Introducing DATA: the Data Analysis Tool for All

Hi everyone. Thank you so much for joining us today. My name is Shelley Reid. I am the manager of the legal services national technology assistance project. We call it Ellison and TAP because it's a whole lot easier to say. And we are here today to learn about our new data tool. And it's kind of redundant to say data tool because it's data analysis tool for all. and Rachel Perry, who is the creative genius behind us behind the tool, is here to talk us through it. And I'm gonna um I was going to say I'm going to turn it over to Rachel, but I think she would prefer me to actually say all the stuff that I'm supposed to say. So, if you have questions during the presentation, please feel free to put them in the chat and then we will get to them. I may be able to answer some during the presentation and then at the end we'll be able to go back and get to the rest of them. Um, obviously I'm Shelley Reid. I'm going to let Rachel introduce herself. >> Hello everyone. Thanks for joining us. Uh, this has been a labor of love, so I'm really excited to share it with all of you. Um, I think I'm I'm seeing names popping up and I know some of you, but uh, for those of you I I don't have the pleasure of knowing yet, let me introduce myself in some detail again. and I'm Rachel Perry and I've been doing data analysis work for well if I admit it you'll guess well I'm just going to go ahead and tell you for over 27 years and the last 15 of those have been specifically devoted almost entirely to legal aid data analysis. Uh I actually was on staff at the Legal Aid Society of Cleveland before starting my consulting practice uh strategic data analytics which I've been running for the past 12 years. Um so I think it's important for you to know that I did used to work on staff at a legal aid organization. Uh, as a consultant, I've worked for legal services organizations all around the country. Um, dozens of you and I've helped with all sorts of data related kinds of projects. Everything from improving data collection and integrity, uh, improving the efficiency with which data are gathered for funders. uh I've helped a lot of organizations develop client focused uh outcome measures and done a lot of evaluation work for different kinds of projects and a lot of training to try and build up data analysis capacity within your organizations created a lot of dashboards and other types of analyses reports and then uh probably my favorite work and some of what's included in this tool are uh the kinds of analyses where we Take external data about your eligible client population and internal case and client data from your case management systems and do some comparisons uh to try and see where maybe there's some unmet needs, some trends, some emerging needs um and with particular focus on disparities by location and race. So that's who I am. Shelley, did you want to go over the agenda? >> Yes, absolutely. So, we're going to talk about what data is and then we're going to talk about the tool itself, where you find it on our website, how you use the tool, where you can find the analysis guide and all the analysis examples, and then we'll talk about all of the things that you can do with data and what data offers. And we may even have a chance to get to some of the other tools that LSNAP has available for you. So, that is where we're going today. Okay, in a in a minute I am going to jump over to the live site. Uh but uh first I a few a few slides before we do that and first what is data? So that stands for data analysis tool for all and it is an easytouse resource that provides replicable data analysis examples inspired by real world questions and actual data from legal services organizations. Um, largely when I'm using data from organizations, it will have been completely anonymized and well, I mean, it's always completely anonymized, but uh, you won't even know what organization it's from, but rest assured, it is from a real partner organization of yours. And the idea is that you'd be able to follow these very detailed examples step by step and and recreate uh, some of the examples that we're going to show you. This uh actually grew out of an LSC funded TIG project from over a decade ago that was a partner project between the Legal Aid Society of Cleveland and Montana Legal Services Association. So it was during that project that I conducted a bunch of analyses of the vulnerable populations for those two programs and uh we thought well gosh you know we've done this for ourselves. Let's turn this into some examples that others could use. So, we had an earlier iteration of this tool, but it didn't have anywhere near the level of detail uh a as the as the tool we're going to be showing you today has. Oops, sorry. So, Shelley, did you want to tell folks a little bit about where to find it? Sure. So, I've dropped the link in the chat um for going right to it to data on our website, but data is housed on our tools and resources um section of the website. As you can see um the highlight there on the screen. If you click on tools and resources over on the left hand side of the menu that opens up, you'll see data analysis tool for all and then the get started. And we have made we we want everyone to start from the beginning. So that is why we've highlighted that get started page. And if you go there, you are right and ready to use the tool. All right. So let's jump in. Can you all see the site? Okay, great. So just as Shelley talked about, here I am on LSNAP's landing page. And I apologize if I periodically look to my left, your right. Um I have it up on another screen. Uh, so I'm going to just do exactly what she told us to do, which is go to the tool, uh, hover over tools and resources and then slide over here where it says data analysis tool for all and get started. And so this takes us to the landing page. And I'm I'm going to uh go through, you know, go through all kinds of parts and show you some examples today. But what I really want to sort of focus as the sort of primary actual tool is this green and blue box. This is sort of your matrix tool from which you can select your data question uh with and these are high-level data questions. Throughout the site there are examples of more detailed data questions that you might have. So you could select one of these high-level uh data questions about topics like who is eligible uh who requests assistance. So think of that as um uh folks who come through and are pre-screened or go through the intake process. Who do we help? So that's you know who are we actually providing service to and and on the flip side then who are we not providing service to? Um how do we help? So that basically is focusing on levels of service, limited service versus extended service and then what resources are required and specifically we're talking about hours here because that's the kind of data we can pull out of case management system. So this is hours worked on uh cases in different activities and then so you could you know select which question you think you might be interested in and then likewise select one of these analyses types that you might be interested in um and click on the start exploring and be taken to an example which we're going to do here uh shortly and and but before we do I did want to point out one I'm looking at my notes I wanted to point out one important tool because you might look at this and think, well, I have no idea where to get started. I kind of have a vague sense of what I what I'm interested in knowing and but I'm I don't know how to how to even pick which analysis whatever you're unsure about. If you scroll back up to the top of the page, there is a link here for the analysis guide and that has really I'm just going to click on it. If you scroll down, I'm sorry for the I know the scrolling can sometimes make me dizzy in webinars, but if you scroll down, you will see these each of the data questions and each of the analysis types with a dropdown. And you can go in here and there's going to be some detailed information some a description of what's for example who the who is eligible question is asking and it's saying generally what are the characteristics of the people who live in my organization service area and have income below my organization's poverty limit and then there's some detailed sub questions that are the kinds of things legal aid organizations have had me help them answer and that so this kind of detail is available under each of the data questions and then likewise under each of the analysis types you can click here I've clicked on trend and I see a definition trend analysis examines changes over time to identify patterns spikes or dips and client conditions or service needs our purpose is to track improving or worsening conditions progress or regress and emerging issues some examples some uh key insights etc so I urge you to if if you're back and we always go back to this get started to get back to that uh to our tool. You know, I urge you if you're if you're not sure where to start to look at that, but also I urge you to just get started. Click on one of the combinations and go ahead and look at an example and see uh see if it makes sense uh for you, if it might help you answer the question that you have. I'm going to go to our first example. Before I do, and I should have said this right at the start, this tool is not your typical website in that uh we were not trying to be uh efficient or concise with our language, but I mean as much as we could, but what we were really trying to do was give you very detailed instructions that you can follow step by step to get the anal the data you need and the analysis. is that you need. So for some of you, if you're experienced data analysts, this may feel a little bit elementary. I'm hoping you some of the analyses are quite complex and so I'm hoping that um you'll still find use out of it or there might be some tips and tricks in there um for you. But if you're someone who's who's afraid of data analysis or inexperienced with it, this should walk you through step by step exactly uh what you need to do. So, I'm going to go ahead and start uh with clicking on who requests assistance. And if you remember, I said that sort of think of people who go through the intake process. They're coming to us requesting assistance. And I'm curious about geographic concentration. I'm not going to go into it now, the difference between the geographic concentration and geographic distribution, but that's the kind of thing you would uh potenti either look at examples or look at the analysis guide to to clarify for yourself. So, I'm I've highlighted those two and now I'm going to click start exploring. Okay. So, I'm going to point out a few things to get you familiar with the page. So on the left hand side you're going to see we've got our sort of matrix tool there um for easy access if we need to change the question or change the analysis type we can just toggle between those different buttons and always hit submit after we make our new selections for a new example to pop up. You're always going to see the description of the analysis type copied up here at the top of the page just remind you what it does. So what a geographic concentration does is uh compare high or low concentrations of multiple variables to understand how location impacts client conditions and it uses a concept called location quotients to quantify those concentrations. Um so that may sound really confusing but we will see how this works and I think it'll make a lot of sense to you. actually isn't a complex concept uh once you start uh playing around with it. But the reason we're doing it is that it highlights area where services could be ramped up to better meet client need and it can pinpoint hotspots or regions with specific emerging needs or re uh or resources. So in this example, our question, our example data question is how does the proportion of people from different parts of our service area who request assistance? So people who go through intakes, how does uh that compare to the proportion of eligible people in those different parts of our service area? Uh in this particular example, this is data from Community Legal Services of Arizona and um and then external data about their eligible population. And what and we're I'm going to what we're going to end up with is the map you see on the screen. And I'm going to show you uh show you how to get there and explain to you what it means in the end. So say you you you see this and you think, "Yeah, this is this is what I want to do or I at least want to see what it's all about." you scroll down and under recreate this analysis, there are two sections, data sources and example analysis steps. So, we're going to go ahead and click on the data sources. And in this case, we're we're getting two different kinds of data. We are getting uh eligible population data from the American Community Survey of the US Census. And there's a a link here uh that will take you right to the data source. And it this this tells you a bit about what's in the data that we're looking at, the the specific table that we're accessing and a limitation that could be important for legal aid organizations. So that is that we can look at detailed characteristics uh at the poverty level below 100% of the federal poverty level. But many of you serve clients below 125% or some below uh 200% varying um varying levels. So there is that that qualification that that in order to be able to look at different demographics like race and education and gender and and you name it. We are going to be looking at that 100% below 100% poverty population. But the advantage that it has is that it gives us uh detailed information about even small counties particularly when we use five-year samples. Um so and I'll speak a little bit more about that in a minute. Then the second big piece of information is intake intake data from your case management system. And this gives you suggestions about the fields that you might want to download when you're from your case management system when you are grabbing that data. Some demographics, some dates you might need, some case information. By case information, I mean things like legal problem code, close reason, etc. It gives you some ideas for how to filter uh the report and how to structure it. So, uh, when I when I say structuring, there's some advice there about getting just one row per record or per case. Um, and then it suggests an exporting format. Uh, and there's a screenshot there. I know many of you use legal server and there's a screenshot there about how to set up the ability to export to CSV. I think that's become more uh I think there now is actually a link to be able to do that right on report pages in legal server. But in case you aren't updated or you don't have that, there's a screenshot there that shows you how to download the data in CSV format. And the reason that that can be very important, and I don't know if any of you have run into this before, but sometimes when you download to Excel, your dates don't download in the proper format. So I am always suggesting to folks that they download their data first as a CSV file and then you can save it as an Excel file. So we've looked at the data suggestions and then now we're going to go to the example analysis steps. And so here's where I say we provided all the details. So it's step by step. You can follow this word by word. It's not summarized. It's not a it's not a a brief highle look. It's a in the weeds detailed look. So, this is really a tool. Um, not sort of a a presentation of ideas. This is a get down in there and get your hands dirty. And so, I and you know, I can't in the time that we have I can't go through all the steps for you, but I want to just highlight what you're going to see and and the sort of level of detail that's there. This again gives you a link to the census site. Talks to you about multiple ways you can find that suggested table. Uh the S1701 uh poverty status in the past 12 months table. It talks to you about uh exactly what you need to click on when you're in that site and provides you with some screenshots from that site about what you can expect to see. because I know for some folks when they first land on the site it can feel a little bit intimidating. I don't know what to click and I don't know where to click and there's all these different windows and so I've tried to include screenshots anywhere. I think it might raise some confusion for a user. And I just want to point out that many of you if you're already using data you understand why we sometimes use five-year census data and sometimes use one-year census data. uh and it's the it's the uh you can get more detailed information or I should say uh lower level geographic data in the five-year average tables um as you can compared to the one-year tables. But of course, especially if you're trying to look at trends, it's nice to be able to look at one-year tables. There's a link here you can click on to get more information about how to make that selection. So again, this walks you through how to find the table. It tells you how to select your geography, shows you some screenshots of, okay, I've selected county, then I've gone into the state of Arizona and selected the five counties I need. It even gives you this little detail. This is the kind of thing that can trip you up when you're just starting. Number 10 there. Once all your geographies have been added, click the close panel button, the two little arrows. That's the kind of thing that I sometimes when I work folks who haven't worked with it before, they're sort of stuck on this window and they don't know how to get to what they really need to see. And so there's even that level uh of detail in here. Um there's some some advice about how to download the data. And then down uh step 14 tells you, okay, now open your data file. And there's suggestions about how to get the data formatted and and uh uh instructions for which exact rows you need to look at. In this case, we're looking at uh the total population. And then we're also looking at the population below 125% and below 200% of the federal poverty level. Just a clarification, you can get total numbers at those different federal poverty levels. If you want things like race by poverty or age by poverty, you're stuck with the lower than 100% federal poverty level. But in this case, we're just looking at overall poverty. So, we can look at those different percentages. Okay. Then part two is telling you about collecting uh internal data from your case management system, giving you suggestions about downloading it, and then right away popping into, all right, here's how you do a pivot table. And so again, if you're someone who knows exactly how to do a pivot table, all right, you can scroll down. But if you're not, um, this will walk you through step by step. It even suggests things like making sure your fields when you're looking at them in the pivot table are sorted in alphabetical order so it's easier for you to find. It suggests whi which fields you put in the columns and rows um and and you know what you're looking for and what it's telling you. Then we scroll down to part three which is combining the internal and external data and performing calculations. And so what we're doing here, it's part of this lo location quotient idea is that we need to know the share. So what we downloaded in that in that table that you see there in the middle is uh we downloaded the county uh and there well the intakes data is from our case management system for 2023 and then that less than 200% poverty population is from the data we got from the census table. And those those columns in blue are where we calculated the share of intakes by county. Then the share of the poverty population by county. And then we calculated the location quotient that number over there in column K with by dividing the share of intakes by its share of the poverty population. So what we want when we look at that location quotient then there are instructions here and let me also point out there's a link here with lots more details about how the what the location quotient means and how you can interpret it. But in a nutshell anytime a location quotient number is between 75 and 1.25 we're going to consider that to be in the normal or expected range. So in this example, all of the counties in the service area except for one are in the normal service range. The top county, Le Paz County, is slightly higher, meaning that it had slightly more intakes than we would expect, but it its share of intakes is slightly higher than we would expect based on that county share of the poverty population. So then finally this tells you okay you've gotten all this data you've done these calculations how do you create a map and probably many of you know but I know some of you don't know because I often share with folks and they're surprised that you can create a pretty easy map right within Excel. You don't have to have mapping software to do it. And so this tells you exactly how to do it. There's a insert maps. You select filled maps and and then it gives you information here on how to format what the map what the map looks like step by step how to change the excuse me change the colors edit the title and then I have a final suggestion that you just add a little note excuse me which I've added to that image that excuse me indicates that what I said before that those ation quotients between 75 and 1.25 are in the normal range. Below 75 are lower than expected, meaning intakes are lower than we would expect, and above 1.25 or higher than uh than what we would expect. So, so that's the you first example I wanted to show you and I I hope you're getting a sense of how uh how the tool works. Now, let's say you look through this and you decide, you know what? I I actually I have a different question. Or you you look through this. This was great, but I'm I just have another question that I need to answer. So, I'm going to go ahead and say I am curious about how we help our clients and I want to look at a snapshot like the the one one point in time on that. And so I click I I had hi hopefully I didn't do that too quickly. I highlighted those radio buttons and clicked submit. And we were taken to our next example. And again as we saw before the description of the analysis in this in this instance it's a snapshot analysis which I mentioned gives you a measure and a period specific period point in time um and uh talks about the purpose and different examples. I'm going to jump right into the example here. So, our question is uh what were the demographic and legal problem characteristics of the people who received advice or limited service versus those who received extended service from our organization last year. I know this visual is probably a little bit small, but what we've really done easily within Excel is to create a dashboard um that I'm I'll show you how the steps instruct you to make one just like this. And in yellow up at the top, it might be a little bit hard to see, but is a slicer. So that so we can go back and forth to answer our question right now. Oops, sorry about that. My apologies. Okay, let me go back. So remember our question is we're wanting to look at the difference the differences in characteristics of uh the people in cases who received advice and limited services versus extended services. This is a static image of the dashboard and it and this one the slicer that's selected is extended service. And so it's showing uh age and race and whether domestic violence is involved, gender, ethnicity, uh disability information, problem categories, close reasons, and poverty levels for folks who received extended service uh from this particular legal aid organization in 2023. So let's say you're interested in in recreating this kind of analysis. We again click on data sources and in this instance we only need closedcase data from the case management system. We're not using any external data uh in this particular example. And so again as we saw in the other one it gives you recommendations about the fields to download the dates uh to download the case information to download and suggests filters uh what to filter in what to include and how to structure the report. And it again shows you this formatting to make sure you're downloading uh that we're able to download the report into the CSV format. And then okay, now this looks like the craziest, silliest, who would ever make a website that looks like this page, right? But there's a reason for this madness. So what this the the first two steps tell you to download your data and then the second one is to create formulas and it says that that you want to create these and add these to the data you just downloaded into columns at the far right that it's important that you do this before you start creating pivot charts or any kind of analysis. So the reason that this looks like this is so that if you wanted so so your data let's say your you age it intake downloads with all everyone's age you know uh 24 37 59 whatever well but you want them in ranges and so you can literally come to this page this is why this is so detailed and highlight the formula copy it and put it right into a cell in in your Excel document noting of course. So I've noted here for you below that a uh ai2 that cell that I'm refer to in the formula is where in my data age at intakes at. So you may when you put it into your data maybe age at intake is in column J. So your formula would be J2. Um and then likewise AH2 is date of birth and uh your that's an important part of this formula as well but you would need to change the reference. Just a quick side note as to why I always include date of birth and and included in part of the formula. This is to avoid making it look like you serve way more infants than you do. You may have run into this where blank ages download as zeros. And so then if you try to do an analysis of the ages of the clients that we are helping, it'll look like you serve thousands and thousands of infants. And so what this formula does is uh to to filter out sort of um anyone whose date of birth is blank. So if their date of birth is blank, their age is also going to be blank. And so when that happens, you're often going to get a blank date of birth and a zero age. It says we're not they're we're calling them uh what are we calling them? Unknown age. Um so I won't go into all the details of how the parentheses do that. Um but that's just a little side note as to why uh why that particular formula has those two columns. But a lot of them do. So, poverty ranges. Uh likewise, if the type of in I'm sorry, if the type of income field is blank, that might lead you to when you're analyzing the data, it might lead you to say, "Oh, wait. We've got many more people uh with zero income, 0% poverty, when really it's just those fields are blank." So that likewise helps you uh strip those out uh and avoid overexaggerating the folks with zero income. So there's lots of examples here. You won't need all of them, but they're there in case you want to copy them. for ethnicity for uh disabled whether domestic violence was involved and I'll uh mention that domest the domestic violence formula includes legal problem code and the field is the caller a victim of domestic violence. So sometimes you'll have a case with a if you're an LLC funded organization 37 domestic abuse but the box for whether domestic violence was involved or not has not been checked. This operates under the assumption that if that legal problem is selected that there is domestic violence and it takes care of that uh data entry error uh for you. And then finally a level of service formula that helps you identify advice unlimited service cases and extended service cases which goes back to our ultimate question here. And there's just a screenshot showing how those formula fields are copied to the far right of the data that you have. This next walks you through how to create a dashboard or pivot charts with a slicer to compare those two levels of service. Lots of details like we saw before about how to how to do a pivot table um or a pivot chart, excuse me, if you've not done those before. I won't walk through that. It's similar to what we saw before. Um and then help with formatting visuals. So, and how it might look, you know, I know in this example, I know I wanted a pie chart, but when I first created the pivot chart, it gave me a column chart and so how to how to change that and ideas about changing labels and color and um just making it, you know, formatting ideas. Um, and then finally, it it suggests that you repeat the steps that you just did to create visual charts for each of the demographics or case details that you might be interested in and plopping all of those onto the same tab uh or screen within uh within Excel. And then finally, step five tells you how to make a slicer. In this case, we want a slicer where we can toggle between different levels of service. It walks you through all the steps about setting that up. Um, what you need to do to make sure the slicer changes every visual that you've included in the worksheet. And then finally, gives you some images here, some static images of what the the dashboard easily created in Excel looks like. In this case, the slicer is sitting on in vice and limited service cases. And then down below for comparison, what it looks like when the slicer is uh extended service cases are selected via the slicer. And then finally, it has some information about how once you've set something up like this, you don't want to have to recreate it every time. And so what you can do to keep the visuals, this dashboard the way that it looks. um but update the data. And so there's advice about how to do that without, you know, messing up the visuals or having to redo them. So there's one final example I want to show you with the caveat being that I'm going to go and let me say before the caveat, um I'm doing who do you help? So, this is who do we actually serve as opposed to who we have to reject or unable to serve. And I want to look at a comparison. I'm going to go ahead and submit that. And the caveat is that uh we are waiting on the web designers to make a change on this page for us. And so, I'm going to show this to you because I really want you to know about this example. Um, but I also want you to know that there's going to be one little tweak that needs to be made um, which we hope will be made very soon. So, this so this is a comparison. We're comparing uh, uh, we're examining relationships between two or more variables to uncover insights about client conditions or data linkages. And we're highlighting disparities, disproportionalities, differences, relationships, or conditions requiring further investigation. In this particular example, our question is, how does the racial and ethnic makeup of the people who request and receive assistance from my organization compare to the racial and ethnic makeup of the eligible population? In this case, uh lower than 200% of the poverty level in my service area. And are there any racial or ethnic groups who are unrepresented in uh in our served cases? And so what what this example uh where this lands us is the ability to compare. The top left pie chart shows the eligible population data broken down by race and ethnicity. Then the served intakes. So the intakes who went on to receive some level of service and those not served mostly that means rejected. Uh, and you can do a comparison. And I'll just highlight what this what this jumps out and tells us right away. When I look at the top two pie charts, I can see the light blue slice that the poverty population in this particular service area uh is 42.3% made up of Hispanic or Latino people, but those being served are only 32.4%. So this might tell this organization um you know this holds everything else equal. There will be other uh factors at play for sure and the organization will probably know some of them. Um but but they this would be the kind of thing that might make them sort of dig in a little bit and see why are why is that a little bit uneven? Is there something that we could do to reach that population uh uh more effectively? So, but this is where I'm going to stop showing you the web. Well, I'm gonna I will Oh, no. I'm sorry. I am going to show you the data sources and then I'm going to have to switch back to the to the PowerPoint. The And here's the reason I wanted to show you this example even though the the formatting thing I'll show you in a minute is problematic. This uses the American Community Surveys public use microdata sample um via this tool called the microdata access tool. And this is this can be a really powerful tool for us to use because it provides that detailed information that you can't get in the American Community Surve survey um at different poverty levels. So, if you're looking for lower than 125% uh of the poverty level and and lots different demographics that you can uh put in different combinations, you can um limit it in all different ways by different demographics. And it it doesn't have to be 125. It could be 137 if that's your um your number. This tool gives you a lot of flexibility in that regard. So it's a really useful tool. The limitation there are two limitations. I've only listed one here, but the one I've listed is that it's only available at higher level geographies. So states uh the public use micro data areas which I believe have population most of them have populations of about 100,000. Um and and depending on your service area, some of those will be really small. if it's a densely populated area, some of geographically some of those will be really big if it's a sparsely populated area and then the nation and region. So there are some some uh geographic limitations. The other thing is this tool is not uh intuitively very easy to use. Uh but but lucky for you, you have this tool because it shows you how step by step how to use it. Um, I won't go through the details of the intake the recommendations then for the intake data. It's just what we've seen before except limiting it by intake date for example as opposed to close date. I'm going to switch back then to our PowerPoint and walk through very quickly because I'm cognizant of the time that this uh what you will see. Oh, actually let me just quickly switch back and show you the problem because you may still be able to use this under the example analysis step. The issue that we're having, you'll see, is that the right hand u margin, the words are cut off. Now, you may still be able to use this. The links are still there. For the most part, I think you'd be able to sort of figure out what the words were. >> So, Rachel, one one little trick that they can do is right click on the screen and they can get the print friendly version and see all of the text. >> Okay. Super, super. So, that's great to know. right click and you do print friendly. Let's see. Did I >> Yeah. >> Uh I don't see it. Am I >> um >> Well, go ahead. >> I was just going to say we can play with that later, but there are other ways like you could print it, you can save as PDF. Um but we should have this corrected very quickly. >> Okay. And you did say uh you've been able to see it on some larger screens. So it it may work just fine for you because it's not visible on mine. I am going to switch back over to the PowerPoint. And the main thing I really want to highlight for you is the stepbystep instructions about using this MDAT or the micro micro I'm sorry micro data access tool. um because again it just shows you step by step exactly what you need to do on this not terribly userfriendly resource. Uh and so it's it walks you through how to select your data set. The first screen that pops up, oops, my apologies. Oh gosh, my apologies. Okay. How to select your data set and your vintage, meaning the year. Um how to select your geographies. It tells you at this point you need to X out of the screen in case again you're stuck on a screen and you don't know what to do next and you're worried if I X out this will everything will go away. No, it won't. I'm telling you that that you do that here. It it walks you through then how to download different variables. It tells you exactly what they're called. Here's an example of this not being terribly intuitive. The race field, there are multiple race fields. The one I'm recommending that you use is called I'm so sorry. I've got the uh screen. Okay, there. RAC1P. Well, that might not jump out at you. And so, I'm giving it to you here um along with several other fields, uh telling you that you don't you put them in the cart. And then I I'm I'm so used to scrolling down on the website. I'm sorry. That's why I keep doing that. Um then once it's in the cart there at the bottom, how to create groups and reabel categories. So what this gives you, like I said, if you wanted to look at less than 137% of the poverty level, you can do that because some of these fields like the poverty level for example is a continuous field. So you can define whatever categories you want to. And so this walks you through exactly how to do it. I will point out that it also has some extraordinary detail. If you don't want the high level, I think the the race field that I picked has something like nine categories, but there are other race fields that have 200 categories. So perhaps you do a lot of immigration work and it's it would be helpful to you helpful to you to know uh much more detailed race and ethnicity information. Uh you can find those variables here. So this I mentioned that this the data tool walks you through in an example like this how to create groupings from continuous variables. Um so I'm not going to stop and and and go through the steps but just show you exact you know step by step this is exactly what it looks like. Um, so that we and then it tells you how to how to arrange. You'll look you'll look at the screen and it'll ask you how to arrange columns and rows and that might not be intuitive and so it walks you through suggested ways to do that. You may play around with it and land on a different way but it walks you through my suggested methods um such that you can end up with um and again it's clear on the website. These are screenshots, but you you the the table on the left shows you the raw downloaded data. And then I've gone in and formatted it in the right such that I can get where I finally need to get, which is that table at the bottom that shows me the Hispanic population and then various races. And what this does, I know some of you are aware that one of the problems with using census data is the fact that uh the Hispanic population can uh uh for many of the race fields, it's inclusive of the Hispanic population and then it can be confusing because there's different uh options for the white population whether it includes the Hispanic population or not. Well, this walks you through how to separate out the Hispanic population um and then all of the race fields that don't have any ethnicity information. So you So those really are uh unique th in that bottom table. Those really are unique categories which matches tends to match legal aid data better. Okay. Now here we saw this before. These are the same exact formulas that I showed you in the last one where when you're on the website, you can copy this coding exactly just in your Excel uh in your Excel file after you've downloaded you've downloaded your intern uh intake data from your case management system. Oops. Oh dear. And then, oh shoot, I think I hid a page I didn't mean to hide. You know what? I'm going to just I'm just going to scroll down here on the site. Uh, that wasn't that's not in the PowerPoint. So, I'm just going to say it shows you now again what we've seen on other pages, how to create uh the charts, pivot tables, I'm sorry, pivot tables that we're going to use to create our charts. So, we've got now what we downloaded from the MDAT tool for our eligible population with our case management system data. We have the intakes that we were able to provide service to by those same categories and then those to whom we weren't able to provide service and then it it walks you through how to create those pie charts that we saw at the beginning where we can do the comparison that I mentioned that shows that the Hispanic Latino population is slightly under represented in those cases that uh received service. So, I have flown a little bit. Let me just get us back up. I would just want to show you a few other things that are available. So, there are 25 examples. I'm going to scroll all the way back and go up here to our back to data overview. So if you you know there's 25 different combinations of these uh data data questions and analysis types and they all have varying there they all use various kinds of data various kinds of visuals uh there's lots of uh mapping and I will mention the mapping that is available in the geographic concentration and geographic distribution options is nothing where you are where you need any kind fancy spatial GIS software or anything. It's it's stuff that's available in Excel, in Microsoft PowerBI. Um, I think those are the two main options. But if we scroll up to the top, I just want to highlight that there are some other the other parts of the of the tool that I'd like you to know about. First is data resources. And so this gives you suggestions for sort of the common fields you might need from your case management system are internal data options. I call them key data fields to gather. And then if we scroll down external data, there's a lot of recommended external data sources for demographic data. And that's everything from uh government data, think tanks, foundations, uh all sorts of sources. And then some ideas about other sources you might look for on the right there. Courts, uh different different uh cities and counties, state different state departments like of aging, children, and family services. And then I've listed just a few. There's there's uh four local think local think takes, foundations and researchers from different parts of the country. There likely is something like this wherever you are. Um so this these are just a few examples of that. Then scrolling back up to the top looking at our our uh bar across the top tips and recommendations. Lots of details in here. why we need to watch or uh why we want to watch for data patterns and some examples where that can uncover some information that we weren't expecting. Uh some ideas about data integrity dealing with difficult data. Uh factors that can skew the data lot. So, there's some I would suggest and when you're playing around with it that there's some uh some good ideas with real world little descriptions of issues that have popped up as I've been using this legal services data over the last 15 years and some ideas about solving them. Um there's a page with partnerships and a whole bunch of information here about all sorts of different kinds of partners that you might consider university and academic uh institutions, data focused nonprofits, local and regional government agencies, research institutes and think tanks, professional associations and networks, technology and software providers, foundations at grant makers, private sector partners, community based organizations, ations, legal technology, startups, lots of partners out there for you to consider. There's a tab I won't even click on, but you're welcome to click on it. It's a description of the origins, the project uh 10 years ago with the Legal Aid Society of Cleveland and Montana uh legal aid services that that uh started all of this, got the ball ball rolling. uh but I do want to highlight there's a data FAQ that has uh questions that we've heard and then for example how do I start exploring data for my service area and there's a little answer there uh down here well maybe I am interested in GIS mapping systems how can I learn about that well we have some answers here about some spots you might look for some some training u all sorts of different questions Okay, I'm going to take a breath and maybe a sip of water. And let's see. Let me Oh, let me just point out that the the link again to the analysis guide there, as is the more detailed uh explanation of the location quotient. So, let me hand it back over to Shellyley. >> Sure. So, the too long didn't read version of this is that the data tool is there to provide step-by-step directions to show you how to recreate what what Rachel has provided for you, but then take those same steps using your data and be able to do try new things and then we have suggested other questions that you can answer using these same steps. So that's what data tool is. So we'd love to answer questions if anybody has any. I haven't seen a lot in the chat. But um if you have questions um while we're waiting for questions, we can point out that um Ellison Tap recently released a video um a data management and v visualization toolkit and it is videobased and it talks all about video um all about data and but it's in a fun video format. So I'm going to put the link to that as well. So, if you're just getting into data, that can be really useful for you as well along with data, the data tool. Um, anything else that you would like to point out, Rachel? >> I don't think so. Did you want to mention on this slide the the list the meetings, the list serve and the webinar? >> Wanted to do that. Yeah. >> Sure. So we actually have now a monthly meeting of data statisticians that that get together. Every other month we have a little bit of an educational component as part of the meeting and then on the um opposite months we just have a chance to ask each other questions, share what we're working on. Um and it's a great opportunity to meet other people who are working in data and come and ask questions that maybe you have um that you need assistance with. We also have our list serve that's available that if you want to join and find out what's going on in data. It's one way to get questions answered in between meetings. And then our data webinars on our events page, you can filter events by different things. And one of the filters is by using data. And let's see, let me get the chat back. Um, and I'm going to just put a link to the events page, but you keep an eye on the events so you know when we've got new data things coming up. Oh, too. We says you explained everything too well, Rachel. So that's great, right? But we we really encourage you to go out and try it because we kind of used me as a guinea pig. I'm just going to be honest with you. I'm not a data person. So I was able to walk, you know, follow the steps and and and do things. So if I can do it, so can you. So I really encourage you to give it a try. >> Yeah. I I just want to reiterate that. I I uh I tried really really hard to make these instructions as clear as possible so that you really can easily replicate them. Um and so I guess my my sort of final tip would be there isn't a single instruction in there that isn't important. So even though sometimes it feels like a lot, if you read every step and do what it says, um you should be able to end up with the kinds of visuals easily, you know, without having to learn potentially new software uh uh you know, easily. So, I just I hope that it I hope that it proves to be uh the easy tool that I think that I think it could be. >> And yes, Brian, we hope that it is a great starting point for people. That is the whole point is that organizations who may not have a data person on staff can can take this this information and then start using their data for whatever purpose they um might want to use it for. Um, so yes, you know, we know that there are people on this call that have the skills already, but you know, this we we think that if you look through, you may learn a few tips and tricks that maybe you had not seen before, but this is really for someone who has not done this type of analysis in the past or maybe you've not done a certain kind of analysis and you want to expand your skills. And I guess the final thing I would mention also is that uh we're hoping periodically uh either once a year or once every other year to update you know for example I'm really hoping that the census improves the MDAT tool although I don't know if that's going to happen in the next few years but um eventually hopefully they will uh improve that tool and so maybe there wouldn't need to be as many screenshots. of the instructions. Uh, and so we're we're planning on keeping it updated. The last one we weren't able to update and this one we want to be more of a living tool that advances as the the data tools advance and the data resources become more user friendly. >> Yes. So it's a lot of dense information but it is all there for a reason. So, you're not going to come to for a pretty web page, these aren't those pages, but for a helpful web page, we hope that these will serve that need. All right. Well, it is the top of the hour again, so I want to thank everyone for joining us. Um, I appreciate Rachel for all of her work and in creating this data tool. Um, it has been a labor of love for Rachel. She has spent countless hours working on this and we'd love to hear your feedback. So if you have thoughts, please let us know. Thank you so much.