The EU Superstore sales & profit analysis project is a data-driven exploration of a store sales data for one year. The project involves the analysis of several tables, including Segment, Product Types, Region, Orders, and Order Details. By creating relationships between these tables, various metrics can be derived, including sales revenue, product sales by type and size, average order value, monthly and quarterly sales & profit, top-selling categories and sub-categories, and sales & profit by time.
Data cleaning is a crucial step in any data analysis project, and it can be a complex and time-consuming task. The aim of this challenge is to enhance our expertise in cleaning and preparing datasets for analysis. We worked with real-world datasets, which contains incomplete, inconsistent, and messy data that requires careful cleaning and processing. During the challenge, I use MsExcel and Powerbi to clean the data, including managing missing values, handling outliers, standardizing formats, and managing duplicate records. By the end of the challenge, I gained valuable experience in data cleaning and was better equipped to handle complex data in our future data analysis projects. I'm looking forward to collaborating with other experts and opened to Internship opportunities.
This is a power BI project on sales analysis of an imagerinary store called Bez Pharmacy. The project is to analyze and derive insights to answer crucial questions and help the store make data driven decions.
Disclaimer : All dataset and reports do not represent any company, institution or country, but just a dummy dataset gotten online to demonstate the capabilities of PowerBI.
These includes PowerBI and Microoft Excel projects.
This is a SQL and power BI project on inventory analysis of an imagerinary hotel called SLG. The project is to analyze and derive insights to answer crucial questions and help the store make data driven decions. The process was achieved using SQL for data wrangling and exploration, and Power BI for visualization.
Disclaimer : All dataset and reports do not represent any company, institution or country, but just a dummy dataset gotten online to demonstate the capabilities of MySQL and PowerBI.