 Let's go through an additional example looking at the desegregated categories that are available for different data elements So what if we have a data element that's separated into desegregations? This could be for example a data element that collects information on male and female Or it could have certain age groups that are attached to it Let's take a look at this concept in a bit more detail Here in my data, I'm going to work with a data element Let's work with something from HIV Aside the data element group. I have this option to select totals or details The total is a summation of the data element including its individual categorizations So for example, if I have a data element that's broken down into male and female What I see in the total is the sum of male plus female If I click on details then I begin to see different categories associated with my data elements You can see the different desegregations such as female and male start to appear If I scroll down a bit more you can also see that there is sometimes multiple desegregations that are associated with one particular data element For example HIV test performed has both the sex which is male and female as well as the service type This is where the test was performed including TV other or PMTCT Let's have a look at the HIV test performed for these individuals between 15 to 19 years of age We can select these groups by double-clicking on the individual items that appear So if I want to look at the males, I will just double-click on those particular data elements We then go to our periods just as before Let's deselect the last five years and look at the last year for my organization unit I'll just select training land I'll check my layout very quickly I've only selected one organization unit, so it's okay if it's acting as the filter My rows are my periods, which is last year and my data is the data elements that I've selected Let's go ahead and update the table Here we can see that this HIV test performed data element is not broken up into desegregates including male other male PMTCT and male TV But this is not always ideal If I go back to the data tab I Can see there are two desegregates associated with this data element male and other Right now. There's no way for me to select only male cases or for example other cases that include both female and male cases together We can see that the female cases are completely separate in this example In those cases, it's often better to add these desegregates as their own data dimension to the table So let's go ahead and go through an example, which allows us to accomplish this We're going to change back from details to totals See here that the data element I was working with HIV test performed 15 to 19 years attached to this data element is the desegregations of male and female which includes sex and Other PMTCT and TV, which is the HIV service if I scroll down I Can see that these desegregations are available is data dimensions This allows me to add these as additional dimensions to my analysis Here I can click on gender you can see that male and female are available I Can use these double arrows to select both male and female I? Also have the HIV service available. You can see here that PMTCT TB and other are present Let's use the double arrows to move these from available to selected Back to my data. I just want to make sure that I selected the data element that I'm working with So I will double click on this HIV test performed data element now that I selected my data element and my periods Our organization units are still maintained from our previous selection Let's go back to the layout and see what's happened Now I can see there are additional dimensions for the gender and HIV service We can then choose where these appear We can filter them out completely or have them appear separately in either the column or row of this particular table For example, if I move the HIV service down to the row I Can filter out the period since we're only looking at one period and I can leave gender in the column and go ahead and click on update Now we can see here the HIV service appears as our rows the sexes for male and female appears in our column We can see that this provides a lot more flexibility in our analysis when we add in these desegregations as data dimensions Rather than using details Just be careful when we do this We have to make sure that we're adding desegregations That have data attached to the particular data element that we are working with For example, this data element is already separated into 15 to 19 years If I try to select an age group Say less than 12 months and 12 to 59 months It's not going to work I'll select those age groups and click update You can now see that no data appears This is because there's no actual data attached to these particular age groups for this data element If I remove these and then click on update Now I can see that the data appears correctly Let's add a bit more dimensionality to this analysis We can add in the facilities so we can see the data broken down by facility We'll go to organization units Change our selection method to select levels And select the facilities as the organization unit level Let's check the layout to make sure everything is in the appropriate place You can see the organization units are currently filtered out. Let's move those down to the row so they will be displayed I'll move the hiv service to the column and I'll filter out the data as I'm only looking at one data element When we update the table, we can see that there's quite a bit of data available broken down by these two desegregations