Why time-based analysis drives decisions in Power BI - Dashboard Impact

Dashboard Mode - Why time-based analysis drives decisions

Business Question

How do sales change over time, and which months show growth or decline? This helps decide when to boost marketing or stock inventory.

Sample Data

Month	Sales
January	100
February	150
March	130
April	170
May	160
June	180

Dashboard Components

• KPI Card: Total Sales
  Formula: Total Sales = SUM(SalesData[Sales])
  Result: 890
• Line Chart: Sales Over Months
  X-axis: Month
  Y-axis: Sales
  Shows sales trend from January to June.
• Bar Chart: Month-over-Month Sales Change
  Formula: Sales Change = SUM(SalesData[Sales]) - CALCULATE(SUM(SalesData[Sales]), PREVIOUSMONTH(SalesData[Month]))
  Shows increase or decrease compared to previous month.

Dashboard Layout

+----------------------+-----------------------+
|      Total Sales      |   Sales Over Months   |
|       (KPI Card)      |      (Line Chart)     |
+----------------------+-----------------------+
|    Month-over-Month   |                       |
|     Sales Change      |                       |
|      (Bar Chart)      |                       |
+----------------------+-----------------------+

Interactivity

A slicer for selecting months lets you focus on specific periods. When you pick months, all visuals update to show data only for those months. This helps spot trends or dips in chosen time frames.

Self Check

If you add a filter to show only March to June, which components update and what happens?

• All components update to show data from March to June only.
• Total Sales KPI recalculates sum for these months (130+170+160+180 = 640).
• Line chart redraws sales trend for March to June.
• Bar chart shows month-over-month changes only within March to June.

Key Result

Dashboard shows total sales and monthly sales trends to help understand time-based sales changes.