This is to analyse the metadata and linguistic summary from a real online forum.

A dashboard for a uber-like business using Power BI.

The composition of child mortality has changed over time. In particular a larger proportion of deaths are classed as neonatal mortality, which is a death that occurs within one month of birth.

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.

This is a simulation case of System Analysis for a university PHD Research Meeting system; my role is conducted as a Business Analyst for Quatro J Ptv. Ltd.