User guide
...
A new
...
action named Analytics is added to the Export menu in the Issue Navigator.
It exports the current JQL into the Data Analysis console:
This creates a Mondrian schema on the fly which is loaded into the console:
Choose a cube to start your analysis
Drag Dimensions into the Rows and Column boxes and Measures into the measures box.
Click on the Save button to store the analysis report on JIRA for later use.
and provide a friendly name
| Warning |
|---|
Currently blank spaces are not supported! |
...
NOTE: You can directly access to the schema listing at any time by copying the URL below on your browser:
<JIRA_BASE_URL>/secure/KintosoftMondrianSchema.jspa
Click on the Analysis link to load the schema into the console (Saiku). You can also click on the Open folder icon to load previously analysis stored associated with the schema:
Analytics Client console (Saiku Community Edition). Select the Jira Core cube.
This will load the Cube with its Measures and Dimensions:
Expand the Issue dimension and click on the Key to add as Row:
The click on the Issue Count measure. The pivot table will count the issues for each dimension. This is a quite obvius measure: you got 1 issue per key!
We will neasure something more useful now: issue status vs issue type. Revove the key dimension and add the Status as rows and the Type as columns:
In the eaxmple above, there are 8 stories taht are already done. But what are those stories? Click on the Drill action from the top bar and then click on the cell to see its detailed data:
This will bring up a dialog. Expand the Issue dimension and select the Key option:
Click on the OK button:
The issue key for the eight done stories are listed!
Easy no? But what is it happed behind the scene? You have been building a MDX query behind the scene! Click on the Show MDX button:
The MDX performed behind the scne is displayed. Copy it into the mememory for later use:
| Code Block | ||||
|---|---|---|---|---|
| ||||
WITH
SET [~ROWS] AS
{[Issue].[Key].[Key].Members}
SELECT
NON EMPTY {[Measures].[M01- Issue count]} ON COLUMNS,
NON EMPTY [~ROWS] ON ROWS
FROM [JIRA Core]
WHERE CrossJoin({[Type].[Type].[Story]}, {[Status].[Status].[Done]}) |
The good news are that you can build awesome complex MDX queries in a visual way (with darg and drop) without any knowled about the MDX language!
Actually the cube is volatile and it will be lost if the console is abnadoned. You can save it for later use. Click on the Save button and provide the Demo name for the Catalog (a set of cubes grouped in a Mondrian schema):
Clcik on the Save button to close the dialog. The catalog is now saved in the Jira database!.
Click on the Manage cubes button to list the saved catalogs in Jira:
A new page listing all the saved schemas (catalogs) is displayed. Click on the MDX Console button:
The MDX console is opened. Type the
SHOW CATALOGS;
instructions to list all the saved catalogs:
Type:
USE [Demo] ;
to load the cubes in the Demo catalog.
Now, copy&paste the MDX query that you built in previous steps:
The eight closed stories in the JQL are listed! You got the same results than from the Analytics client (Saiku). You have seen the XMLA protocol in action. It is possinle to connect to Jira to list the saved catalos and perfom MDX queires on their cubes. The MDX consle above is an example of a XMLA client tool. But you can use any third party compatible tool. You might want to use the Arquery's XMLConnector for Excel and connect to Jira from Excel to perform analytics.