 This session will be an overview of the pivot tables. In this session, we will introduce the pivot table interface. We will start by going over a detailed introduction of selecting our data dimensions that contribute to our final table outputs. This includes selecting data, periods, and organization units in particular. We will go through a couple of examples showing you the creation of some different types of pivot tables. We will also discuss how the table layout affects our pivot table output. We will also describe the various pivot table options that are available and show you how to save table favorites and provide table descriptions. We will also show how to download tables to our computer. We will end the session by reviewing all the various concepts that we have gone over. Let's go ahead and get started with the session. In this session, we will go over the pivot tables. The pivot tables allow us to make dynamic tables and output them directly within DHIS-2. We showed you some examples initially when we did the DHIS-2 overview session. In order to access the pivot table application, I'll click where it says Search Apps, and then I'll click on the pivot table application. This is going to load the pivot table application for me to review. We can see on the left-hand side, we have a variety of different inputs. This includes the core building blocks which we discussed earlier. Our data, our periods, and our organization units. At the top, we have some additional configuration options. We can update, add a favorite, adjust the layout, and change the options, as well as options to download and embed. Let's discuss some of these features through this demo. There are actually multiple data types. This includes indicators, which as we identified earlier are different from data elements. Indicators are our calculated values. We have data elements, which are the actual raw counts that we enter through our numerical-based data entry. We have data sets that allow us to define characteristics associated with an entire data set. This includes items such as the reporting rate, event data items, and program indicators are used in event and tracker-based programs. We will discuss these two options later. For now, we will focus on the first three, including indicators, data elements, and data sets. In our first example, let's select a data element to review. We'll select the data elements as our data type, and then we can see that the next prompt asks us to select a data element group. In DHI's 2, we group our data elements together. This allows us to quickly find data elements that are within the same thematic group or within the same health program. This all depends how we define these groups, and we will show you how to create these groups later on. When I click on the prompt to select the data element group, a number of different groups appear. Let's work with one example, looking at maternal deaths within Turning Land. The maternal deaths data element belongs to the delivery data element group. I'm going to select the delivery group, and the data elements associated with that group will appear. We can see here I have the maternal deaths right here. We'll get into why these are named a certain way in other sessions, but we can see that the different deaths are listed in alphabetical order for review. In order to select this maternal death data element, I can highlight the data element and use the single arrow. We can see that this moves it from available to selected. I can use the same process to move it back from selected to available. I can also double click on the data element, and this will move it from available to selected. The double arrows take all of the data elements within the group and move it from available to selected. If I only want to select a subset of data elements, on a PC I hold down control and select the data elements I want to review. On a Mac I will hold down command. Then I can use the single arrow to move those data elements from available to selected. Since we just want to focus on one data element, let's select the maternal deaths data element. We've now selected the data element. This is the what aspect of our analysis. It is one of the three key dimensions that we discussed earlier. The next data dimension that we want to select is the period. This is the time dimension of this analysis. This will define what period of time our analysis will show. If I click on periods, we can see that there are actually two types of periods available for me to select. At the bottom I have what I refer to as relative periods. Relative periods are relative from today's date. This means that if I have the last five years highlighted and it is currently 2016, it will select the years from 2011 to 2015. Notice that the current year is not selected. There is, however, relative periods that indicates we could select this year and we could use this to select 2017, for example. This is an important concept as the relative periods allow for a lot of flexibility in our analysis. We'll get into this a bit more as we go through this session. We can also select a defined period. Here at the top we have a prompt to select the period type. If we choose the dropdown, we see the different period types that are available. If I select yearly, for example, a number of years will appear. I can then specify the years that I want to show in my analysis. For example, if I only wanted to choose 2011, 2012, and 2013, I can double click on those years to move them from available to selected. When you're using these defined periods, make sure to deselect any relative period that might have been chosen earlier. Otherwise, you will get a mix of both the predefined period you selected as well as the relative period. In this example, let's use a relative period. One of the advantages of using relative periods is that you don't have to continuously update any of the tables that you've already made. This is because the last four quarters that I've selected in this particular example will continuously update as future periods arise. This means that I can save the table, and as time goes forward, the last four quarters as represented on the table will automatically update. Because these relative periods possess a lot of inherent advantages, we will use them frequently in the analysis sessions. So I've selected my data, which is the what aspect of my analysis. I selected the period, which is my one aspect. And now I'm going to select the organization unit. This is the where aspect of my analysis. For now, I'm just going to select training land. We can see it's automatically highlighted. There are actually a number of different ways to select a different organization unit within DHIS2, however. If I did want to select a different organization unit, then I could go through this process and access the other organization units that are available. Just like in data entry, I can hit the plus signs beside my regions to expand my organization unit hierarchy tree. I can also click on the plus signs beside the districts to see all the facilities. We can select any combination of organization units to appear in our analysis. For this first example with training land highlighted, it will output the data for the entire country. Let's just go ahead and create a simple table and continue from there. In order to output the data, I click on the update button. Now we can quickly see that this pivot table has been created. You can see that the last four quarters from the current date are displayed. The organization unit, which is training land, is highlighted at the top. And the data element that I selected, which is the maternal desk, also appears in this pivot table. In this table, we have a duplicated total. This might not be so useful. We can see that the column total is quite nice to have as it shows the total over that period. But the row total is just repeated. Let's remove this from the table. In order to remove this, I click on options. You can see that a number of different table options appear when I click on the options button. We'll discuss these in a little bit more detail later on. For now, I just want to remove the row totals. We can see that underneath this data tab, we have options to remove column and row totals. Let's remove the row totals from this table. Once I've deselected that option, I'm going to go ahead and click on update. This removes that duplicated total from my pivot table.