The purpose of this analysis is to conduct a preliminary analysis on a set of US bankruptcy data in order to better understand and potentially categorise different types of bankruptcy. Before this analysis takes place, a brief data description is provided, followed by some data wrangling and exploration to first clean the data, and then visualise some of the patterns and characteristics present in it.

Traditional methods such as language tutors or finding language partners can be expensive and time-consuming to organize. However, with ChattyChatty, you can now have an AI-powered language partner ready to chat with you anytime, anywhere, and on any topic. Our team aims to introduce ChattyChatty, its features, and the benefits it offers to language learners.

This analysis is to look into aspects of analysing churn data. Customer churn time is the length of time a customer stays with a company before leaving. This is a vital metric in many businesses and there is great interest in estimating it. The churn time changes, so we always want to estimate it with the most recent data available. This is statistically challenging as many (hopefully most) customers will have not churned at the time when the data is collected. This means that customer churn data is highly censored.

The motivation of this project was that I was curious why Apple was ranked top for years by Gaertner. And I found out their Supply Chain was highly optimised under the administration of Tim Cook.

This is a business process model documented as a context diagram and a Data flow diagram (DFD)