 And of course there are multiple ways of doing it. So for example, let me share my screen again. You must be also seeing a plus mark next to the direct messages here, right? When you click on this plus mark, it will open onto your right side, a list of all participants who are in this workspace and you can select a person's name just by, you know, you can click on his name or else you can type at mark and then type that person's name, right? So that's how we do it. Say for example, if I want to message Rajiv, I just type at Rajiv, right? And then it'll be a direct message that is opening with Rajiv and me. Say in case if I want to create a group, right? Group passing like if you want to, like for example, I think it is on the eighth day, we have a group activity about interpretations. So if you want to create a group amongst yourself, discuss something, you can add multiple people, like I'm now randomly trying to send some messages, so I will add Rajiv and also say for example, yeah, Alex, right? And I do like this and I say hi and this is in fact a group chat between Alex, Rajiv and myself, right? So that's the next way of doing it. So like you have multiple methods, the first method I displayed was that you can search the person's name here, or else you can click on this plus mark here and then select the people you want to message. If it is just one person, just select that person's name and then send a message. So if you want to add multiple people, you can select or you can start typing with at mark. I hope it's clear. If you all have having no other questions, I think we can start the next session, yeah, all right. Also, Saurabh? Yeah, thanks so much. I'll share my screen and start the next session. I hope my screen is visible. So yeah, so during past few years, a lot of enhancement is happening in the analytical features available in DHIS too with each release. So before we start the core applications and the sessions related to that, we thought it's good to kind of take you through to the new features and the enhancements that have happened over time in different versions in DHIS too. And there we stand today with respect to the functionalities available so that when we discuss these apps broadly, you kind of have a background to these apps and the functionalities which have been developed over the past few years. So as we all know, most of us know that in DHIS too, there are four core analytical tools used, the dashboards. Then we have data visualizer for our charting needs and pivot tables are also not part of the data visualizer app and the maps application. So with each release of DHIS too, there are updates made to these tools and in this presentation, we'll go through the main updates that we've seen lately. So after 2.28 in 2.29, major revamp happened with the DHIS to dashboards and the analytical applications. The dashboard stack was totally rewritten to kind of build it on the new React framework and which kind of made it more dynamic in terms of utilization and gave many more options available on the dashboards for the users to configure them in a better manner and make it more presentable to the end users and make it more attractive in a way with different features which have just been evolving from version 2.29 onwards. So with version 2.29, the dashboards allowed the custom sizing and location of the dashboard items where we could size the dashboard items based on our need. We could scale them up for full scale width or we could make it more concise to kind of fit more objects together so that we have a collection of items which could kind of depict a story, depict a picture for the end user to gather as much information as possible. The maps dashboard items were kind of extended to be shown as in a full screen mode. So there is a full screen option available, the icon which you see here. So the map can be shown on the full screen. Then there were rich text formatting added to the interpretations, the comments and descriptions so that they could be seen on the dashboard at the onset itself on the dashboard page. You could see what interpretation has been added for this particular map who has created this particular analytical object and when it was created and when it has been last updated and how many views have been there and what was the objective behind creating this respective dashboard item. From the dashboard itself, you could easily move between the different visualizations available in the HS2. So if I have created a map item here and that's the default mode of presentation which I have on the dashboard, I could use, I can kind of switch the same dashboard item into a chart or a table. So from the dashboard itself, I'm able to change the visualization type and to see the same data in a different format based on the layout and the dimensions that I selected while I was creating this map, the same apply to the charts and the tables depending upon the structure which is defined by you. Then there are filters available which kind of allow you to add different filters based on the periods and your geographic hierarchy, your organization unit hierarchy and then the dimensions of data which might be applicable to the dashboard which you have created. So you could apply multiple filters on the dashboard and all the corresponding dashboard items will get filtered based on the dimensions that you selected on the top. So for example, if you're talking about seeing the data only for a specific period and a specific district or a province, then you can put those filters here and the entire dashboard will become a dashboard which is filtered to the period that you selected and the province of the district that you selected. Or if you want to see data by different dimensions that you have, say by ownership of the facility or you want to see by type of the facility or you want to see by the residence type, the urban or rural, then wherever these dimensions are applicable to that data, the filters would automatically apply and dashboard would convert into kind of a filtered version of the entire stack of data which are populated on the dashboard. Then on the dashboards which you're creating, you can always put a star mark on the dashboards so that your favorite dashboards are always stacked in front of the queue and you can have, of course, more than one dashboard which is available, but when you star mark a dashboard, you kind of mark that dashboard as a favorite. So your favorite dashboards will always be stacked up in the order and your rest of the dashboards get followed thereafter. Then there were navigation changes which were made so now if you want to further explore this particular map into the Maps app, then you have a separate option to kind of open the visualization item into the core app in which it was constructed. So since this map was built using or designed using the Maps app, then you have an option to open this particular map into the Maps app to either make an update to the map or add further disaggregations, maybe change the legend, things like that. So you can go back, update this and save so that your most recent version gets updated on the dashboard. The most in-demand feature from many of the organizations and the ministries of health which is using DHS was to have the ability to print the dashboard into a PDF or into a printed version which could be shared with the users or could be kind of used in a report as an extras or things like that. Any external use cases which you had with these dashboard items. So now there are two options available. One is you can either have one item per page, one dashboard item per page in the print file that you generate or you could have the dashboard layout as is. So a frame of that specific dashboard will become part of the one page of that respective PDF file which gets generated or the printable file which gets generated. So you can take printouts from the dashboard directly. So this was kind of most requested feature which is available now from version 2.35 onwards. So this is your print preview. So based on the way you have designed your dashboard and the right fit of charts on a single print area, the system generates a print preview for you where you can take a print and also download a PDF copy of the dashboard itself into different pages. The data visualizer has been around a long time and it has evolved over time. So a new visualizer app was introduced in version 2.31 where there was a new interface for selecting chart type dimensions and setting your layouts. Now the layouts are always persistent over the chart. Earlier they were hidden in the layout option so you had to click every time to check the layout but now you see the layout always on top of your chart and if there's any change required you can do that particularly. There were new chart types introduced based on the requirements which came up from the ministries of health and the partner organizations who have been using DHLs for their analytics and data management to have air over air bar in line charts to kind of see the performance of that particular indicator in the month over a period of years so you could compare the performance and the trends air over air on a monthly basis. Then there was also requirements to see the single value charts where you could just see the summary of the data both as raw and cumulative forms so that a snapshot could be taken and this has been extensively utilized for the COVID systems where you just create a grid of data for your all identified positive cases how many recovered, how many are active cases, how many deaths so the single value charts kind of gave you a quick snapshot view of the latest data and kind of helped you to have a quick summary of data available right at that moment as you open your dashboard. Then there were also requirements coming in to create combination charts in terms of supporting multiple accesses and kind of merging two different chart styles together in the same chart so from version 2.34 we started with supporting two access chart where you could plot two indicators of two data elements of two different accesses or if you wanted to include your raw data and your coverage indicators on the same chart then you could use them on multiple accesses now from version 2.35 onwards you can have more than two accesses up to four as of now and you could use a combination of chart types you could use on the same dashboard on the same visualizer item or the chart item you can use a bar in the line chart to show two different indicators and you can see the numbers and your coverage proportions together on the same chart so those trends can be plotted now pretty easy. Then there were also requirements coming in to kind of support multiple categories on the same chart earlier you could either see the monthly distribution of urban cases or the monthly distribution of the rural cases but now on a single bar diagram you could compile information for multiple categories so you can group your urban doses given for example in urban areas in one slot and your rural areas in the next slot so that you could do a comparison between the different categories in which the data is collected so now two category charts are supported from version 2.35 onwards and you can access four accesses to your charts Gate charts were available since version 2.31 but then earlier they were with the same color but now they are supported by legends and you can add your target and your baseline lines as well so on a gate chart you can put your baseline that this is what is the bare minimum you're looking at and this is your highest target that you're looking at so this could help you to see what indicators are covering your baseline and what are kind of crossing your target which you have said then on single value charts which kind of came up in version 2.33 they did not had support for adding legends or colors but now from version 2.34 onwards they have the option to add colors to them so they kind of were used extensively for the COVID grading where we kind of were able to put our positive cases in red we were able to put our active cases in orange and recoveries in green and deaths in gray so that we could kind of symbolize the data with the different legends which are available in the system there have been kind of attempts towards making the system guide the user that what could be the potential recommendations with respect to the data elements of the indicators the person has selected so for example I have selected data elements or an indicator for BCG coverage and then the system is kind of recommending to these green dots which you see that these are the possible recommendations which can be used for further enhancing this respective chart icon so if I selected BCG coverage then in the background this is the system understands that for this particular data for BCG doses we are collecting it by say the type of facility or we are also collecting it by the doses given in urban or rural areas so it kind of highlights the possible recommendations which could be used by the user to add further disaggregations on top of their data to kind of make your charts more descriptive more elaborative and kind of give you a detailed overview of the different disaggregations or dimensions which you can add so these recommendations come automatically based on linking your data input categorization to the indicator disaggregation which you can add on the interpretation panels when under a company design where you could subscribe in the interpretation panel so as we do on different social media platforms we subscribe to different YouTube channels and as soon as a new video is posted by the YouTube channel we get us alert on our mobile phones similarly we have functionalities where if some dashboard items are your from your area of concern and you would like to let us updates made to the interpretations then you could subscribe to these dashboard items and as soon as any user posts any update to the interpretation then they are able to get an alert that an interpretation or an update has been posted to their subscribed dashboard items and they could also kind of put mentions you can search for different users similar to what we do on our social media chats on Facebook and Instagram and also we saw on Slack that we could mention a particular person and tag our response to that specific person so kind of building one on one communication within the group and kind of building communication around the data through the use of the interpretations panel this could be done both on the dashboard on the data visualizer app and also on the dashboard as well then another feature which was requested was to kind of have chart color sets so basically the early releases of DHS2 it had a fixed color palette which was applied to all the charts but now you have some predefined color sets which you can apply to your charts so you have various options to choose from when we will be covering these applications you will see that in detail what are the color sets available and how you can utilize these color sets in your charts when you create you can do text styling now you can change the style color and size of the text and within a visualization you want to use the style you want to put in bold you want to change the color or you want to change the size of the text you can do that so you can customize your chart item based on the preferences which you have favorite tables earlier were working as a separate app in all those releases till date but towards kind of creating and more integrated experience for the user all the functionalities of the pivot tables are now being added to the visualizer app as an additional visualization type and the pivot table app will get deprecated and will not be part of the DHS2 package moving forward so from version 2.37 the pivot table app will no longer be supported and all the functionalities which are available in the pivot table app will be integrated within the data visualizer app and pivot table is now as a chart type or visualization type added in the data visualizer so when we cover pivot tables we will be focusing more on the chart type which is integrated within the data visualizer app and not the native pivot table application which is available in the system in terms of migrating from the old app to the new app if your instance has already configured pivot table favorites then they are already compatible with the data visualizer app and they will open as they do in the pivot table app so that migration has been taken care of. In terms of pivot tables there are a lot of improvements have been made to in terms of the performance as done for the charts the arrangement of the dimensions between column periods column rows and filters is now persistence over the header earlier in the old pivot table app everything was within the layout menu now it shows on the top and it's easy to switch the dimensions if you want to the recommendations same we saw on the visualizer are also applicable to the pivot table and there are interface improvements where you can define the spacing between these rows and columns you can increase the size of the text and the arrangement you can make the table more compact or you can make it more easy looking so based on different options available you can make certain changes to to the pivot tables that you create maps earlier we were using the GIS app in the older versions but from version 2.29 onwards we have the new maps app which has brand new interface for adding the different map layers so these are the layers which are supported as of now and from version 2.35 onwards we have moved to Bing maps and in 3.6 we have added more integrations with world pop 3 which kind of brings the population data set into DHS2 kind of adding more external source of data available for you to analyze your data against the downloading of maps was not initially supported in the new maps app but that has been added now and you could download the image of your map that you've created with the legend and you could decide the location of the legend based on your preference and now you could also download the map data in a downloadable format which is supported by ArcGIS or QGIS or any other GIS software so if you want to do much more than what DHS2 offers in terms of maps you could always download the data from your map and import that into any other GIS system for advanced analysis so this is how it shows up you can download the layer data and you could import that into your GIS application all the maps are now supported by a data table so not only you see the data on the map in terms of the legends that you have defined but you also see a tabular format and you have these filters available where you can put the different filters here so you want to filter by custom values which might not be part of a legend you just put greater than 70 less than 75 so you can put ranges and then it will automatically categorize the map and the table both for you so we will see this in our demonstrations and further exercises that we do moving forward you could now use data dimensions as a filter in your maps for example if you have created a map where you want to see the total number of HIV testing done but then you are collecting data by male and female disaggregations but you only want to focus on the female cases so you could add a filter in the thematic layer that you want to filter the data by sex and only want to see the HIV test done for female cases on the map so you could also do filters on the maps as well now now you can do both the clorpet and the bubble maps earlier only the clorpet or the heat maps were supported but now you could also plot data and different bubbles both supported now in the maps application then there were two new introductions done where you could see the maps as split view so if you selected last five years of data for one indicator then it will just show you individual map for each year for that respective data or if you want to see a timeline map then you could select your timeline map select your period then for each period it kind of works like a graphical interface where it will keep on switching year after year automatically and you could see the change which happened for that indicator here after year so these are the two two new functionalities which have been added in the maps application so this was my last slide so these are the latest updates which have happened or over the analytics apps most of you might be aware of these proceedings to those who were not aware so we wanted to give a quick snapshot of what has happened over the last three or four releases on the analytics application and we will be covering these features in detail through the dedicated sessions that we have for each of the core apps and we will be happy to take questions which you have during those sessions but if you have some immediate comments and questions please feel free to ask or you can post them on the Slack channel and we will be happy to answer them thank you alright so I think we can take a break now for 10 minutes before we do the last session of the day where Pamuth will do a quick demonstration of key analytics features in the application so the local time is 3.17 let's come back at 3.30 and that would be a last session for the day and we could close the day for today and the Slack channel will remain open for you any comments any suggestions please put so and yeah that's it so let's regroup at 3.30 and then Pamuth will take you to the last session thank you