Now the data we are talking about is usually highly confidential and one of the major reasons why we will be working with dummy data.
The data we have is that of a single ATM, for various time periods.
Our fields are Holiday (Binary) where 1 indicates an holiday and 0 indicates a normal working day.
Up time defines how long was the ATM up. At times ATM’s could not be functional because of power outage, network connectivity or physical issues.
Peak period (Binary) where 1 indicates peak period and 0 indicates non peak period.
Dispense cash is dispensed cash against a particular day.
Now in general for a normal ATM the weekly trend would be a spike in dispense on the start of weeks mostly Monday and a drop during end of the week ie Saturdays and Sundays.
For a monthly trend the spike would be at the beginning and end of the month and a drop somewhere in between. And this seems logical to, think of salaried people as an example, they get their salaries at the end of the month and probably use it to plan their month ahead, or business men would like to pay their dues or salaries to their employees at the end of the month and therefore withdraw cash.
Above you can see a few basic insights regarding cash dispense.
You can download the dummy data set that I have created from here