The Integrating tracker and aggregate data section of the DHIS2 Implement documentation has been updated to include the recommend use of the new Program Disaggregation. If you have been using the aggregate data exchange to map program indicators to aggregate data elements you should check out the new options available for v42.
Tracker and aggregate data integration - DHIS2 Documentation
Hi @DavidCKen
Thanks for the documentation it helps a lot already.
We have a fairly large implementation using PI disaggregations and the Data Exchange so it is really helpful.
What is still a bit unclear though is what is the best practice when setting up the Data Exchange Requests
What is best practice in terms of how many PIs you can add to one request? (I saw a bug that the exchange sometimes bombs out.)
What is best practice in terms of filtering? - Should you add PIs with the same filters into one request or can you mix PIs with different filters in one request?
It would be great if the Play instance has PI disaggregations and Data Exchange set up for replicating issues we experience and to have something to look at if this is possible.
Overall, I really appreciate the documentation though it helps!
Elmarie
I can answer this question: each PI is evaluated separately. It doesn’t make any difference whether the PIs in one Data Exchange Request have the same filters or different filters.
But then if you want to link it to a visualisation, a visualisation will only show up if DE from the same COC/AOC is in the filters right?
In the Data Visualizer, you can mix and match data items of different types (Indicator, Program Indicator, Data Element, etc.) and different disaggregations, and you will see the totals for each data item – as long as you don’t select any extra dimensions.
Then if you select an extra dimension, for example Gender, you will only see those data items that are disaggregated by a category combination that includes Gender. This can still include data items of different types (Indicator, Program Indicator, etc.)
When using Program Indicator disaggregation, the PI can be disaggregated by any of the categories that are either in its Disaggregation category combination or its Attribute category combination.
When using Data Exchange to output to a DE, you will want the DE to have the same category combination as the PI Disaggregation category combination. Then you can disaggregate the DE by all the same categories as the PI.
Note that you don’t have to use Data Exchange in order to get disaggregated visualizations from events; you can also get them directly from a PI that has PI disaggregation. The main benefits of using the Data Exchange are performance when the visualization is displayed, and that you can move the DE data to another system without having to move all the event data.