This project showcases an analysis of a Bike Sales Dataset using Excel. The project is divided into three main parts: Data Cleaning, Pivot Table Analysis, and Dashboard Creation. The goal of this project is to demonstrate the skills required for cleaning raw data, summarizing it through pivot tables, and presenting insights using a visually engaging dashboard.
In this project, I performed the following tasks:
- Data Cleaning: Organized the raw dataset by removing inconsistencies, missing values, and unnecessary columns.
- Pivot Table Creation: Built pivot tables to summarize the data and generate insights on bike sales trends.
- Dashboard Creation: Designed a dashboard to visualize the insights gathered from the data, focusing on clear and impactful visual representation of key metrics.
The dataset used in this project contains information on bike sales. It is a dataset that was downloaded from AlexTheAnalyst's github and you can check it out here
It includes various customer demographic details, product-related data, sales regions, and other fields that allow for a detailed analysis of sales trends and performance metrics.
In this part of the project, I cleaned the raw dataset to make it ready for analysis. I:
- Removed empty or unnecessary columns and rows.
- Corrected formatting issues, such as inconsistent text or number formats.
- Filled in missing values and standardized categorical data.
This step ensures that the dataset is properly structured, allowing for accurate analysis in the next phase.
After cleaning the data, I used pivot tables to summarize and analyze key metrics. These tables allowed me to:
- Calculate the total number of bikes sold based on various criteria like product type, region, and customer demographics.
- Understand the relationship between customer characteristics and bike purchases.
- Analyze sales performance across different regions and time periods.
Finally, I created a visually interactive dashboard. It includes:
- Sales by Region: A chart showing the breakdown of bike sales by different regions.
- Sales by Product Category: A chart to visualize which categories of bikes are performing the best.
- Demographic Analysis: A chart that links customer demographics to sales patterns.
The dashboard makes it easier to communicate the results of the analysis to stakeholders.
This project demonstrates my ability to clean and structure a dataset, derive meaningful insights using Excel's Pivot Tables, and present the findings in a user-friendly, visually appealing dashboard. Through this project, I aim to showcase skills relevant to data analysis and business intelligence.