DS-MARKET

This project is the final result of my journey to become Data Scientist. Here, we present a deliverable solution for managing the products of their stores of a company according to its requets.

Requirements:

• To analize the state of each store, the sales trends of the products, and their evolution,possibly by Country.
• Identify similar groups of products; how many exist?
• Forecast of sales.
• Forecast inventory supply.

Sprint 1

1. We received 3 datasets with information of company(item_prices, item_sales, daily_calendar_with_events)
2. Check and clean the datasets, understand the variables and analyze the data.(Worked with python using libraries like numpy,pandas,matplotlib,seaborn inside of Visual Studio Code y Jupiter notebooks)
3. Preprocessing to build the main dataset; here we created a dataset to show the visualization report and other dataset for clustering.

Sprint 2

1. Worked in clustering. Used K-means.
2. Choosed the correct model for prediction, ARIMA vs skforecast of Sklearn.

Sprint 3

1. Worked in visualization report.
2. Make prediction with model choose.
3. Worked in storytelling about results.

Results

We develop a dashboard report in Power Bi showing the stores´ behavior and busines.