 Hi everyone, welcome to the final session of the day one of the Academy and in this final session what we are planning to do is to demonstrate all analytic tools in a nutshell how we are going to use the different analytic tools, few of which is our best demonstrated in the last session how we are going to use it in a practical setting. So for this purpose, what we are going to do is we are going to access one DHS to instance, similar to what you will be accessing for doing the exercises. So, to give you a bit of context of this DHS to instance, this DHS to instance is the HMIS or health management information system of one country imaginary country called training, right. So, just assume that all of you are the health managers of the HIV program of this country called training. Okay, so what we are going to do is like you may have most of the countries like most of the health programs. From time to time, we want to assess how ours is how our health program is doing. So for example, we want to know how this HIV program is performing to do this, some simple thing that we can do by sitting at your office at national level is to do something called a desk review. So what I'm going to do now, what I'm going to demonstrate now is how to do a basic test review by using DHS to. Okay, so for this purpose, let me now share my screen and log into the DHS to instance. Okay, I hope you can see the DHS to instance now. So what you are seeing here, I have logged into this instance from my personal account, right. And in this instance, I'm seeing right at the top here I'm seeing lots of dashboards. So for a brief, briefly mentioned what dashboard is we'll be talking in depth about what these dashboards are in time to come. So what I want you to do you want to do is don't just follow the same steps that I'm doing just observe how we actually in a practical setting using different analytic tools available in DHS to perform a basic desk review. Okay. Right, so I logged into training land as a country, or national level user, and because I'm a national level user, the usual scenario is that I'm going I'm going to see lots of dashboards as you can see here I'm seeing around 20 dashboards. But mostly for this desk review I'll be focusing on this particular dashboard here which is HIV district. It's a new to right. So in this situation like because I'll be most of the time using this dashboard. I would like this to come right at the beginning of the list, right so that I don't have to go browser some I mean, sometimes it may go to the bottom of the list and it's very difficult to find to find it. So what I will do in this instance to make it come right at the top is to make is do something called star right so when I click on this star button, you can see it has been starred, and that particular dashboard comes right at the top of the list. Right. So let's now focus on what we have in this particular dash. So it is for the HIV district sub national level two, and I'm seeing some charts, there are some tables, maps, things like that. Okay. So, like, I mean, I just want to know I just want to ask a question, like what is this data representing. I mean, in, when you are learning DHS to I guess you must be aware that the DHS to we can have different old organization unit level. Right. So for example, we can have national orders. The second could be regional district health facility right from training land which is the national level. Right. Okay. So, right. Now, something I'm going to do is like most of the time I can see data from national level and just by looking at national level we will not be able to understand the discrepancies of data, which is taking place at lower levels. So to do that, without going into, I mean, like, you must be aware that we can drill down and notice we can open this each of this widget on separate modules, without doing that, from the dashboard itself, I can do something called application of filter. So when I do that, the data will be filtered data and the visualizations that you see in this dashboard will be filtered based on the filter that you set here. So let me add organization unit and a period filter. So right now it is showing data for the training land for last 12 months. Is that clear? Okay. Let me apply a filter. So first of all, I will filter data from here to show at animal and food region and click on confirm. Right. And you will see that now the data is showing animal and food region. So let me apply another filter. So that I'll be seeing data from this month. Confirm. Right. Now that you can see there are two filters which have been applied. One is organization unit filtered for the animal and food region, and this month. So what we have done is, right, just by sitting at national level, I have just, you know, like not permanently changing the dashboard transiently I have set up a filter so that all the dashboard items in this dashboard are filtered based on the organization criteria and a period criteria. Okay, you can see this. Right. Let us now focus on one of these dashboard items. Right. So let's focus on the first one, which is HIV cascade this month. Okay. So in here, when we just compare, we are seeing three data items which is HIV test positive, HIV, new one ART and last 12 months for animal and food region. Just by a comparison that I'm seeing that there is a issue like there is high reporting of HIV positive tests in this animal region, and I'm a bit concerned about this thing. Right. So what I can do is just like what you are doing on Facebook and other social media platforms, I can do something called I can open up this option here by clicking here called interpretation and detail. Right. And what I can do is, I can just make a comment here so that the person who is in charge of this region, he will have, I can communicate to him here that you have to look here you have to look at this data there is something wrong with this data. Just have a look at it. And let me know. Right. So I know that particular users name is admin. Right. So let me start. I just want his attention also so what I will do is I will start typing admin. Right. So there are a couple of admin users. So this is the one I'm interested of admin district. Right. And I'm going to basically what I do what I'm going to do is, I feel that test results are usually high for this month. And I want to know whether he has performed data quality reviews for this information right. So I'm going to type here, without taking too much time I'm going to copy paste right I'm saying admin district. So this positive seems unusually high this month have you performed data quality reviews for this information. Right. So I just type it there, and I click on save interpretation. Okay, so you can see now, I have this chart, and there is this start chart description, and I have type of comment here, which needs to be addressed by this admin district user. Okay, great. So let me now try to log in from admin district user and see what happens. Okay, let me open that account in a new dashboard. Right. And let me share the screen again. So right now, I'm now logged in from a user called admin district. Right. So from this admin district account I logged in, and let me refresh. Right. And now, when I refresh, you will see that as soon as I log in, there are two buttons here. Right. One is called interpretation. One is a message. So, so let me click and open this message and see what happens. Here is one system message. Right. I just clicked here and we have a system message. Right. And it says that you were mentioned in following interpretation. And it says, like now for example, I logged in from other users account and I typed something, and that message appears as a system message. And also in this interpretation, when I click there, it will also also show that there is a comment down to see, there you go. Right. So here it says admin district dispositive seems unusually high this month. Have you performed data quality reviews for this information. So what happens is this created interactivity between the users of the same system. Right. So you can communicate with the system, not only this, let me log in from the email account of the admin district user. So I logged in from the email account of the admin district user. And you can see this email here. Let me open that email. Right. So you see that when I typed interpretation in the particular dashboard and mentioned that particular user that user is getting an email in his email account and also is getting notifications in system messages as well as interruptions. So this is a fantastic way of communicating while you're performing a desk review. Right. Let me go back to my previous account. I hope everything is clear up to this point. Okay, so let me now remove these filters I just click on remove and remove and back at this previous original dashboard right. Right. Okay. So let me go down and I'm actually see I'm now going to focus on a few other items. So let me go look at this particular pivot table which is ART performance. Okay. So what I can do is I can basically, I mean, this is a bit of a crowded table as you can see here. So to have a better look at it, what I will do is I will just click here and try to open it in the data visualizer app. Right. So from the dashboard I'm going into this data visualizer app and I'm going to open the same pivot table in the data issuers app so that I can, you know, do some tweaking and have a better look at the information which is there. Right. So the first thing I want to know is like I'm a bit concerned about this HIV ratio of newborn ART to newly diagnosed. Right. So here I'm seeing a lot of figures based based on the district level. Right. So what I can do is I can quickly have a look at which organization unit or which district district was performing birds. So to do that, what I will do is I will just click here so that data is getting sorted. Right. So just by looking at it, I can see that this is the bird district here is the verse performing district. Okay. And then