Among all my personal projects, this is my favorite. I created this report when I found out that the Puente Hills location, where I workout was going to close. So, I thought of making a report to show the busiest locations and provide detailed insights into member workouts for effective decision-making across all branches. For the Data Source, I created a table on Azure SQL Database. The Data I entered is according to my observation every time I worked out. Including the Month, time and the age of the members.

My Analysis Provided the following

• Shows the Total Number of workouts by Location. Management will be able to identify the locations that need attention especially to those location that has less visits.
• Insights of members by age group. Through this, Management can determine which machines and equipment are needed.
• A summary of workouts by time group, enabling management to plan appropriate training sessions for specific time periods.
• With the busiest times identified, management can plan staff allocation per shift, optimize electricity consumption and make the cleaning schedule more efficiently for financial purposes.

Here are the steps taken to complete the analysis

• Created a Server and Database on Azure Portal.
• Added table and entered data using Azure SQL Database.
• Used the Table as Data Source on Power BI Get Data.
• Created a Date Table and marked it as Date Table.
• Grouped Time and Age for clear insights.
• Created several DAX measures for the desired metrics.
• Published, Administered and created an App in Power BI Service for end users and business stakeholders.