E-Commerce Data Analytics
&Visualisation
&Visualisation
Overview
TheLook is a fictional eCommerce clothing site developed by the Looker team. The dataset simulates real-world retail activity across users, orders, and product categories. I wanted to uncover actionable insights to support business decisions around market segmentation, seasonal trends, and product performance. I utilised SQL for data exploration and Power BI for data modelling, analysis and visualisation.
Approach
The Goal was to practise end-to-end reporting by translating raw data into meaningful insights that can guide pricing, marketing, and regional sales strategies.
Approach
I began by exploring the raw dataset in Google BigQuery using SQL, filtering for relevant fields such as non-null user IDs and valid order records. Once cleaned and structured, I exported the query results into Power BI for further analysis and semantic modelling.
In Power BI, I standardised column names and data types, handled missing values, and resolved formatting issues, such as converting text-based date columns to proper date types in Power Query. I then structured the tables and relationships into a semantic model, with a custom date table to support time intelligence.
I developed measures with DAX including total sales, total orders, and revenue share by category. These were used to build dashboards that visualise YoY sales performance and order volume trends across 2023 and 2024. The visuals compare quarterly patterns and highlight category-level dynamics, enabling a clear snapshot of seasonal behaviour and revenue distribution.
