DeepSee Analyzer is a WYSIWYG editor for MDX queries which are the data sources for DeepSee interactive widgets
Hello all,
Currently I am trying to create a pivot table based on a cube with several calculated measures that perform a distinct member count, as in https://docs.intersystems.com/iris20231/csp/docbook/DocBook.UI.Page.cls… . However, when I add these measures as the columns of the pivot table, the resulting row generation step can take a long time (at least five minutes). This includes row generation when performing drill-downs.
Hello community, I need to solve a complex but trivial issue.
Given:
Two tables "Comment" and "Post". Each one contains an "Author" field, which is essentially a user ID. In these tables, each user ID represents an author. The goal is to count all participants together and then group them by month, language, and other metrics.
The question is how to do this within the IRIS ecosystem. Is it even possible to take two tables, get distinct data from them and then combine into one cube?
I use $SELECT() in Architect to aggregate various data conditions into a single dimension.
I have a data table like this: id, user, userData1, userData2...
Where each user action is the %Integer ID of that action from some source. Then in expression field i use: $SELECT(userAction1:"This user action", userAction2:"That user action".) and so on, up to 14 conditions, excluding the default placeholder 1:"Other" (which is always empty because there is a condition with 100% chance).
Hence the question: is there a way to do that?
The goal is to get data (from half a thousand to 3-4 thousands lines) from DB, calculate standart deviation then use it as logical condition in analyzer.
For example IF std > custom_value = show_the_result ELSE null
There is a STDDEV(MDX) method used in Analyzer but it is a measure and it can not be used as logical condition (correct me if i am wrong)
And there is a Embedded Python with numpy, but logic behind STDDEV(MDX) and numpy.
Hi!
I have question about MDX functionality in context of IRIS Analytics.
How does IRIS MDX distinct selection works? Is there any restruqtion when analyzing strings? Like special symbols or length?
Here is an example
I have this data:
6 rows and 2 of them unique
Then we create data cube based on this model and examine it with Analyzer
Detailed listing
6 rows an ONE unique string. Which is obviously not true.
This happed only with string with symbols in it
My task is to get the right amount of unique strings