- The data includes records about amazon orders in the united states over years 2014- 2017.
- The data includes scores per segment, city, region, category, product sales, and profit in the Orders Sheet and Returned orders in the Returns sheet.
Now that data collection has concluded, I will share the full report summarizing the sales trends over years, and whether we should go ahead with more investment in the USA market. And I will include the following information areas: Focus areas:
- Data set characteristics
- Market share in terms of Volume and Value
- Top categories by region and state
- Return Rate by all possible classifications
- Strengths and improvement areas
- Promising Categories, products & Locations to invest in.
- Recommendations based on the findings
I will practice this project from start to finish, I will go through all stages from data analysis to deployment.
In this part, I will apply data analysis in order to extract a lot of information that can help the company decide whether to continue working in the US market or not, and also highlight the areas that can be invested in, in addition to determining the best state, the best city, and the best and most suitable products for investment.
I will work in data analysis using many tools, I will move away from Excel for the time being and complete the work using
- The Python programming language, in order to obtain beautiful Python code in the end, and also because Python enables me to work comfortably on data.
- Power BI data visualization tool, in order to extract an interactive visualization of the data that can be shared with non-professionals in programming and also helps decision makers to easily understand the results, and also so that they have a dynamic dashboard to deal with and look at the data away from tables and codes software.
After all, this will produce a lot of information that helps in a lot of things, and therefore I will organize those results in a good PDF file and work on summarizing my findings with many recommendations and tips for stakeholders that were extracted from the data analysis.