I am glad to share with you my latest work.😊😊
This is an #Exploratory #dataanalysis #project.
In this project, I used the Adventure works dataset, and I used #Excel and #PowerBI to perform the data analysis.
Adventure works is a virtual retail company selling bicycles, bicycle accessories, and clothing.
While working on this project I followed some steps to derive the most accurate and decision-making-supporting insights.
These steps are:
- Asking the right questions.
- Preparing data for analysis.
- Processing data and ensuring data cleanliness.
- Analyzing the data.
- Designing the dashboard.
In the first step "Asking phase", I started asking some questions that might help me in the following steps and help me set up a track to work on. Some of these questions are:
1- What is the most sold product?
2- What is the region with the highest sales rate?
3- What is the product with the highest net profit?
4- What is the average return number for all products?
5- What are the customer demographics that affect buying habits?
Then I started preparing the data to make sure of its integrity and to make sure it was suitable for my project.
After that, I started the processing phase by cleaning the data and preparing it for the analysis phase by ensuring it doesn't consist of any errors or null values and it's formatted correctly, and has the right data types.
This is an #Exploratory #dataanalysis #project.
In this project, I used the Adventure works dataset, and I used #Excel and #PowerBI to perform the data analysis.
Adventure works is a virtual retail company selling bicycles, bicycle accessories, and clothing.
While working on this project I followed some steps to derive the most accurate and decision-making-supporting insights.
These steps are:
- Asking the right questions.
- Preparing data for analysis.
- Processing data and ensuring data cleanliness.
- Analyzing the data.
- Designing the dashboard.
In the first step "Asking phase", I started asking some questions that might help me in the following steps and help me set up a track to work on. Some of these questions are:
1- What is the most sold product?
2- What is the region with the highest sales rate?
3- What is the product with the highest net profit?
4- What is the average return number for all products?
5- What are the customer demographics that affect buying habits?
Then I started preparing the data to make sure of its integrity and to make sure it was suitable for my project.
After that, I started the processing phase by cleaning the data and preparing it for the analysis phase by ensuring it doesn't consist of any errors or null values and it's formatted correctly, and has the right data types.
Then I started the data analysis phase in which I started observing the data to find any patterns, anomalies, or anything unusual. I also started creating some measures, custom, and calculated columns to help me increase my understanding of the data.
At the end of this project, I started working on the design by searching for the most suitable colors which may reflect the company's businesses and vision and selecting the right visuals for each page in the dashboard.
I concluded some insights from this project such as:
1- The United states drive the highest revenue across all regions so we maybe should focus on marketing in this region and try to make more retail shops in it.
2- Bikes are the most popular category and it derives the highest revenue.
3- The most sold product was the water bottle - 30 oz but the product with the highest net profit was the mountain-200 black bicycle.
4- The average return rate is 14.74 items.
5- Homeowners tend to buy more than those who don't own their homes so we should focus on marketing our products to homeowners.
This is the link to the project on GitHub: https://lnkd.in/dV_MHGkJ
Finally, I would like to know if you have any comments or advice on this project. ☺️☺️
#work #data #design #retail #projects #clothing #marketing #sales #github #share #like #help
At the end of this project, I started working on the design by searching for the most suitable colors which may reflect the company's businesses and vision and selecting the right visuals for each page in the dashboard.
I concluded some insights from this project such as:
1- The United states drive the highest revenue across all regions so we maybe should focus on marketing in this region and try to make more retail shops in it.
2- Bikes are the most popular category and it derives the highest revenue.
3- The most sold product was the water bottle - 30 oz but the product with the highest net profit was the mountain-200 black bicycle.
4- The average return rate is 14.74 items.
5- Homeowners tend to buy more than those who don't own their homes so we should focus on marketing our products to homeowners.
This is the link to the project on GitHub: https://lnkd.in/dV_MHGkJ
Finally, I would like to know if you have any comments or advice on this project. ☺️☺️
#work #data #design #retail #projects #clothing #marketing #sales #github #share #like #help
