Documents for QlikView related information.
How do we create a simple Control or SPC chart in QlikView?
You can see how to do this in the attached Application and Document.
I have also placed a short blog post on the QlikView Design Blog.
Thanks for the post. It is quite informative and will help many developers.
HI Adam. I wonder if you have time to take a look at a recent query i have put on Qlik Community regarding advanced control charts? http://community.qlik.com/message/446647#446647
Hi Adam, re the formula
[Mean Process Time] + Deviation.
I can see where [Mean Process Time] comes from - I did not realise you could re-use a formula this way.
I cannot find where Deviation comes from (what is the formula behind this?)
Thank you I am working my way through your example.
I have a bar chart , and this is my expression in the chart
Expression : COUNT(if([SLA_DAYS_PAST]<=0,[PPL_ID]))/COUNT(if([SLA_FLAG]=-1,[PPL_ID])) (sl_flag_past<=0 indicates compaints that are taken care of on or before due dates) and (sla_flag=-1 indicates all the closed complaints)
Calculated Dimension : if(CLOSE_DATE>=vMinDate, MonthName(CLOSE_DATE))
Now, first of all I need to build an SPC CHART, so I have calculated the average value using this expression:
Average: COUNT(TOTAL <PPL_ID> if([SLA_DAYS_PAST]<=0,[PLL_ID]))/COUNT(TOTAL<PPL_ID> if([SLA_FLAG]=-1,[PPL_ID]))
Now to calculate upper and lower control limits, i need to get the standard deviation:
uppercontrol_limit : average+STDEV
So, I need a formula to find the STDEV. I have a dead line, and i really appreciate your time.
We held an on-demand session with National Health Services (NHS) about how they built and leverage Statistical Process Control Charts (SPC) and Run Charts in QlikView and Qlik Sense. johnmackintosh covers these topics in depth:
Be sure to check this out: https://youtu.be/OVkUOTA-GQw
Thanks for the post.
Just wanted to drop a quick warning that the control limits in the sample document and chart above are incorrect. They are based on the standard deviation, which will typically inflate the limits. The correct way to calculate limits for an X chart is to use the mean (or sometimes) median two point moving range. I have examples of this implemented in Tableau for anyone interested. And note that Tableau also has examples up that also incorrectly use the standard deviation. The best article on how to calculate the limits correctly is here: https://www.qualitydigest.com/inside/twitter-ed/individual-charts-done-right-and-wrong.html
We have also released a Control Chart extension for Qlik Sense. More information and a 60 day trial can be downloaded from here.
Key features include: • Outliers Highlighted • Runs ‘above’ and ‘below’ the average highlighted • Trends up and down highlighted • Moving average based on Runs and/ or Trend triggers
Key configuration options include: • Customise Labels for Dimensions, Measures and Rules • Customise Line and point style for Dimensions, Measures and Rules • Pick the number of points to set the highlighting criteria for both Runs and Trends