 In this session, we will demonstrate how we can analyze individual event-based data using our routine analysis apps. We will start the session by discussing the concepts of program and combined indicators in a little bit more detail. We will then analyze individual-based data within our routine analysis apps. We will then use these concepts to produce aggregate data based on the individual-based data we have entered within a particular program, within our routine analysis applications. We will also go through an example where we analyze aggregated data based off individual program data, together with data that we have collected through our routine aggregated processes. Let's go ahead and get started with the session. In this session, we are going to discuss some methods to analyze event and tracker data. In order to do this, we will use the analysis applications that we should be familiar with by now. We'll start by going into the pivot table. Within the pivot table, we previously demonstrated the use of indicators, data elements, and data sets. Let's have a look at program indicators to start this example. We will use the CERA program that we demonstrated in Event Capture to demonstrate a couple concepts. Program indicators are a little different than the indicators that we have looked at previously. Program indicators calculate aggregated data values from individual events that are entered into DHIS2. We can see an example of a program indicator, the number of facilities offering antinatal care. This program indicator is calculated by taking the number of yes responses to the question, does this facility offer antinatal care services? Remember, this survey is performed by facility. What DHIS2 is doing is counting the number of facilities that answered yes to that question and giving us the output. We can also do the same for the number of facilities offering family planning services. On the survey, there is a question that asks whether or not a facility is offering family planning services. DHIS2 is going through each individual survey result and adding up the number of yes responses to provide us with an output. We then go through the same method of selecting our other dimensions. So we select our period and we select our organization units. We'll select the district level in this example. We'll just change our layout. We'll filter out the period since we only selected this year. And we'll click on update. What we see in this pivot table are the aggregated data values which link to the individual responses within the CERA survey. In this example, for the number of facilities offering antinatal care within bird district, we have a value of 7. This means that when the survey was done, 7 facilities responded yes to the question of does this facility offer antinatal care. The same is true for the next program indicator, number of facilities offering family planning services. In bird district, we have 4 facilities that responded yes to the question of whether or not the facility offers family planning services.