Getting Started with Data Visualization in Power BI

Key Takeaways

foreign thanks very much for joining today's code along uh I'm will I'm going to be your uh moderator today we'll be kicking off the session in about five minutes which is going to give everyone a moment uh to join and get ready but in the meantime um let us know where you're coming from we'd love uh love to hear where you're dialing in from um and ping us um yeah let us know in the comments uh to the side um just let you know if the code long we'll be using power bi so if you haven't already got that installed please get that done now um keep an eye on the comments and I'll be sharing links uh throughout um and please note the session is being recorded and the recording will be sent to everyone who's registered for the event I'll send registration to the event um shortly as well if you haven't already um yeah register and um yeah and if not you can also head over to www.datacamp.com webinars too cool I will send those through and I'll be back in a few minutes to introduce our hosts foreign foreign foreign thanks very much for doing joining today's code long we'll be starting in a couple of minutes we're just going to give everyone a few more minutes to join uh my name is will I'll be your uh moderator today in the meantime we'd love to keep hearing where you're from and loving all the comments coming in um just let you know for the code long we'll be using power bi so if you haven't already got that installed please get that done now um keep an eye on the comments and I'll share a link so you can go along with us um it is actually already in there and I will send it through again so it's the top of your feed um just to note this session is being recorded and the recording will be sent to everyone that has registered the event um if you haven't already ready please register the event we'll be able to send you all the recording resources to you um and if not you could also head over to datacamp.com webinars2 where all the information is there also um yeah be back in a couple of minutes to introduce our hosts foreign looks like we are nearly ready to um begin so just um just one small sevens on the same page um we're going to be using power bi so if you haven't already got that installed um please um get that in now um to register for the event I've um I've put the link in the comments a couple times so it should be there um when you register the event you'll um receive the recording all the results you need afterwards um if not you can always head to datacamp.com webinars two um cool well that is fortunately for you guys everything from me I'm gonna hand you over to your host uh Richie um Richie if you'd uh like to take it away um all right uh thank you uh for the intro will um all right so welcome uh data scamps and data jams this is Richie and today we are going to be talking about one of my favorite topics namely data visualization so I feel that being able to draw plots just provides perhaps the best value to effort ratio of almost any data analysis skill so it's relatively easy to learn but it's just incredibly useful in a wide variety of situations so in this session you'll be learning how to create plots in power bi and we're keeping the decision this session pretty beginner focused so you're going to be learning how to get started working with power bi and drawing some data visualizations Our Guest is Nick Switzer he's a sales analytics solution lead at the medical Tech provider Striker and Nick's got a pretty interesting career because he didn't start in data analytics he originally worked in engineering and supply chain and really later moved into Data Nick is the instructor for the supply chain analytics in power bi course and that's what today's session is Loosely based so uh over to you Nick all right well thank you Richie for the introduction um I am really excited to be here I'm a fan of the data framed podcast so it's um uh sort of nerding out on the fact that I'm I'm here with Richie uh so it's very exciting um and also I I'm a big fan of data Camp I I'm a student as well mostly for our python work uh so as well as being an instructor uh so it's just an honor to be here and a privilege to share with you all today so like Richie said we're going to go through some uh some basic visualization in power bi we're just going to get started um this is intended intended for beginners but if you're a seasoned Pro or a veteran with a little bit of time in power bi uh you still might be able to pick up some tricks and and tips along the way from this but but it is definitely focused on on beginners um so the data set that we'll be using today is the surgery center quality metrics from um this the center for Medicare and Medicaid services so that's uh that's Healthcare United States Health Care data CMS is the largest provider of insurer of Health Care um but it's not it's all public and so we have it's an amazing data set and we'll talk about that a little bit more um but what we're we're going to be diving into from a power bi perspective today is making a straightforward report we're going to have a scatter plot we're going to use top end filters if you've ever used those um I'm a big fan of those for how they can make the data more easily digestible and so we'll talk about increasing report space this is one of my favorite tricks that we can go through too that that helps um really make data storytelling a lot more a lot easier to do than I think standard power bi reports do so but it's pretty straightforward when we get into it and then also if we if we have the time we'll get started with with the map so and really why why are we doing this why do we build power bi reports uh and dashboards I mean it's always to me it's always important that we're building these reports to drive decisions we don't we don't just make the report even though it is great if you make something that's beautiful um and in a lot of cases that's okay too but for me I love that with it on the other side somebody is taking that data um and making making their lives better with the decision based on that uh so like will was saying in the in the intro this is all going to be on power bi uh desktop so if you don't have it you can go to microsoft.com uh Power bi and you can click on products you can download it um and don't stress if you're if you're doing that now and falling behind if you don't have it already uh we are recording the session so you can spend some time over your weekend or you know whenever you want to uh just read re-going over the session so if if you if you get behind but um so if you can download and get it installed so um now for our task today we are going to build a dashboard to theoretically help patients friends and families assess their health care options so we have data from surgery centers and we want to help them choose the surgery center that might have the best outcomes for them uh so the data set specifically the title is this is ambulatory Surgical Center quality measures uh and it's at the facility level and it's available at data.cms.gov there's lots of great data sets there um we use some data that's based on that for our work at striker um and it's it's very valuable and if you're looking to build a portfolio to get into the analytics space it's it's just one of many many great data sets so um definitely dive in there so some definitions that will be useful for us today there is a surgery center is it's not it's not a hospital it's a healthcare facility separate from a hospital that focuses on outpatient surgery and outpatient surgery is surgery that uh basically you you don't need to stay overnight in a hospital it doesn't require hospitalization afterwards so the ambulatory part just means I mean that you can walk out even though you don't have to walk out the idea is that you can go home you can rest in your own bed that night after after the operation so these are um still very serious procedures um but but they don't require hospitals issue and then the the main target um that we're looking at today or the main feature of these is that there's a risk standardized hospital visit rate the rshv rate is how uh what rate what number of patients uh cut that go get these operations end up in going to the hospital within seven days of having that surgery so that could be an indication that maybe the surgery um wasn't wasn't performed properly something went wrong and that's something you'd like it like a heads up on so every every surgery has its own inherent risk um when uh we'll see that there's definitely baselines on Baseline RS HV rates um but it's it's something that if you can choose to minimize it you'd probably prefer not to go to the hospital in an unplanned way um at least that's yeah that's how I approach my weekends is not not trying to go to the hospital in an unplanned way so uh all right so we have the the data set in power bi already um we're not we you can you can always get the csvs from or connect to the API cms.gov but in this case we've just provided it uh for sake of getting straight to the visualizations today and that's in a link that I believe has been sent out um and then there's also CMS has a great data dictionary for us to use so with that Richie are we good to head to dive into the to the power bi visualizations now all right I think you might be muted oh sorry that was a yes I'm ready to go to Power bi awesome yes I I I felt it um so uh you see in here we have a very a very Abridged data catalog like I like I mentioned the uh CMS has a good a great data catalog where you can go to get the definitions on some of these these rates um and and well some of the the data that is in this data set so I've written our task here uh so we're going to create a report investigating Urology quality metrics to help patients explore their options um so when I think of when I look at a data set at first I just I usually just come over here to the right to this data Pane and I scroll through and if there's not too many too many different uh columns in the data set I might scroll up and down but I'm not seeing uh I'm not seeing anything too quickly here um so I also prefer to go to the table View and that'll give me a better idea what the data is looking like under there um so here's a look at our data set it's a CSV that's already been imported we've got facility names here their their facility IDs they're um and then lots of different data about where they're located uh the year that that the data came from but then we have all these rates that are kind of meaningless if unless you have that data catalog so that's probably why they have a good data catalog uh because they everything's labeled ase9 ASC 9 footnote I don't know what those are um so in our case I've I've pulled out ASE 18 is the one that focuses on um Urology surgery so um really we just want to focus on control um can we just bump up the text size a little bit for people who are on small screens thank you yeah all right um so really we're looking at the ASE 18 and I know I know this this part has stayed small um in the columns here but so if we're going to explore our options for getting surgery done in a Surgery Center uh and and just trying I want to understand this data at a national level um we can just take a look at how many surgery centers are we are we talking about in the in the in the United States got 50 different states um but how many are performing these ASE these Urology surgeries so again I'm focusing on ASE 18. um and I'm going to pull out the facility ID actually and we're just going to make a simple card here this is so it automatically gives me a table I'm going to come to the visualization pane turn this into a card and instead of seeing the first facility ID I'm going to come here to the to the visualizations tab and right now it's summarizing this by the first but I want the count uh the distinct count of facilities that are performing or sorry the distinct count of the facilities um that meet this criteria and I'm sorry I noticed I didn't intend to do this and uh but I left a filter in here a lot of you may see I've already filtered for where this the total cases are greater than zero so we've got 548 facilities that are performing the Urology surgeries um let's I'm going to clear that really quickly and then we'll see okay we've got over 5 000 facilities in this data set so about 10 are actually performing performing uh the surgeries that we're looking at so I'm going to go I cleared that filter I'm going to go back and now offer this entire page I will be filtering since we're focused on the Urology surgeries we will be filtering for the the total cases of this as18 greater than zero and we'll see oh we go back down to 548 surgery centers so uh I also I mean we could leave it as count as a facility ID and if I'm doing just exploratory data analysis A lot of times I'll leave almost all the time I leave these uh with their basic whatever the power bi Auto populated title is but in in the case where we're making a dashboard for someone uh to or a dashboard or report for someone to use I'm going to go ahead and change the name to uh Surgery Center is sort of changing the name of the field Surgery Center is performing Urology procedures and that's a little bit too long in this case I'm just going to go back and I think we've got ASE all over the place I try to um a lot of the feedback I S when I sent this to some friends at first is oh there's so many acronyms in here and as data people we always end up dealing with acronyms rshv ASC trying to reduce the acronyms as much as possible but in this case uh we've got we we still can get a lot of we can use it um to give us a little bit more space for text so pretty straightforward we have the count of count of facilities doing these um and then one of the first things I do also from from an exploratory standpoint is I I like to look at a scatter plot um sort of scatter chart as it's called here so really our Target metric we don't have too many metrics around the the ASE 18. we've got the rate um and we have some other data here and we have the total cases so we could explore relationships between the rshv rate for for Urology and maybe some of the other surgeries but in this case I think a natural question is does performing more of these surgeries lead a surgery center to be more proficient so I would like to explore that using a scatter chart or a scatter plot I'm going to select the scatter scatter plot visual and I'm going to take total cases put that on my x-axis and take the rshv rate and put that on the y-axis and right now we have it's just giving us the sum for everything so we need to give the put the ID of the facilities to oh no actually we need to come into the come into the visualization area and where where we've placed the rshv rate it says sum and we'll just click on this little carrot down here and go to do not summarize and now we see okay we've got a nice distribution of rshv rates here on total cases rather sorry and one of one thing that I didn't discover until much later in my power bi career was that uh I always just changed it in the visualization but what you can also do is you can treat you can change the way this column summarizes uh as it as a default so honestly for this for this rate I don't ever want to be summing these the the rates and so I'm going to come back here and select do not summarize so I've already selected it for the visual it won't change but in the future when I have this when I pull this right in uh I will not be it will not Auto summarize um and then for this visualization I'll do the same and I'm going to blow this visualization up in a second I'm sorry I left it so small I can't see it that well either is it all so the dots are also bunched together so um here should have made that larger earlier um so we can see we've got total cases across the bottom and then we have the the RS HV rate and we notice that we um that the the rate is actually expressed and even though we'll just look at this one um I know that's small but it says the rshv rate is 8.3 so uh I know we're supposed to have something like a hundred a hundred to two hundred folks on the call um the the rate here you know it it might not sound that bad oh you have an eight percent chance of of going to the hospital on an unexpected visit but if a hundred of us or two are going that means eight of us are going to end up going to the hospital in an expected way so we definitely want to minimize definitely want to minimize that um our chances of ending up in the hospital uh after after going to a surgery center and I feel bad I feel bad for uh calling this out but really we're trying to focus on the best ones here so we've got our scatter plot we see maybe there's somewhat of a an inverse relationship but it's it's it's kind of stretching there um so I we still we have explored it and if if a surgery center says hey we do the most in town maybe that's maybe that's reason to believe that they'll have a lower rate but I wouldn't necessarily uh just look at that I would I would love to know their their rate before going in um so I want to point out some other things that I love to do with Scatter Plots um and one of those well actually the first one we have this performance category over here um and I'm just gonna pull this out this is not going to be a long-term visualization but pull this in to see what it is we've got performance category no different than National rate and worse than National rate um so we can use that to give us different we can use that as the legend in the visualization to give us sort of a color guide to see until we can quickly see where the where a surgery center is is actually different statistically significantly different from the national rate um and so I part of the preparation for this is we wrote a Dax um column here you can feel free to look at it but we're going to use this Dax column because it's a little bit more abbreviated and easier to easier to see when we pull it in so I'm pulling in this this performance category to the legend and then we really the ones really stick out um and I don't know if dark blue quite tells the story uh of of what we're trying to say here so these these These are the places with the with the higher rates so we want that to be highlighted and so I'm going to come in and and I wouldn't want to change the color on these change the color on these dots um and I have now all right so we come to markers and then we can scroll down to color So within markers or in at the visual pan tab and then come to markers and then we find the color and we'd say okay what what really highlights where's the national rate um and I'm probably gonna go I want more of an alarm than a red a red it might be too harsh so I'll go with an alarming yellow here um just so we know okay we we need to have a good reason for choosing these surgery centers so I'm going to get rid of this visual so we what else can we do with the scatter plot and I guess I'll realizing I could have made this also larger by going into Focus mode um so if you hover in the upper right of the visualization you can blow up the blow up the scatter plot and now we can get down and even deeper into it so this is very useful and actually a very useful tool for uh for your users as well so a lot of times I deal with users who are who are asking to see who don't who aren't in power bi all day they look at Power bi maybe once a week to inform their decisions but uh they don't know all the tools and tricks so I end up telling them about Focus mode all the time just so they can get in and see the see what's in each visualization a little with a little bit more granularity so we've blown this up and I'm also looking at this it's hard to tell we could pull out some when we will later pull out some other statistics from this but I would like to know naturally I jumped to what's what's the median if I just um I want to know where every what's the what's if I'm going to choose one at random sorry not choose one at random but if I want to know where the middle middle point is am I going to be so I can I have a good point of comparison am I doing better than than the middle of the data set or not so we can come over in the visualizations tab and we can click through to this further analysis we have this this magnifying glass and it's got all sorts of stuff all just flash it can give you a trend line you don't see Too Much from the trend line there but it is it is nice in this case I want to show the median rshv rate so I'm going to click on y-axis constant line that will give us a constant line on the vertical axis and I we are going to add a line here and it auto it defaults to zero so for this value we can come we could come type in a value but I'm actually I don't know what the median is yet so I'll come and click on this function button and now we get to select the field that we are going to base this on and we want to see the median rshp rate so I can look up rshv we're looking at ASE 18. and we can come over to our summarization mode and for this line we want to see the median so we'll click the median and there it is that's beautiful so now I can see okay if I'm choosing anybody on the bottom half I that's probably gonna um that's a better bet in terms of reducing my risk uh of surgery of going to the hospital after this operation um so I'm going to label this median and I find this very useful all the time is also putting obviously putting the data label in so so people know what they're looking at so we can come here we can turn the data label on and then the style is we can give it the value oh and it's all the way over here to the left before we fix the fix what we're showing um we go to the horizontal position put it out here to the right it's got um oh we might not it might be too far to the right now to see in focus mode so it's out here I'm going to take us out of focus mode so we can see our median label and I love to actually give them the name of the line as well so I give them both name and and the median is 5.1 um so that's that's our basic scatter plot now we've done some some investigation and this could tell our back to what we actually want to communicate to the um to our you to our to the patients and potentially to their families is we have the national median um you could look for a a surgery center that is more experienced than this if they do tons of procedures that could indicate that they have a lower rate but it's not necessarily it's not a grade um it's not a great indicator actually so I mean it's it's an interesting data point how much how many total cases they do um but doesn't actually help us that much so um and as a quick side one of the things I love about data is actually it can tell you what it what it doesn't matter to pay attention to so a lot of times people a lot of there's a lot of false signals um and I think number of cases is one of those type of false signals that could people could throw out um as hey we're great we do the most in the city well that doesn't necessarily mean um doesn't necessarily mean you're the best so when you use data you can see that all right it doesn't it's not actually it you don't need to fall for the false signals and you don't need to pay attention to those all the time but you don't know that unless you do the do the analysis and look at the relationship all right [Music] um I can move on I don't I have not been able to look over and check out if we have a lot of questions or anything should I keep rolling or should we take a question pause or anything like that we have a couple of questions from the audience already uh if you do have any questions for Nick please do ask them in the chat um so uh actually the the two questions are slightly more general questions so um maybe we'll cover those at the end okay but but I I do have a question for you just um while we're letting people uh think of their own questions um so we've covered Scatter Plots a lot I'm curious as to when you can just draw like a simple scatter plot and just have the points they're showing and when you need to do all this extra work to um to like add the titles and figure out access labels and all that sort of thing do you have a sense of like when that's important or not um well honestly I usually use the Scatter Plots for investigation um and so if I put a scatter plot up and I don't see any relationship um a clear relationship then usually uh I I have learned something from that but I don't keep it but I um very frequently if I'm communicating to other people in the business I I and I have a more I have a story to tell with the scatter plot I'm I'm pulling in uh almost always a median line or a trend line or something like that um the performance categories I don't usually wouldn't necessarily usually use but I think the lines actually help um help tell whatever story you're trying to tell and this um so I use those very frequently and yeah and then and then if I don't see a relationship and there's in this case the the story is total cases don't necessarily make for a lower rate it's not a guarantee and if that's the story I was trying to tell um I would probably yeah that's the story we found so um but usually otherwise I wouldn't probably show this you know unless there was a hypothesis that we were um actually trying to maybe debunk I I wouldn't I wouldn't usually use the scatter plot so it's either to it's it's really good to look at a hypothesis between um about a relationship between two different variables so I think those extra bits of detail just helps clarify what's happening and helps you develop that story from uh from the relationship between the two variables yes yeah all right wonderful all right um I think since we've not got many questions from the audience we'll we'll do a longer q a at the end uh but for now you can carry on with uh with going through creating the uh the plots sounds great um so I'm gonna change the title on this this is our last bit on the uh the last bit on the on the scatter chart um and I am just going to say um Urology rshp versus total cases so I I might in other cases I might actually write a sentence about what we think we're seeing here but um in this case I'm just going to leave it because we might be a little short on time for some of the other things we're looking to get to um so you can see I feel like we're quickly uh running out of space um and so I'm excited to show this the the the way to make more space but we will get there in just a second um so we're looking at ases uh all are these surgery centers from all across the country um one of the things that that naturally comes up uh and maybe it's just a competitive nature but um it's just also a a question is other states that are much better is there is there a location in the United States where um we have a huge huge difference um by by state in the in the performance of the surgery centers so for that I am going to pull up a we'll just use a column chart uh and in the beginning we also now we want to for we see that we have state for each of these facilities so on our x-axis I will pull in state and I want to see the rshv rate oh I called the wrong almost pulled the wrong one I pulled the orthopedic surgery on um so the ASE 18 or Urology um rate and this was not my intention but and we'll go into go into Focus mode real quick we can see there's a huge variance in the um in the cases per state or I'm sorry facilities per state I mean with California having the most of north of 68 surgery centers in Wyoming down here uh with just a few and that correlates pretty well with population um but what we really want to see is the rshv rates here so we've seen that the number of different count of rates but we want to summarize this as median um and so it it had to choose the default summarization um in this case so okay this is this is crazy um we can't really get much of that even we can go to focus mode but honestly my uh I lose track here I really want to focus since we're focusing on choosing the surgery center with the lowest rates I want to focus on just this uh tail over here we want to look at the lowest rates um so what we can do is utilize the the top end filter um for um here in power bi so we're going to look at the state and we have our filtering options we open our filter pane we have basic filtering we can choose select them um by select them by their state abbreviation but what we want to know here is just which state should I focus on if I want the the lowest risk rshv so I don't think people actually shop for um I don't think people actually shop for their surgery centers this way uh although maybe you could look at States in your neighborhood um it's not I don't think it's common to to travel that far for these but maybe it's worth it it's something to consider um so in this case let's look at the bottom seven uh so I want to show this the bottom seven items and then oops I'll pull the rshv rate into into here um and in this case uh we want to see the bottom median so which states are going to on give us are we most likely to have a best okay seven is even a little bit crowded so we'll go to bottom five and so this has this drives tons of focus um oops I didn't apply my Factor or or we have a tie with the medians here but um but sorry to the point of uh of top end filtering I have been in a lot of meetings in in life where the the the the the the data point that is maybe the least important uh is also drawing the most attention it has and so if you show Too Many data points you can overwhelm the users and you can also um you invite distractions and that are not associated with the biggest drivers uh what you're looking to to demonstrate so um that's one that's I love the the bottom or the top end filter in power bi so we see uh we've got uh South Dakota Delaware Rhode Island Pennsylvania so lots of lots of different states in Alabama here um so lots of different states and without knowing the geography of the United States you don't necessarily see if there's if there's any sort of trend here um but now we we know we have some direction given to our given to our patients if they are in a position to travel um but also we chose this to to just demonstrate demonstrate the top end um and maybe get our geography brains going a little bit so at this point I'm going to actually give a label because I'm I'm actually to a point where I feel like I'm running out of space uh so let's label our label our tool here and oh sorry I will keep this this large aerial black font uh and we'll say all right the best Surgery Center is um for Urology by rshv rate so you can quickly put this at the top and tell our tell our users what they're looking at um and then and then one design principle that I that we right now we've just been throwing the throwing the plots onto the uh onto the to the report but now as we start to think through you know how is our how is our user going to in interpret this um we've got we really want to start from the top left and then attention will flow from there so in this case I mean we're kind of giving a scope or a size of this um size of this the data set that we're looking at 548 surgery centers and then I'm just going to put the surgery the total cases up here for a second oh no actually um in our in our final file I also want to call out that median rate really quickly so I am going to just do a simple copy paste here because I like the format of this card it's large and communicates quickly but I want to also pull out that median because I think that that's that kind of sets everybody what the what's your Baseline risk going into um risk of of going to the hospital after going to this for this procedure so I'm I've copied this card over I'm going to just pull the rshv rate in it has defaulted to count but I want to show the the national median um and I am just going to label this national median here oh [Music] all right so this so far we don't have a ton of direction for our for our users except that we could tell them which state to go to and not necessarily to trust uh the number of uh the number of cases performed as an indicator but we need to make some space and uh for for our own report and really something that uh someone on our team I mean this has always been available in power bi but we're going to come and click click on any space here in the canvas and we can see that we can change our canvas here and this is oops I've accidentally created a q a so we can change our canvas so this is where you can add a picture you can add um as your background you can do lots of lots of cool stuff um but in this case I am actually going to to make our canvas longer um so I could we could choose a letter format or just do custom pixel by pixel so I'm going to estimate that I need our height is 720 right now um I'm going to estimate we need another 300 pixels here and honestly this is really powerful we're not making that many visualizations today but it kind of harnesses what we have already what a lot of folks are used to which is scrolling and I'm not an advocate for Doom scrolling or spending too much of your life in the scrolling world but it's really great when you're trying to tell a story and that's just kind of how how people operate a lot so um so a lot of times instead of having separate reports where you have to click through that slows users down so if you had something like eight visuals and you needed to tell the story you just need to extend that canvas so just a small tweak um to the to the existing power bi AI um but and something again that I wish I had I had discovered earlier so now I'm going to jump into one of my favorite favorite Parts uh of of power bi which is the map they have lots of different map visualizations and it can be helpful if you're looking for Geographic Trends in your data or if you're just trying to help direct someone to and help them get an understanding of uh of the underlying data set if there's any location involved so in this case surgery centers are are definitely location data so I definitely recommend checking out the Azure Maps but for today we'll use the the standard map I believe there's less permissions involved um so if we scroll down to the bottom we see lots of this uh lots of the data and or the location data and facility name so I am going to use zip code and it does a lot of the geocoding on its own and now we see here are the surgery centers it's already populated those for us and it is overwhelming again just kind of like when we did 50 states it's hard to take it all in but generally it correlates with uh highly on the location of our surgery centers is correlating with highly populated areas you see lots on the coast uh on the coasts rather and so to highlight each one of these I well first off I am going to reduce this to the you would use the top end filter again to show which um which yeah which facilities have the most so I don't we're going to dial down to maybe 50 facilities instead so we'll pull a facility name or really facility ID we could use as well uh pull in top n change our filter to Top End we'll pull total cases um oh you know what I I've made a mistake here um I want to actually focus on the rshv rate because we want to direct our direct our patients and and families to the facilities that have the the lowest risk so we're highlighting the ones who who have the best outcome data um and let's do top 50 in the country here okay that's a little better um and I'm gonna just extend this a little bit so we can see and so I still want we have these bubbles here I would love some sort of uh visualization to to quickly help them pop out um and one of the things that that helps differentiate maybe the size of these would be the total cases so we can pull that into bubble size and now um we've got much larger bubbles for the ones that do the most so again that's not necessarily what we're what we're looking for to drive the best uh the best outcomes but um it is it is it is helpful um and let's see I am and oh one of the things I really definitely want to demonstrate here is we're looking at the top 50 Across the Nation but we have all of these all these states that have the um the best medians as a state so let's go ahead and click on Alabama I see a couple there and now we can this the interaction um is awesome in power bi as well so when I click on Alabama then we see the top surgery centers in Alabama uh by their in this case we're doing top or oh no I'm sorry I'm sure somebody in the chat or somebody has noticed this already uh but we're actually looking for the bottom 50 we're looking and I did I fell for it the when we say the best often we think the top but in this case uh the bottom is the lowest our lowest less risky I was wondering about that I was going to ask you like um is it a really good idea to go to Alabama for your surgery or a really good idea to leave Alabama like not go to all about my face surgery um yeah yeah we need to I'll we'll zoom out so yeah I mean I think it's actually by the here we're looking at it's it has a the median rshv rate is below this national median so uh if you're just choosing at random you're more likely in Alabama to to be below the national media and we see the we see this facilities here there's a few and then there's one here that I probably wouldn't recommend right away um so we can see where they are on the map is it is it worth just going through and just clarifying like what the sort of meaning of this is then so so the RS HP right this is like how many people are getting hospitalized what was it within seven days after surgery yes yeah and so you actually want this number to be as low as possible yeah so do we need to redraw that plot then what happens if if we update uh well this plot is by the median by the low all right okay and and I just had pulled the wrong filter for my map here and yeah so but yeah that's I mean yeah we're definitely looking for the lowest rate um oh so is that South Dakota is that is the best place then it sure is and now it looks like we've only got one Surgery Center here um and uh but they have a below below average right there and I'm just going to pull the facility name into the tool tips here so when we hover over it uh sometimes it takes the uh the the tool tips can be a little slow on the maps but all right click in and out and we should be getting that should be getting the oh I I'm sorry the facility name is here I pulled the facility name into the wrong so if I'm going by ZIP code or looking on the map um Urology Specialists uh here in South Dakota so maybe it would have been wise to uh also have a filter for just the number of cases and actually let's go back to that visualization um I think I do have this in the solution and just and just forgot to add it but if we filter by the number of cases the median isn't uh super meaningful for just one I mean it does tell us so let's say total cases uh above I'm sorry I'm not looking for total cases now we're looking for for facility names so the count of facility names um facility IDs so let's look at we're going to change this to filter for states where um oh sorry I want to be doing this by the by the counter facility but I have not all right we'll have to you can check that out in the solution um but we've got um one more thing I wanted to show from this because this obviously if we do have the map um it can show us the the location points but almost always when I have a map I'm putting a table with it so that we can we can actually see what's being displayed so in this case we want a simple table with the facility name and the rshv rate so facility name will be our first column I'm going to make that column much much thinner and then we'll pull in the rshv rate and we'll sort sort that column for the lowest rates rshv rate um so we're looking for the lowest rates I'm going to take all my filters back and so now when we click on let's go to Georgia we haven't clicked on that one yet we can see not only on the map how these surgery centers where they are but also we can see okay if I want to go to the absolute lowest rate rshv rate then its Gainsville Urology um all right so I know we're running sort of short on time so I would definitely uh change this title here but I guess uh if we if we had if we had more time I would change this title and also go and figure out how I did the the filtering for the for the by the number of facilities in each um State on this uh but I want to save time for questions so I will do that afterwards and you can find it in the in the solution notebook all right super uh thank you very much Nick um yeah that was very cool like it's um nice the way uh you can just like grab all those different plots together and then make a sort of coherent sense as a whole and you know you got that interactivity that affects multiple plots so uh that sort of reactivity where you're updating several parts at a time that's absolutely valuable for dashboarding And So yeah thank you very much for um showing us all that now before we get to audience Q next we have got some good questions in there okay I just want to let you know uh next Thursday so that's September the 28th we've got a very special event so we've got the radar virtual conference so we're going to be talking all about data literacy and AI literacy we've got a lot of big speakers uh like very big names uh in the world like literacy uh coming to join us so please do register for that um so I think uh will is just posting links to that in the chat and with that uh we've got uh we've got a good uh five minutes or so to go through some questions so there were lots of people in the chat talking about the the pl 300 exam so this is the uh professional power bi exam that Microsoft runs so Microsoft makes power bi and they have their own certification to go along with it now the data Camp uh data analyst with power bi career track is going to take you through all the skills you need with that uh so perhaps um we'll compost link to our power bi career track um Nick I don't know um is this something you you've been you've taken yourself or you've had colleagues take the um the Microsoft certification for power bi uh I have not I have not taken it I did the I got started with power bi at their dashboard in a day I'm not sure if they're doing those anymore but those are a wonderful way to get started as well but um I have not taken that I think it would well I think it would look it definitely would look good as an indicator um but it's not something that I think of as a as a must-have okay or I mean certainly if you want to get your first job as a data analyst and using power bi then having that extra credential is is possibly worthwhile so to go back to Shear brush your original question um how long does it take to prepare for this um so the courses in the uh day transfer power bi career track there's about 50 hours of content and that's probably going to get you part where you're going to need to do some like practicing on your own as well so you're looking at sort of between 50 and 100 hours I think to to prepare for that and it depends on how much data analysis experience you've got uh uh next question comes from Jennifer Nick I don't know do you have an opinion on the difference between power bi and tableau uh it's been it's hotly debated or at least was hotly debated because we we used to use both uh in the office but um in general Microsoft uh Power bi works really really well because all of our users have Microsoft accounts um and it it it they're they're using Outlook and everything just works syncs together really really well one thing we didn't get into because this was a beginning courses um is the row level security and I know you can do relevant Security in Tableau but um I think it works really really well in power bi and it's something that can take your reporting to the next level where where you're just limiting users to seeing the data that's associated with them so they see the rows um and you write the rules for that so um that's one of the one of the awesome Parts about leveraging and just being in the Microsoft ecosystem I didn't mean to make a commercial for Microsoft but like there's a free one I guess yeah I mean I think there are a lot of like pretty powerful uh business intelligence tools now so trying to decide between like power bi or tablet was like from a drawing dashboards drawing plots and like creating dashboards point of view you're going to be happy with either of them it's really a lot about like the rest of your Tech ecosystem and how it integrates with that yeah and I know people who have definitely transitioned and now are ofly sort of bilingual in the both of bi systems and um yeah I think that's that's awesome that's the way to be all right um one last question so this comes from um Ferris so we didn't uh cover anything with Dax so Dax is the uh is one of the programming languages built into Power bi and um basically first we'd like to know when do you need to care about decks um I even with this very straightforward data set I ended up making just a few Dax calculations um or and I think I showed one of them but I I think pretty pretty early in your power bi usage it's it's a very it's a very powerful um and yeah I don't think we have almost any reports that have zero Dax um and we we do a lot in the in power query as well before the data gets to the visualization stage but yeah we use we use quite a lot of Dax um so I definitely encourage diving in with thanks absolutely so I think um when data companies use the curriculum it's like we have an intro to power bi course and then like Dax is like the the very next course so it is something you need to learn pretty sharpish um it sounds scary but it's actually it always looks to me like it's just sort of fancy Excel formulas uh yeah it's that kind of style of things so yeah you can probably get started with it pretty pretty easily yeah I think there's a there's a curve there's a learning curve and it gets maybe a little bit uh it doesn't it's not fun in the middle but then after a while it definitely picks up so easy to start and then uh really fun once once you get into the more advanced stuff so all right you just got a hump to get over in the middle but anyway it's good to know that it's easy to get started with yeah yeah excellent all right uh so with that I think we're at time uh thank you once again nick uh yeah uh great stuff and always nice to see yeah how you go how you think about building dashboards uh thank you to will for moderating thank you to everyone who asked for versus a question thank you to everyone who showed up today uh please do join us next Thursday for the radar virtual conference and I hope to see you again in uh further webinars and code alongs in October excellent all right thank you everyone bye thanks everybody bye-bye