Introduction

Today marks the second day of Dashboard week, where our focus was to pivot towards analyzing gambling data in power BI. This source contained a bunch of information about different gambling types, but I chose to focus on gaming machines, and look at how it changes between states and overtime.

Alteryx

My first goal was to gather all the necessary information associated with gaming machines, in which I used Alteryx to do so. The first issue I encountered was that each measure I wanted data from was unclean.

To clean the data for each desired measure, I designed a macro. This macro would be able to perform all the cleaning duties required so that the measure data was clean, and formatted the same across all measures.

Eventually I was able to collate all the information for a specific combination of state and year into one table as seen below. I could now start visualizing in power BI.

Power BI Report

This report was built to provide insight into which states contributed the most towards gaming machine measures, as well as any other unique insights discovered along the way. The big difference that was made today is that this report was made to tell a story. Yesterday’s dashboard was geared towards a more business setting, leaving little room for a story to be told. This report however tells a story, and builds upon the insights as more measures are introduced.

You can check out the full report through this link: https://app.powerbi.com/view?r=eyJrIjoiMmJlODVkMmQtMjBmYi00ZTcxLWEyYjMtNDRjZTdmMmNiMDk5IiwidCI6ImVmZjQxMDE3LWMxZmYtNGMyMC1hYmEyLWMxMWIzOTMwYmIxMiIsImMiOjEwfQ%3D%3D

Source: https://www.qgso.qld.gov.au/statistics/theme/society/gambling/australian-gambling-statistics