To add a forecast, go to the ‘Analytics’ section on the visualizations pane. Make sure that the line chart is currently selected.
Scroll down until you see the ‘Forecast’ part. Expand it and click ‘Add’.
Congratulations! You have just created a forecast on the data from the exercise file.
For example, here’s how the current forecast looks like:
As of now, it’s just a straight, diagonal line.
The forecasting settings available in Power BI are the following:
- Forecast length (by points, seconds, minutes, hours, days, etc.)
- Ignore last
- Confidence interval
This time, let’s mix the settings up:
- Forecast length: 12 months
- Seasonality: 12 Points
The seasonality represents the complete cycle of peaks and dips in your data. Power BI automatically detects this but as you can see, it’s still a bit clunky.
The date we’re using has 2 years’ worth of data recorded monthly. The season is 1 year so that’s 12 points.
Press ‘Apply’ once you’re ready and you’ll see the effects immediately.