There were two tasks completed as a part of this program, Exploratory Data Analysis and Predictive Analytics. These tasks were based on a synthesised transaction dataset containing 3 months’ worth of transactions for 100 hypothetical customers. It contains purchases, recurring transactions, and salary transactions. The dataset were designed to simulate realistic transaction behaviours that are observed in ANZ’s real transaction data.

Link to the Github Repository.
Link to Exploratory Data Analysis using Tableau.

This case study has been completed as the final capestone project for the Google Data Analytics Professional Certificate. The purpose of this case study is to answer the key business questions of a fictional company, Cyclistic, by following the steps of the data analysis process which has been taught in the course: Ask, Prepare, Process, Analyze, Share and Act.

Link to the Github Repository.
Link to Visualization using Tableau.

The objective of this assignment is to predict whether the customer will subscribe for the term deposit during the bank marketing campaigns. Building such predictive model could really help bank to identify patterns in the past bank marketing campaigns data and help them improve the future strategies for marketing campaigns. For an example, it could save effort, time and cost by targeting only customers who are more likely to subscribe for the term deposit.

Link to the project code.

This report has been submitted as the final assignment for the 'Data Wrangling' course during my Master's Degree at RMIT Univeristy by me. The purpose of the assignment is to find some open data and then preprocess the data using knowledge and skills gained during the course.

Link to the report.