An SPC (Statistical Process Control) chart is a popular chart, especially in healthcare and in manufacturing processes, but is not an outofthebox standard visualisation in Power BI. In this video we build a SPC chart. We start with a line chart, add a couple of slicers, write a few measures, and use these to add reference lines. If you want to follow along and build your own chart, the raw data for the chart is available at
https://raw.githubusercontent.com/Mar...

You can also download the Power BI file that I built
from https://github.com/MarkWilcock/Course...

Timestamps
00:00 Introduction to SPC Charts
00:42 The sample data used in the chart
01:10 Import, clean and reshape the raw data in the Query Editor
02:40 Build the basic visuals: line chart and slicers on date and region
04:55 Write the first measure, for the central value and add the central line
06:12 Add a Calculations table for the measures
07:05 Write the measures for the upper and lower control limits
08:10 Add the upper and lower reference lines
09:40 Add a vertical (constant xaxis) reference line to indicate the date of an important event
10:35 Conclusion. Next steps

More information on SPC charts
An SPC chart is based on a line chart. It records observations of a particular value at regular intervals typically hourly, daily or monthly. The chart has three reference lines; a central line, a lower control line and an upper control line
The value of the central line is often the average of the values. The lower and upper control lines are typically set to the average value plus or minus 2 or 3 standard deviations. The purpose of an SPC chart is to monitor a process to determine if it continues to operate normally – usually defined as observations staying within the upper and lower control lines. If points occur outside these line, this may suggest that the process is not operating normally and should be investigated.