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Sharing a sample of my Excel data cleaning and quality-checking work.
In this project, I worked on identifying duplicate order IDs, checking missing values, correcting data formats, and validating calculated profit metrics before analysis.
I'm continuing to build my Data Analyst portfolio through hands-on projects using sample data and Microsoft Excel.
#Excel #DataCleaning #DataAnalysis #DataQuality
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Related posts
How I Built an End-to-End Sales Analytics Dashboard in Excel for an E-commerce Company
I recently completed an end-to-end sales analytics project using Microsoft Excel, transforming raw e-commerce sales data into an interactive dashboard that provides meaningful business insights.
In this project, I explored the data, performed analysis, identified key sales trends, and built an interactive dashboard to help businesses make data-driven decisions.
I documented the entire process, including the approach, tools, analysis, and dashboard development.
Read the full project walkthrough on Medium: https://medium.com/@Refino/how-i-built-an-end-to-end-sales-analytics-dashboard-in-excel-for-an-e-commerce-company-e8692d81f354
Excellent work! Turning raw data into actionable business insights is a valuable skill.
Exploring how complex financial data can feel simple, structured, and easy to navigate.
Vault One is a crypto portfolio dashboard concept that brings together asset performance, portfolio allocation, transaction history, and key financial metrics in one workspace.
I focused on visual hierarchy, information density, and data visualization, using a neutral color palette, subtle UI details, and selective accent colors to keep the interface clean without compromising functionality.
The goal was to make the data easier to understand, not just nicer to look at.
Would love to hear your thoughts on the visual direction and layout!
#ProductDesign #UIDesign #Fintech #DashboardDesign #UXDesign
This project demonstrates my approach to preparing reliable data for analysis using Microsoft Excel.
I worked on identifying duplicate order IDs, checking missing values, correcting data formats, and validating calculated profit metrics. These quality checks helped improve data consistency and prepare the dataset for further analysis.
Key activities
Identified duplicate order IDs.
Reviewed missing values in important columns.
Standardized data formats, including discount percentages.
Validated calculated profit and profit variance.
Prepared the dataset for accurate reporting and analysis.
