Ecommerce data analysis

n this project, I analyzed sales data from 2017 to 2019 to provide actionable insights.

Data Extraction:

Connected Power BI to the SQL Server database.

Retrieved relevant tables and queries containing sales, customer, and product data.

Data Transformation (Power Query):

Cleaned the data by removing duplicates and handling missing values.

Applied transformations such as splitting columns, merging tables, and normalizing data formats.

Created calculated columns and measures for KPIs like Total Sales, Total Profit, and Average Order Value.

Data Modeling:

Established relationships between tables (e.g., Sales, Products, Customers).

Defined hierarchies for drill-down analysis (e.g., Year > Quarter > Month).

Dashboard Design:

Designed interactive dashboards to visualize key metrics and trends.

Used various visual elements such as bar charts, line charts, and slicers to allow users to filter data by region, product, and time period.

Insights and Reporting:

Highlighted top-performing products, sales regions, and customer segments.

Provided insights into sales trends over time and identified areas for improvement.

Shared the dashboard with stakeholders via Power BI Service for real-time access and collaboration.

1. Sales and Financial Analysis

Total Revenue: $154.57 million over three years.

Profit Trends: An average annual profit of $19.26 million, with 2018 being the most profitable year.

Top Revenue-Generating Cities: Christchurch, Hamilton, and Waitakere.

2. Customer Insights

A total of 50 customers, contributing to 7,991 orders and purchasing 67.58K products.

The top 5 customers by profit include companies like Medline and Apollo Ltd.

Notable growth in customer numbers from 2017 to 2019.

3. Product Performance

15 products analyzed, with Product 7 being the most ordered and profitable.

Insights into delivery duration, average orders per customer, and profitability of each product.

4. Currency Analysis

Transactions conducted in multiple currencies (NZD, USD, AUD, GBP, EUR).