 To open up an existing pivot table, you have to go into File, click Open. Of course, you could find a lot of visualizations that are available. By telling if it's a table or a chart, and of course, which type of chart, you could clearly see from these icons. I'll go and look for HIV tests performed. Go and open HIV tests performed by subunits. If you look at this pivot table, you could clearly tell that the whatever figures that I'm looking at here, one is these are HIV tests that have been performed which that marks the what part. But it's not just the HIV test performed. HIV test performed as well as the HIV test positive, and of course, the HIV test positivity rate. What does that mean? Let's go back to the data dimension. If you go back here, I would see three of my items selected. How are these selected? One is first of all, you need to clearly understand the type of, the data type that you want to look at. Under the data type, we have like five types that are available. We have the indicators. As I said, these are more of computed or calculated values, but also we have the data elements. These are more or less of the raw data, the actual figures that have been captured in the data collection form, but also we have the data sets. When you're looking at the data sets, it's more as to sort of look at the reporting rates and the actual reports that have been submitted based on the data sets that are available in the system. Also, we have the event data items, as well as the program indicators. These are mostly and usually used when you're looking at the individual level data. It's more of tracker data. So with HIV tests performed, positivity and rate as well as the HIV test positive, the first I'll go with data elements. Once you select the data element, you could have a very huge database which captures a lot of information. So just by selecting data elements, that means you'll be given the list of all the data elements that are available in the system. That could be very cumbersome in case you need a very specific data element. So the better option would be grouping. We have data element groups. This is very important, especially when you're doing the customization, because this is now where you could see the importance of having these data element groups. They really help when it comes to analysis. So with the HIV test performed and HIV test positive, all those available under the HIV data element group. So once I select this, you could see at least I have some of the data elements that have been chunked out. I could scroll because I have few in the list. Alternatively, I could also search. So just go with HIV. If you know the name, you could just search. Sometimes if you don't know the name, you could use the keywords like HIV. So if we had a lot of them, it will also trim down and have give you the list that at least have this kind of keyword. So my interest is on HIV test performed, as well as the HIV test positive. So I'll select that. For them to be selected, you have to make sure that they get dragged into the other window under the selected items. So I'll select that. Of course, I'll deselect those. So those are the data elements I now have. But remember, we said our report needs to have the HIV test performed, HIV test positive, as well as the HIV test positive positivity rate. So the HIV test positivity rate, that it's a different type of data type. It's not a data element, but rather an indicator. So for me to be able to find it and select it, I'll have to go back here and change the data type. So instead of data element, I'll have to say indicators. So once you select indicators, the process is more or less the same. We have indicator groups as well, so that they usually help in terms of when you're looking at, you want to retrieve the specific indicators you want to use for analysis. So again, my indicator, the HIV positivity rate falls under the HIV indicator group. I'll go and select HIV indicator group, and I could still see a couple of them. So if I don't want to go through one after another, I could just search, saying HIV test positivity could see, at least I could have few, which I could easily look at and be able to select what I intend to use. So here is my indicator, HIV test positivity rate. So by selecting that, that means I have my three watt dimensions, two data elements, and one indicator. So what do I do next? So usually you have two buttons here at the bottom of this data item window, we have the hide as well as the update. So the fact that we have not yet defined the period, as well as the organization unit, we recommend to use hide instead of update. Because if you click update, that means you'll be sending a request to the server, and the system will start now retrieving, processing such kind of information, and it will be a misuse of resources. So you'd rather click hide, then go to period, if you click period. At the moment by default, we have this last 12 months. So usually most of the time, we have such kind of period already selected by the system based on the configuration that on the system settings, where we define what would be the default period. But it's not necessary to be last 12 months, sometimes could be last six months, last three months, it all depends on what has been configured under the system settings. So I'll go with 12 months for the first time, then the organization unit. But before I get to organization unit, remember we said we have two category of periods. We have the relative periods, we have the fixed periods. What's the difference between these two periods? I think the names portrays a lot. Fixed periods, these are usually the static periods. No matter when you're pulling the data in the system, if you use fixed period, it's always going to pull the exact same information. For instance, I'm in 2022 March, if I say I need data for February 2022, if it's 10, it's always gonna give me the data for that particular period and it's 10. But if I move to April 2022, and I say I need data for February 2022, again it's always going to bring me the same information, right? Because what I'm trying to ping in the database is the fixed period, it's static, it doesn't change. And when you go to fixed period, of course it also accommodates different type of periods. That could be months in terms of, if you want to analyze data in monthly basis, if you want them in daily basis, or if it's weekly, yearly, quarterly, it all depends on type of data they're analyzing. But once you're selecting the period type, you need to be very careful because you cannot analyze data in weekly basis while that data is captured into the system in monthly basis. So how DHS2 works, you could always go up but you cannot go down. So it's more less of a bottom up. So that is one type of period. We have another category, which is the relative period. And with relative period, this means that whatever that you're selecting, the system will always check your current date. So if I say last month, before the system pulls the data for last month, it has to check your current date. From your current date, what is the last month? So if it's March, the last month, it's gonna be February. But if I move to April, that means the last month is gonna be March. So that is in terms of months. But again, it's not just months, but we also have different type of periods. We also have weeks, we have days, we have six months, quarters, and of course, years. I hope that is clear when it comes to the different period categories supported. So we have the what, we have the when, but where is the data coming from? That takes us to the organization unit. And with organization unit, from here, you could see we have different ways on how you could select these organization unit. One could be the user or unit. And by using user or unit, you are basically telling the system to pull the data with respect to the organization unit that the system user has been assigned to. Because usually when you configure the system accounts, they have to be attached to the organization unit. So when you get into analysis part and say I'm analyzing data and by user or unit, that means the same information, if it's accessed by a person at national level, that person will be able to see the data for the entire nation. But the same if it's accessed by someone at the regional level, that means that person will only see data for regions. Same applies to district as well as to facility. This depends of course with the hierarchy level that you have in your DHS to system. So data review also have this user sub. And for instance, for this visualization, we have, it has been selected by user sub or units. What does that mean? It means that with whatever level that you've been assigned to your account, the data is going to be pulled by the, just the second level below the level that is attached to the account. For example, if my account has been assigned to training land, which is with assumption that is the entire country, the national level, by using sub or units, then the data is gonna be retrieved in terms of the region because that is the level below the national level. We have regions and it's only two regions, which is the animal region and the food region. So if my account was assigned to regional level by using user sub or unit, once I pull this kind of information, it's gonna give me the data in terms of districts because that's the level below the or unit that has been attached to my user account. So the sub-sub, which is gonna be the children of the children. So if it's at regional level, then the sub-sub is more or less the health facilities. So and when you're configuring a visualization that it's intended to be used with different users at different levels, we recommend you use this kind of organization unit selection. Why? Because it's gonna give people chances to see data with respect to the level that they're supposed to see. Instead of going into the system and create data for national team, go back again, create the same data but regional level and again the same information for district level. So just to avoid having a couple of table tables with the same information but different levels, it's recommended to use this kind of organization unit. So I've selected the what, when and where, which is the sub-user. If I click update, then this is how the visualization is going to look like. But the table has been arranged in this manner just because I have this data assigned at columns and I have organization unit at rows and I have period at filter. And you could clearly tell that with columns and rows, you could have data specifically for each item. But in filter, it's always going to give you the sum up of all the information. What does that mean? It means that for instance, if you look at filter, we have last 12 months. But whatever figure that I'm seeing here, this 17.5% that it means it's the percentage of all the last 12 months. But if I want to see the percentage of each months within the last 12 months, what am I supposed to do? Now this is the whole concept of the layout. You need to play around with this layout so that you could have your information well arranged in a manner that you want to see your information. I'll just give a quick, I'll just reshuffle these dimensions. So instead of having organization unit, I mean periods and a filter, I'll just drag them and drop them under columns and swipe the data under filter. So if you click update, I want us to see what could be the changes. Something is wrong because it's saying that you cannot have indicators in data filter. So you could see that even the system, it's still intelligent enough to tell you what sometimes should be allocated where. So if I want to see these information in the granular months for each month, what can I do? I can also try to reshuffle this, take the period and assign it, let's say under what? Under columns. So that means my table will have the data and period arranged in a column, but the organization unit will be arranged in rows. If I click update, you could see how data gets to be arranged in a table. So from here you could see how many HIV tests performed in all the last 12 months by each region. And of course the positive test again more or less the same by all the last 12 months by region and again the positivity rate. So this is how you do the layout arrangement. But that is in terms of dragging and dropping these things to be in terms of rows or columns. But what if the same information, I need them in terms of more details in terms of let's say districts of a certain specific region. You could always go back to organization unit and of course I could use the parameter at the left panel or I could use whatever that is available in this layout. So I just go there, click organization unit. So to be able to specify the exacty the exacty organization units that you want, you'll have to first of all reselect these sub. Otherwise, if this is still selected you cannot do any other specific selection because as I say this is by automatic if you want select this the system that understands that you need data to be rendered in terms of user of units. That means you cannot further do more specifics to this type of organization unit selection. So I'll have to go deselect that. And I could have two ways of selecting districts. One could be going through the hierarchy for the entire training land hierarchy and peak specifically. But that is only possible if you have very few districts. I assume you have a hundred of districts going through this entire hierarchy. It's gonna take you long and it's very tedious. So alternatively, you could say, okay, I need data by district all the districts within let's say animal region. If I click and I have to select animal region then I have this tab here say select level. If you click that, since you need data by district you'll have to select district. So by selecting that and click update that means the system is going to give me the data for all the districts that are within the animal region. So if I click update, you could see now my data has been further desegregated in terms of district within the animal region.