ability to:

• Join complex datasets using SQL
• Perform data cleaning, filtering, and transformation
• Create business-ready dashboards with KPIs and insights
• Forecast revenue using time-series models
• Tell a compelling data story to stakeholders

Tshepo Vincent Kgopane – Aspiring Business/Data Analyst