Power BI:

June 2025

Data Information:

Dummy Data was generated by AI.

Online Retail Sales Overview Dashboard

Project Overview

This project explores synthetic transactional data from a large e-commerce retailer to analyse customer purchasing behaviour over a 2-year period (May 2023 – May 2025) across multiple countries. The dataset was designed with intentional inconsistencies and messiness to simulate real-world data cleaning challenges. PostgreSQL was used for data exploration and cleaning, while Power BI was used for data modelling and visualisation.

Full project details can be found on my GitHub.

  • Insight Analysis
  • Data Analysis
  • Visualisation
  • Power BI

Dashboard Analysis

Watch the Overview Analytics Dashboard in action.

Key Dashboard Insights

  • Total Revenue: $15,411,232.13
  • Top Markets: United States, New Zealand, India
  • Best Time to Sell: Morning hours lead in sales quantity
  • Top Category: Clothing
  • Forecast: Potential dip projected in mid-2025

Visualisation Summary (Power BI)

  • Enhanced Visibility: Offers HR leaders a clear view of key workforce metrics, enabling better understanding and management of human capital.
  • Data-Driven Decisions: Supports strategic HR initiatives by providing actionable insights derived from comprehensive data analysis.
  • Employee Insights: Helps identify trends in employee satisfaction, performance, and retention, allowing for targeted interventions and improvements.
  • Equity and Inclusion: Promotes fairness in compensation and gender representation, fostering a more inclusive workplace culture.

Project Timeline

  • Data Cleaning: PostgreSQL
  • Data Modelling & Visualisation: Power BI
  • Dashboard Creation: Power BI
  • Analysis & Insights: Power BI

Summary

This project demonstrates the full analytics workflow from messy raw data to actionable insights. It showcases skills in data cleaning, normalisation, SQL, data modelling, and interactive visualisation using Power BI. It reflects a realistic scenario of preparing data for business decision-making in e-commerce.