 Right, welcome back. So I assume you have finished doing the exercise one So let us move on to the next the second part of the Demonstration for the event visualizer So let me share my screen again right So Now we know how to produce a basic visualization. Let's try to look at something different So let me open the favorite item That you're seeing here The test results So I click and open on open this test results and I'm seeing again another column chart So what do we actually see here? So we are seeing a column chart Which has three columns. So the first one the green one is inclusive blue is negative red is positive and Here We are seeing different values. So we have five positives and eleven Sorry, five inconclusives and eleven positives. So let us look at the configuration So this is coming from the COVID-19 case-based surveillance program And we are looking at the stage three, which is lab results So lab results stage is a repeatable stage and in that repeatable stage. We are looking at the data element Which is the lab test results, which has these three in the visualization. We are Asking to visualize, let me see what are the all the options which are having here We have many options, but out of this all these options. We have selected inconclusive negative and positive so because this is coming from a repeatable program stage and We have grown this visualization for events. It is possible that you are having Test results for the same person repeated again because it is a repeatable program stage Nothing is preventing you from obtaining multiple laboratory tests from the same patient So in case if we want to see how many unique Patients results are represented here We have one way of doing that. How we can do that is we go to this options here Right, so just please note the values here right now. So we have five inconclusives one negative and eleven positives and we go to these options here and What we can do is right now the output type has been configured as events But when we expand this output type, we are seeing multiple possible Different analysis that we can do so what we are seeing now is events Then it gives us options to the enrollment as well as track-tentative instance However, this enrollment feature does not really work because in the event visualizer. We cannot kind of analyze based Data from multiple program stages So ideally speaking what actually works is the track-tentative instance here So if you are using this output type, I advise you to use the event or the track-tentative instance Options so right now what is selected is events and if we select track-tentative instance, it should be Visualizing as the unique Patient reports Coming from this program stage. So I selected track-tentative instance and when I click on update You will see the values are now changing remember previously we had 11 positives and now it has come down to nine positives because it is only visualizing One it is counting one event From each of the patients right. So this is what it means by having track-tentative instance type of analysis here Right. So we are looking at unique patients test results Right, so With that I think Most recent event or Yes, ideally it should be the latest one that should be counting. Yes suppose one entity Gator one negative report at one time and one entity One lab report as a positive Yes to two event but for the same Entity what would be the result? Yeah, that's the thing So that's what I mentioned here when you try to take the track entity It is only it is only looking at one event from this entire track so because we can't do an enrollment type of analysis here and So so let me let me go back again So here we had two options This one is events and second one is track entity So here we are looking at out of all the events So just imagine if you get a table of as you correctly mentioned like so many patients are there Like it could be the same. I mean multiple reports from the same person. Okay, and then again, you also have You can also have one report coming from one person But ideally speaking here what we are looking at we will forget about the event Type right. We will be looking at track entity instance So for example, just imagine if you have a unique identifier for each track entity, right? Say zero zero one zero zero two likewise. So it will only count How many you have I mean like so if you have saved three reports from all of them It will only take into consideration one, right? And it will count how many unique track entity instances are there which has positive values something like that So this is not ideal as you correctly like both the questions are about like I mean what if it has multiple values Will it be shown here? No, it is not. So that's why probably there'll be like some enhancements come into this event Visualize application, which will provide you more functionalities to address these types of analysis But one thing I can mention is if you really want to see how many unique Counts are there for each different like I mean combining different data element values coming from events Tomorrow, we'll be discussing about program indicators. So there we have the possibility of defining it in such a way They are we I mean like I'm not going into depths of how to configure program indicators But there we can do something called filtering where we'll be able to kind of like define the positive values in the filter and Kind of do a track entity type or events count, right? So there we will be having more flexibility in producing Aggregate visualizations in a better way So I guess I'm not going to take too much time explaining what that is possible in program indicator configuration So we will discuss about that tomorrow, but this is one limitation. We have with this event visualize application at the moment right Okay, so With this this demonstration on a event visualizer comes to an end We have the exercise to that you can do but before that let me show you Let me do the recap where we have one slide So we'll be discussing briefly on this slide what we have discussed under event visualizer So when creating a visualization that uses events as the event output type Both event and tracker data handled in the same way When we are using event visualizer, so this is what we discussed a while ago the enrollment type of Output is not really working in this application, right? So this is one major limitation which we have in the current event Visualize application. We can't analyze enrollment type data So if we are thinking of one enrollment to a person where we want to kind of have Data connected from multiple stages, that's actually not working and then track entity instance output type Will only work with tracker data, right? It is the tracker data not really the event data because it is only counting Number of unique track entity instance that meet a given criteria within a single program So when it comes to our last example, it will only count the unique criteria is whether there is a positive I mean whether we have a lab result there and in that list it will only count the track entities the unique track entities Right, so we can't actually do a kind of granular Analysis taking into consideration the event data values. So these are some limitations which are there In this event visualize application as it is now, but still it is a very handy feature To produce some output specially based on event data Right, so With this we come to the end of the section on event visualizer So now you can do the exercise to which is a very brief one. So I hope you can Maybe take a maximum five minutes to do the exercise to and once you are done I think we can start the next session which is on maps