Our dashboard is built in Power Bi Desktop is free and can be connected to any different sources of data. In our case, we connected our SQL database.
I followed following steps to create my visualization and reports. 1) Connected to database 2) Transformed and cleaned data to create a data model 3) Created visualizations such as charts, graphs of data 4) Created reports generated of collection of visuals
We obtained a dataset of call center that includes following information.
Tables:
- Customers
- Customer Acquisition
- Customer Chat
- Employees
- Receipts
- Reviews
Each table has its own unique IDs such as Customer_ID, Chat_ID etc.
Created our own measures with Data Analysis Expressions(DAX) that help us to perform some calculations that I can use for my visualizations. DAX formulas are similar to formulas we use in excel. Once we create measures and its values can be aggregated. With those measures,
Aggregations are very important in understanding measures. Those measures further can be calculated to find following values: 1) Sum 2) Average 3) Min and Max 4) Count( Distinct) 5) Standard Deviation 6) Variance 7) Median values
Advantage of DAX function is that it works with relational data and can perform dynamic calculations as you interact with your report.
This measures help us to perform calculation on our data and results can be diplayed on dashboards.
Below, average rating has been calcualted taking into consideration ratings of employees.
Average Rating = AVERAGE('cassendra reviews'[RATING])
Count of RATING average per RATING =
AVERAGEX(
KEEPFILTERS(VALUES('cassendra reviews'[RATING])),
CALCULATE(DISTINCTCOUNT('cassendra reviews'[RATING]))
)