Zain Bike Share Analysis

A bike-sharing operator needs to understand when and why demand peaks, how casual riders differ from registered members, and where the service can be improved. This project answers those questions by analyzing the bike-sharing data with SQL and turning the findings into an interactive Power BI dashboard.

SQL, Power BI, Power Query, DAX, Data Modeling, Data Visualization.

The project began with data preparation and exploration using SQL to understand the structure of the bike-sharing dataset. I used SQL queries to filter, aggregate, and summarize the data, examining rider types, seasonal patterns, hourly usage, weekday trends, and weather-related effects. The cleaned and transformed data was then loaded into Power BI, where I built a data model, developed DAX measures for KPIs, and designed an interactive dashboard that brings the analysis together.

The dashboard below summarizes the bike-sharing analysis with KPI cards, trend charts, and breakdowns by rider type, season, and time.

The dashboard enables exploration of rider behavior across multiple dimensions. It shows how registered and casual riders use the service differently, how usage varies by season, month, and day of the week, and how hourly patterns reveal peak and off-peak periods. The analysis also highlights the relationship between weather conditions and overall bike-sharing activity, supporting a clearer understanding of demand drivers.

This project demonstrates the ability to move from raw bike-sharing data through SQL analysis to an interactive Power BI dashboard, showing skills in data cleaning, analytical querying, data modeling, DAX, and visualization.