This task is 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 is designed to simulate realistic transaction behaviours that are observed in ANZ’s real transaction data, so many of the insights you can gather from the tasks below will be genuine. The relevant dataset is attached.

Load the transaction dataset below into an analysis tool of your choice (Excel, R, SAS, Tableau, or similar) Start by doing some basic checks – are there any data issues? Does the data need to be cleaned? Gather some interesting overall insights about the data. For example -- what is the average transaction amount? How many transactions do customers make each month, on average? Segment the dataset by transaction date and time. Visualise transaction volume and spending over the course of an average day or week. Consider the effect of any outliers that may distort your analysis. For a challenge – what insights can you draw from the location information provided in the dataset? Put together 2-3 slides summarising your most interesting findings to ANZ management.