Slate Spotlight on Data Explorer

Hey everyone.

There we go, I'll give you, I'll give you back control if you want.

Perfect. Thank you, Rob and hi everyone. As as you trickle on into this share webinar, feel free to introduce yourselves in the chat kind of in a typical technicians form here, say where you're from, what school you're from and how the weather is and we'll get started in just a moment as everybody logs in.

Yeah, I know you and I, Chris, we were talking about the weather just before folks started jumping on. I was telling you where I am in Pennsylvania, Pittsburgh, PA we have our first snow of the year today. I see it. Actually a couple other people said they're getting snow.

But.

Yep.

We were not in Pennsylvania. We were not expecting snow, we were just expecting rain, but it must have dipped a little bit.

Yeah.

There you go, Pittsburgh.

I feel left out now. It's funny as being in the technicians Portland office, we're pretty high on on what it would be. Latitude I believe is like the Easter W Lines and we are close to sea level because we're actually on the Willamette River so we don't see below freezing temperatures too, too often.

Oh, it gets nice and cold here.

Anyway.

We still have quite a bit of participants jumping on it, so we'll give you all just another second here.

Yeah, we can. Yeah. No, no worries. We can wait. Uh, another minute or two.

Let folks get on.

Yeah.

Yeah, definitely feeling left out. There is a lot of snow.

No snow, just cold in Philly.

Closer to the coast.

Yeah, other side of the state from me. People. People, a lot of people who aren't familiar with Pennsylvania don't realize it's a good five hours between Pittsburgh and Philly. So Pitt, Pennsylvania is a big state.

Large state.

Texas is a little bit bigger than.

I used to live in Texas and the drive from one side to the other I think is like 13 hours just to visit my parents.

Yeah, that's a little bit bigger than Pennsylvania, but.

Just a little.

But I can't tell you how many times, uh, I tell. I tell folks I'm from Pittsburgh and they're like, oh, you're near Philly. And I'm like, well, kinda.

Just five hours away.

Just just five hours away.

Ohh, there you go. Taylor Swift tickets went on sale today.

I, I, I, I have a few friends that are.

In that queue for their kids.

All right. What do you say, I think the participants are we're about at our Max, we can get started, right, Rob?

Yeah, absolutely.

Alright. Well everyone welcome. I'm just gonna get kicked off real quick here and then Rob Will will leave the show. Welcome to our Slate Spotlight series. This is data explorer with RNL. You're joined by myself, Chris Gonzalez, one of the client support engineers here at the technicians Portland office and Yep, exactly a nice little title. And then we have got Rob Talarico from R&L, he's a VP of CRM Solutions. Is that correct Rob, am I getting that? Yeah.

Yes, VP for CRM solution. That's my fancy title. I like to just say I get to play around with slate all day. That's that's a good way to put it.

Exactly.

Fun stuff. Alright, let's uh go through some housekeeping real quick and then I'll turn it over to you Rob. So as with all our events, they're being recorded and they'll be made available for viewing later. So if you like what you see here, feel free to share it with your colleagues and feel free to reference it later if you want. close captioning is available. Just click on the little closed captioning icon, the 2C's up at the upper right hand corner of your screen. If you want to focus on this webinar and not get distracted by your e-mail or the things going on next to you, full screen viewing can be enabled by clicking the.

And button up there next to the closed captioning window. If you have any issues at all, which we do sometimes have from time to time, just refresh your browser. That seems to do the trick. It won't kick you out, you'll be allowed back in. And often if like say the slides seem to be stuck or one of us seems to get a little maybe like we sound a little robotic or something, just reset the your Chrome browser there and you should be good questions can be posted in the chat. We'll be collecting them on and answering them at the end of this webinar.

And if the chat gets distracting, you can actually turn that off as well. Just kind of put it aside and just focus on the slides and Rob's presentation, so.

Without further ado, I will turn it over to you, Rob.

Thank you. Appreciate it.

All right. Well, as Chris said before, I'm rob Tallerico there you can see my my fancy titles. I think I somebody saw somebody comment on fancy titles in the in the chat. There's my fancy title. Just to kind of give you a brief background on me for those that I don't know, I see a few folks that I know in the in the chat, but a lot of you I don't. I have been with R&L for a little over a year now. My team at R&L works with all of our campus partners, R&L as a company works.

With something like 12 or 1300 campuses across the United States, every year my team works with many fewer than that, but we are our our CRM solutions team at R&L. We work with our campus partners in their CRM platforms. My team as a whole works with campuses that use many different CRM's. Slate though is my personal background, so I get to work with a lot of our sleep clients and participate in fun webinars.

Like this? Um, but I've been campus based like all of you or many of you are. Spent the 1st 13 or 14 years of my career working in admission offices in at institutions in Pennsylvania and New York. Started as an admissions counselor. My my last campus based role was as the Director of enrollment operations for a university in New York City, where I was the overall slate admin slate captain for the Undergraduate Admissions Office there. So lots of experience with slate.

After leaving the the campus world, the institution world became a slate consultant. I worked for another company that some of you probably work with or have heard of before joining R&L and I was there for almost 2 years as a slate consultant and I've been with with R&L ever since then. So because R&L is a platinum level preferred partner with with technicians, we get to do fun things like this like introduce data Explorer, I know a few months ago.

It's actually been just about six months ago I had the opportunity to to visit technicians New Haven office and they were doing an event for preferred partners and.

They kind of highlighted some of the new features that they were going to release at the at Summit and Data Explorer was one of them and that was data Explorer was actually one of the features the new features that I was most excited for that eventually got rolled out at Summit this year. So whenever they they rolled out data explorer and technicians was looking for partners to to pair to present some of the new functionality. This this is the one that I wanted to talk about I I was hoping to.

To talk about it, because I was most excited about this, ultimately, I'm a data data person, a data guy. I love data. I love being able to explore data and visualize data, and I know that Data Explorer gives us a lot of opportunities to do that. So to talk about Data Explorer today, that's enough about me. You're not here to hear about me or my interest in data Explorer. We're here to talk about Data Explorer and all the things you can do with it. So to do that, we're going to just kind of talk very, very briefly about what is data Explorer, what's the purpose of it?

We're going to then kind of start diving in and how do you use Data Explorer? This is going to be a fairly introductory session. Some of you may have already started using Data Explorer, Dove in and began building reports with Data Explorer. Some of you may not, some of you are maybe kind of looking to hear for the first time so this will be a fairly introductory session. However, that being said, there will be plenty of time at the end for for questions and I would love to go into more.

Depth, any questions that you have along the way, so please as we move, as we go along, as we go forward, definitely feel free to post your questions in the chat and we can either address them as we go along or if I'm not able to get to them throughout the presentation, we'll definitely have some time at the end to answer those questions. And we're going to kind of when we talk about using Data Explorer, I'm going to split it into two parts, right? The first part is going to be how do you actually start?

Getting update Explorer kind of from the back end as you're building the data Explorer reports. And then once that's finished, once the setup is finished, how can you actually use Data Explorer to manipulate the data and really create some neat things along the way. So with that, without further ado, let's dive in and I do think let's see the next slide. Yep, the first thing I want to do is just kind of pull the audience, gauge the audience to see, you know, where are where.

Are you with using Data Explorer? Have have you tried to use it at all? Or maybe some of you have not? Maybe some of you are already using it a lot. I'm sure that there are some folks that have become quite proficient already with it, so go ahead and take a moment and.

Let us know where you are.

So it looks like as we you know as folks are filling this out or as are responding to the the pole most of you are kind of at that one or two level either have not looked at it at all or or are just starting to explore it. Some of you have built a couple of reports maybe one or two or more reports small small number of you feel like you're already fairly proficient with Data Explorer which is great you know I might maybe feel free to.

Chime in if you see any questions, um, that that you think you've got great answers for. This is a collaborative experience today. One of the great things as we all know about the slate community is that it's very collaborative. So for those of you that have been using Data Explorer and have answers, feel free to chime in. I'm not, I'm certainly not the sole font of knowledge when it comes to to data Explorer. So why data explorer? You know, higher Ed thrives on data if you work in an admissions office.

In a marketing office, you know that there are tons of statistics, whether it's an enrollment office, whether you're working with current students in the student success module, whether you work in a fundraising or advancement office, everything higher Ed does revolves around data. And so being able to use that data to visualize that data in a way that's meaningful and helpful is it definitely helps us to do our jobs much better. Slate has always provided some tools to allow us to access.

Data to visualize data, but this is just kind of taking that one step further. But if I will be somewhat open and honest, I'm sure I'm not the only one who feels this way. This may not be slate sanction but I'm the presenter so I get to say what I want. You know sometimes slate has been somewhat limited in in what in the ways that you can visualize the data. I know folks that may have experience with other CRM systems especially things like, you know, Salesforce.

With that has more built-in data visualization, data visualization tools, programs like Tableau and others have certainly seen advanced capabilities when it comes to building to visualizing data. And and admittedly you know Slate has provided some tools for that, but have not always gone quite as far as as some of these other areas. And really data Explorer is an opportunity to begin expanding on that, right to allow you to to to use Slate to keep the data within Slate.

To to be able to better visualize the data similar to what you can with some other tools and specifically with Data Explorer. Data Explorer really allows Slate, allows you to build pivot tables in within Slate. I know currently I have a lot of schools that I work with that love to build pivot tables. They love that that sort of functionality, but they're they're exporting their data into Excel even or other tools to be able to.

Build these. So my next question for the audience do you or someone at in at your institution export data to excel to manipulate the data or produce different tables or charts? This is a simple 1A yes. No question. Go ahead and respond.

Oh, I saw a yes. Unfortunately, I agree.

But hopefully that's really what data Explorer most of you are saying. Yes, yes, yes, a couple of Nos.

Mostly yes.

Yeah, and so hopefully, um, data Explorer is going to be at least a partial solution to this so that you don't have to, if you want to create nice looking pivot tables that really allow you to manipulate the data and the ways that you want. Hopefully data Explorer is going to give us an alternative that you can use within Slate, a tool within Slate so you can keep the data in slate. You don't have to worry about exporting the data out into Excel or some other tool just so that you can get those that that.

Functionality.

So let's start. Um, let's let's dive in, and let's start talking about how you set up.

Umm, the data explorer. So the good news is, is that it already largely uses functionality that you're probably already familiar with. Hopefully most of you as Slate users are familiar with building queries, building, building other reports in Slate, and so to create a Data Explorer report. And I know that this this page looks a little busy, but we'll kind of walk through it here.

The.

The the way that you begin creating a Data Explorer report is the same that you would to create any other type of report in slate. So at the very top you'll see where the number one is. And again, I did mention this is going to be a very introductory session. I'm assuming most of you probably know how to build reports in Slate, although some of you may not and so I am going to walk through a lot of the steps here #1 highlights the the query and.

Reports tool when you click on that you will see kind of at the very top half of the screen. Here what the reports tool the query and reports tool. On the right hand side you see the number 2 highlighted. Where you have the first item is your query tool. The second item that is that is boxed in red. That's your reports tool. So after clicking on the query and reports tool, you can click on the reports icon and that's going to allow you to create reports. You can then create a new.

Port and by clicking that new report button on the top left hand side.

Umm and Umm, when you do that, you're going to, you're going to get a pop up and you're going to be asked to name your report and to folder your report. I won't spend too much time on it, but anybody who's used slate, I'm sure many of you know filtering is particularly important in slate and it and it's not just in reports, not just in queries, but across the system. So I I do, anytime I talk about soldering, I think it is important just to mention how important soldering is across the system so as you build your reports.

Um, definitely think about how you're going to folder your different reports. Think about how you can use the filtering structure to really organize your system in the queries and reports tool, but really across the system. So once you do that, once you name your report, you pick a folder for it, then you're going to actually go into your new report, which is kind of the bottom half of the screen here. And on the right hand side, just like you do for any report, you have your kind of report parts that you can choose to select.

And this is #5 that's boxed on. On the right hand side you'll see that the second item there is the data Explorer option and so you can either click this button or you can drag it. Just like any report. You can have multiple report parts within the same report and so you can you can just drag that data Explorer function.

Uh, right across. When you do this though, when you choose that data Explorer option, you are going to be asked to choose your query base. You'll have to name the report part, but which? You can give a name fitting to whatever the report is that you're building. But then you are going to be asked to choose your query base, and that's really important. Just like when you're building a query. Just like when you're building a report, just like you're building many things, a form or or a many other things in slate. The query.

Case is particularly important, and I see a question there. Can data Explorer views with configurable joints? The answer is absolutely yes. In fact, I would encourage you. I would encourage all of you to use configurable joins as kind of your default, not just with Data Explorer, but across the system. I would really encourage you if you're not already. I know more and more people as time goes by. More and more people are jumping on the configurable joins bandwagon and are doing a lot of great things with.

Configurable joins, but a lot of people still aren't you. Probably you've noticed as slate as technicians has rolled out new functionality, a lot of items in the system are beginning to default to configurable joins. And so there is going to come a time, I'm not sure when that is, but there is going to come a time where you have to use configurable joints. But aside from that, I think that there are just a lot of opportunities to better access the data you're looking for to manipulate the data in.

Ways that you want, and really just build a better query. Build a better rapport when you use configurable joints. So personally I always use configurable joins. That's my default. I would highly recommend to all of you if you're not using configurable joins yet. There's no better time than the present to start using or start beginning to use configurable joints.

All right, so after you choose your query base. So Thomas, to answer your question, will you be creating on your end and following along or just watching? Either one is fine. I will say because of the tool, the webinar tool that we're using today, I I will not be able to actually click. You won't see me clicking through, but I do try to through my slides. I do try to kind of take you step by step so if you did.

Want to try to follow along and play at home? Like I always like to say you're more than welcome and we'll you know we'll be doing some pretty pretty basic things today. So I would encourage you, if you've never used data Explorer, go ahead and do it. It's actually, it's not that complicated to do. It does use very steps that you should be familiar with from other areas within Slate.

Alright, so we're at the point now. We've created, we've gone into the query and report tool, we've created our new reports, we have added our data Explorer element or Data Explorer part and we've chosen our query base. I will say most most times you know the most common of course are going to be your person base or your applications base. But depending on what you're trying to report on there, you might end up using a lot of different bases. And this is again one of the reasons why I really like.

Using configurable joints here. If you want to do a message of messages mailings or messages query configurable joints query base you can easily tie that back to the mailing recipients. If you wanted to do a form responses query base you can easily tie that back to the the students that have submitted those those form responses. So you can certainly do that to kind of track things like the the the number of emails that are are are going out per population the number of.

Event registrations per population, things like that. But for the most part and what I'll be doing today is really just kind of using some standard person based exports and filters and using the person, the configurable joints person base. So we've added that base and then once you choose that, once you add that base, just like any report, you're going to get a pop-up that kind of looks like this on the screen and you're going to be asked to add some exports and some filters.

Um 4 U M4 data explorer. These exports and these filters are very important because this is really where you're choosing the data elements that are going to be available to manipulate later on. So as you can see there the notes that are on the bottom of the screen here, the exports, whatever exports you add, are going to become the X axis and the Y axis on your on your pivot table, and so you'll want to make sure that you add in all of the.

Exports all the data points, data elements that you'll want to be able to have in your pivot tables. The filters, as always, are going to determine what records appear in your report, right? So if we want to limit based on student type or term or program, we can certainly add filters in to do that. So an example of.

An example of some filters that I used today look like this, right? I've gone ahead and add some filters. You can see I am using configurable joins and I've added some filters for things like term and student type and program, but also some kind of demographic information as well. Citizenship, race, sex. The status there represents the person status. And so wanting to be able to to kind of use these different data points in my data Explorer, I'm adding them as exports here. Kim, your question will you?

Receive a copy of the slide deck after this webinar. I know that it is being recorded, so technicians I'm sure will share the recording afterwards to everybody who attended or was not able to attend. If you are interested in the slide deck at the end of the of the program, I will share my contact information as well. You can always feel free to to contact me directly and I'm happy to provide my slides as well.

Alright. You can also see down at the bottom here the filters which got cut off a little bit, but you can see some of the filters that I used. Again looking at terms, I wanted to limit my report to some specific entry terms. I think I limited the student types as well. I wanted to only look at certain student types and and so that way when the data gets pulled in, we have just the records within the data that we want to use. So we've added, we've now added our.

Exports, we've added our filters. We're going to go ahead and save this and then when you save it, the next thing that's gonna pop up is kind of on the top half of the screen. You're actually going to see a screen that looks like this and it's going to look blank at first, but that's because you have to one more time add in and explore element. Now one thing you may note, and I've seen this already, is that if you don't add any exports on the previous, the previous.

Gap, right if you kind of skip over this because a lot of times when you're building reports, you don't have to add exports. In fact, you may not even have the option to add exports. But you may not add exports when you're building a normal report in slate. If you skip that here one, it's OK, you can always go back. But two, if you don't add exports and you just save, when you go to the next screen you may get an error message. You might see an error message there. That's pretty common and we could probably get the the syntax of that.

Message. But the reason is is because you didn't add any exports. So you will get exports until or, I'm sorry, you will get an error message until you add exports. If you do for whatever reason miss adding those exports before, you can always just click that edit button at the top right hand corner of the screen and you'll be able to add exports or any additional filters that you like. There it is. Thank you Chris. There's in the chat, there's the error message that you will receive. You can add, you can click the edit button and add any exports.

Their filters to that report. As soon as you add exports and you refresh your screen, that error message should go away. As I mentioned though, the next step is going to be to add your Explorer Icon one more time, or your Explorer part one more time, and when you do that, you're going to see a pop-up that looks like the bottom of my screen here, where you have a couple of options, and these settings will eventually become very important because that's going to.

Determine what you can do with the pivot table or what your end users, whether it's you or you're building these reports building these tables for other folks. These settings will determine what you can do at the end of the the report, and we'll go into this a little bit more in detail a little bit later. But know that these these do matter. These these are important and just like anything else, you can always go back and update them or change them later on. So if you don't check these boxes or you find out that you want to check these boxes, that's perfectly OK.

So now when you finish this, you check the boxes or you don't, you save the the the explorer item, then you'll move on to the next screen. Before we do that, I do want to mention one other thing. Slate does give you the ability to add static content here as well, which really could be used in a number of different ways. It does have, it is like any other static content block in other areas of slate. It has an HTML editor.

So you can add you know, different images and branding if you wanted onto the report. You could use that static content to provide instructions to whoever your end user is going to be to kind of teach them how to use the drag and drop editor if you want.

So uh, but there is that option there to to add the static content if you wanted to provide some some additional information.

So once you do that, once you save though, um, you're going to see a screen, right? You're going to see the results of your setup so far and right now it's going to look like it's blank. But that's because you still need to set up the the rest of the report. What you will see is in the you'll see a number of columns here on the screen in front of you, and in the very left hand side you'll see all those exports, so anything that you selected as an export.

Previously on that previous step, you'll now see those things as exports for your report. So when you what you do next is you're really going to start building your table, your pivot tables, using the exports that you've added. If you. Again, as I mentioned before, if you determine later on that you.

Need additional exports. You can always go back and add them in later, so it's perfectly fine not to have them here.

So Next up we're going to, we have another audience poll question. This will be the last one for the the presentation today, but I #2 we were asking before, do you export data, are you building pivot tables at your institution?

You know, what are you doing? What kind of reports are you?

Are you doing?

So go ahead and if you if you do this type in the chat.

Yep, sorry. Uh, for those of you that were expecting the poll, this one's not an actual poll item. Just go ahead and type in the chat.

A lot of dashboards, funnel reports is a big one.

Seems pretty pretty.

Comment a lot of again a lot of funnel reports, I'm seeing a lot of that dashboards that sort of thing.

Alright, so.

Next, let's start looking at.

The things that we can do, how do we start building that? So we've set up our data, our basic data Explorer. How can we now go about beginning to build our.

Pivot tables. So at the top half of my screen here you can see um, Slate does use a drag and drop editor just like many other places in Slate where you can begin dragging all those items that in that are in that far left hand corner. You can drag those into either the the X axis or the Y axis to begin creating your table. So for example you'll see.

In my example, I've got term going across the top. I've dragged my term item across the top. I'm dragging the status item onto the. I guess that's the Y axis. And by doing that, by having the status and the term, we can begin creating our pivot table. But we can even take it a step further in that slate with Data Explorer now allows us to have multiple levels of data, and we can get to that just by dragging additional items.

Um, into the data explorer so as you can see, um.

The below the status item, right, the status was the first one that I dropped down. I've now added the student type as well. And so you can see that it both now on the Y axis going up and down, we first have the status applicants, inquiries and prospects. But within each of those statuses we've kind of separated out four student types. So that you see we've got our freshmen, our graduate students, our transfers and you can.

You can see that it's now split up the report appropriately.

Um, it does total up. So you can see both it totals across the bottom and down the side it will total up those.

It will. It does total up those, um in both ways, so it's pretty nice to do that.

All right. So can you do a percent of a total? Well, that that's a good segue because as we move on, if you click on right, the, the kind of the default is that in that middle column, which is right above those Y access things, the count is the default. But if you click on that, we can actually begin to change, we can add in different metrics, different statistics that we want to use. So we can sum things up. We can do averages.

It's it's pretty nice to be able to do that. One of the things that I felt was particularly helpful and where I could see an immediate use for this is if anybody's ever had to build like a profile of the freshman class with different metrics and characteristics. This should make you know, data Explorer should make it pretty easy to be able to to kind of build that sort of table for for your students. So for example here I'm using the average, the average metric.

And I'm gonna pull GPA and you can see, right as soon as I choose average, another drop down menu appears in that middle column and it gives me an opportunity to indicate what item, which data points that I have in my list on the left. Which data point do I want to average? So in this case, I've chosen to average the GPA.

Um, and so you can see that on the right I've got uh where where my table is, I've got the status and I've got the term. And so you can see term across the top, you can see status down the side. And for each of those groups, our applicants for each term, our inquiries for each term, our prospects for each term that I have the, the average GPA for each of those groups. So pretty nice that that we can kind of create that table pretty easily.

It does also create those totals, so it will kind of sum up and average out the the average GPA for all of fall of 21. It will also average out the the average GPA for all of our applicants for all three years as well in those total columns as well.

But just like the other charts that that we were looking at, um, we can add even more complexity into the chart. So on the chart that we look at here, we're still looking at average GPA. You can see that kind of at the top of that middle column there. And in this case, I've added program into our Y axis. So you see all the programs listed up and down and then you see we have two different types. We actually have term and student type across the top.

And so, you know, we can begin to look at what's the average GPA for each of these programs by student type, by term. And so we can very easily begin to manipulate this table. And you can change where the different data points sit. You can kind of play with and experiment to see what's going to be the most helpful just by dragging and dropping those data elements back and forth.

All right. The other thing that's nice about data Explorer and this can be done just by clicking on the items that you drag. So for example, you'll see where I have program here. In that middle column where I indicate I want program on the left hand or on the kind of the Y axis. The up and down Axis I want program I can choose to to to hide or display programs very easily. You'll see that next to program there is a.

A little arrow and I can click that arrow and it actually allows it has a pop up and allows me to unselect or deselect different items to to display or not display. One of the things that I saw was helpful. If I had done this before and took a screenshot of my entry terms here I would have you would have seen that some student records had not been tagged with an entry term and that there was a a number of of student records that had no entry.

Term. So I. In this case I deselected the the the entry term and here I've deselected the program, some of the programs as well, and so you can hide and.

You can hide that. What is the difference? So, Carol, good question. What is the difference of removing the programs here versus using a filter? If you know that there are groups that you don't want at all, I would certainly recommend that you try that with a filter. But you never know what kind of data that you get or what you might see. You might even if you add the filters in that you think are appropriate, you might still get some records that have some weird data, some funky data, and so doing it here.

Allows you to kind of remove even further refine the data that you have, even beyond the filters that you initially added a few steps ago.

Alright, so, so here this then. This gives you the opportunity to select select that Slate Data Explorer does also, aside from just pivot tables, it does now have the opportunity to create different kinds of charts. Of course, there's always been the opportunity in standard reports to create some bar graphs, some pie charts, things like that. But you can you can now change, you can select from a number of different chart element types you see.

In the top left hand corner there I've I've kind of squared where you can choose what type of chart or what type of display you want. Again the default is going to be a table that pivot table, but you can also do bar charts and line graphs and things like that. And what's even further, what's even nicer that technicians has added in is that once you choose a different type and you'll see here I selected a bar graph.

Or a stacked bar chart. In this case, once you once you select your additional um the the different type of graph that you'd like, you can actually double click on the chart area itself, kind of where those those bar charts, those stacked bar charts are and you see in the bottom half of the screen here you actually get a chart.

Setup tool that looks very much like the one in Excel, where you can select different line graphs and bar charts and things like that. You can also somewhat customize the actual display. The chart display you can move the.

The the legend around so you're you're different items where it indicates what items or what color. You can move that around to the top or the bottom, left or right so you get some of that same functionality that you have within Excel. If you were creating some charts in Excel using your data technicians has added some of that functionality here as well. So it gives you a little bit more of a few more options, a little bit more control over what you are doing.

All right, one other thing Umm, I do want to mention is going back before where where I was, I highlighted the those options that you had to either allow end user editing or not right or to person to allow the changes that the end users make to persist. So if you leave those boxes unchecked a few steps ago when you what you'll see is a slightly different pivot chart.

Or pivot table, because you'll notice that the ability to drag and drop those data items is no longer there. Those columns and rows where my different data points existed, they're no longer there, they've been removed and so now all that the end user can see is the the resulting table that I've created for them. And this can be helpful in some ways if there are standard reports that your users need that you know they always like to see the data displayed in in the same manner.

Every time that you can, we can display the data that same way over and over for them. And then in that case they really don't need to adjust that, right? And so there might be some instances where you don't want an end user to be able to change the tables and so you can leave those items unchecked, you can leave them unmarked. But if you do want for for different reports, you may want them to be able to play around a little bit.

And So what they get is really all of those data elements that you've set up and that you've provided for them. They'll be able to play with the different data elements that you want if you only check the first box, and you allow end users to edit regardless of what they do, regardless of which items, which data elements, they kind of drag and drop.

The table will always revert back to the way that you've set it up now. If you do check that other box persist end user edits that will actually allow you however an end user changes that chart, it's going to stay that way. It's going to stick that way, and so those are two different options that you have.

You cannot. You can always go back and change the accessibility. So if you decide, if you don't add it at 1st and you decide later on, yeah, I really do want to allow people to play with this or vice versa. And you initially think, yeah, let's give them the opportunity. But then you realize, no, we really just want this one report. We want it to stay this way. You can always come back and change those options.

OK.

So now just a few, now that we've kind of walked through some of the very basics of the very basics of Data Explorer.

What are some of the benefits of data Explorer? For one, the familiarity, right? As Slate users, I imagine we're all pretty familiar, or or mostly familiar with the tools that we're using to create these pivot tables and these charts. It's really, as you saw, the one big element that that I did there was to add my to choose my base, and then to add my exports and my filters onto my report, right? Other than that, it's all about dragging and dropping, moving the data elements around until we get a table.

That that we're happy with, right? That gives us the data that we need. So the familiarity, right. The tools are easy to use and we've all used them in other areas within Slate. The speed is another one.

The typically when you drag, if you move a data element from one place to another, either if it was on the far left hand side it wasn't being used and you drag it in for the first time, or if you switch it from 1 axis to the other, those tables will update fairly quickly. Now I have seen some of the comments in the chat, much like many other areas in slate, the more records you have going into the report the longer it may take for that report to update, but typically.

The the the data Explorer options, moving those data elements around from 1 axis to the other that the report does update fairly quickly. I know when I was kind of taking the screenshots for this report I was using a system using roughly 100,000 records in my in my data, which is a good number of records. I know for others that there are you know, other campuses that may use have many more records that they want to display or or many.

Fewer, but I was using about 100,000 records and it it worked perfectly fine. I did not have to wait long, so the speed is is very quick compared to a lot of other data tools within Slate.

The other thing is that you know, the access to data, uh, right, slate being the source of truth. Most of this data is being produced in slate. It's being stored in slate. And so, you know, why not just use slate to create these reports? I mean the data is already here. Slate is already being viewed as the source of truth. So let's continue to use Slate, if we can to produce some of these reports. And then the other is, is the ability to share, right. You can give folks access to the reports directly to give them.

Real time access, whether you choose to to allow them to edit, manipulate that data or not, you can give them that real time access just like any other report. You can also schedule exports. You can export these pivot tables as PDFs, you can schedule that and you can have those go out on a regular basis and then for the reports portal, this is something that I've done with a couple of campuses that I work with recently, is to begin building portals that display different reports on those portals and then making those portals.

Available to your leadership, other staff, other offices on campus, you can put them behind a a log in or not depending on how open you want that data to be. But being able to kind of create a portal where you're storing all of these different reports, or at least displaying them, not storing them, but displaying the different reports on your portal does allow you to share this data with outside elements. You're you're, you know, campus leadership for example, they're not going to want to have to log into slate, but if you give them a portal link.

All they have to do is log in, they can view the portal and they'll be able to see different elements as well. So that idea is something pretty nice as well.

Finally, um, the the data security, keeping the data within Slate. This is something I talk a lot with the campuses, talk about a lot with campuses that I work with, especially seeing how many of you export data to other systems. And I know that's that's just natural. But any time we're exporting data, especially when we send it, when we export it to an Excel spreadsheet and we send that Excel spreadsheet to somebody, to somebody else, we basically lose control, control over what's happening with that data. We don't know.

That those other folks are doing with it, we don't know where it's going. And so from a security perspective, from a privacy perspective, there there are some some real advantages to wanting to be able to use to build these reports within Slate and to use tools that are inherent in slate when possible.

All right. So that's um kind of takes us through most of.

The presentation for today, um, I know we had a lot of questions, a lot of chat in the in the chat, which is great. I'm glad people are excited about this topic just as I was. So Chris, I think you were kind of tracking questions as we were going through. I am not sure if there's a particular place that you wanted to start.

So there was actually one about if. If data Explorer is only limited to more recent terms and I'm gonna kind of like turn on you Rob for this one, you might know the answer. I'm gonna say it's not, but since you can build data explorer elements within existing reports, there's a chance that you'll be running into like top level filters that you had in an existing report that limit your results. Do you by chance know if that's true?

Um, I'm not sure I completely understand the question, but I'll answer what I think I heard. And so the question I think I heard you ask was are you limited to more recent terms, is that is that what I heard?

Right. Like, like more.

Yeah no I so the reason so in my report I was just showing you know fall 212223 that's because I limited my report to just those those terms you can use you can use Data Explorer for any data. Any data you have in your slate instance you can pull into data Explorer. But I think you are right Chris right if you were to go back to an existing report and kind of pull data Explorer in as a as a report element.

Or a report item within an existing report, right? You may have to be aware of any filters that you've previously added to that report, because that could kind of unknowingly or unintentionally limit the data that you have available to that to that report element.

Exactly, exactly. Which also piggies back up piggybacks onto another question we had which was can you use Data Explorer with reports that are already created? Which yeah the answer is yes you can. The icons there on the right I believe it's 2 layers into the report builder. You can add that part and build your data explorer.

Window there.

Yeah, I think it was probably.

Is it? Was it this slide?

Yeah, that would be it right there.

Alright.

Yeah, there you go #5. I think on the right hand side you see that you have your your data explorer element in the middle, but then you have, you know, kind of a standard and I'll admit I can't actually see that slide data and charts, right. You've got your standard data and charts report part as well and so you can pull in a kind of a standard report part and then you can add a data Explorer report part.

All within the same report.

Exactly. So it's pretty powerful tool there. Keeps you counted from needing to go out to other vendors such as Power BI or Tableau. Gonna get you some functionality within Slate to get some some graphical and analytical stuff available to you.

Uh, we had a question. Or we actually had several, and I know we had this actually come in right before uh, the.

Webinar itself when people were registering and there there has been questions about like row limits or the amount of records that can be returned. I personally have not run into this, but I a lot of the questions seem to be on the messages and pings table. Rob, I'm curious if you yourself have come across any roadblocks to the report builder rendering things. I would imagine that if you're not querying on larger tables such as the messages or the pings table, the report builder should work just fine. You're within the same constraints as the report.

Other itself where you have the five minute ability to render things. Of course it's a lot faster here. So yeah. Rob, do you have any experience with like?

Yeah. No, I think you're absolutely right Chris and I and I tried to throw this in knowing having seen seen that that was a question from at least one or two folks I tried to throw in at the end there. The the campus I was you know some of the charts that I was using are are from a campus that I work with. I got their permission, so don't worry so.

The data that I was using from their instance though it was about 100,000 records, which again is is you know a pretty decent number of records. I know you can go a lot more than that. You can go you know fewer than that. So I and I didn't have any any problems with that that number of records that the 100,000 records there Chris, I think you identified it right. I mean ping the ping table has its own.

I'm not gonna say issues, but I mean there are, you know the the ping table does have a a tendency to time out just because there could be so many pings. I mean you could have millions of rows of data on the pings table and that's going to time out anywhere in the system. It's not just data Explorer, but you know, even just running a query or or you know anything else, you can, you know, run into some some timeout issues with the ping, the ping table.

Right, right.

And sometimes the trick to that is just to limit how far back the data explorer the report the query is looking at that that data. I mean, if you're looking only 15 days back it might render successfully, but if you're trying to pull in the last year, chances are it will provide you an error.

Yeah, or to find other ways to to limit the data that you're looking for, right? I mean, if you're using the ping table as an example, you know try to limit the report to only specific pages on the you know, on the on the website, or only you know pings with particular UTM codes attached to them or things like that, right? Find other ways to to kind of limit the number of pings that you're querying on.

So that so that you don't run into those timeout issues.

Hmm.

The one from Dan here can you customize to add the total values to the columns in the bar chart so that you can see the actual numbers when you export?

Can you customize to add the total values to the columns in the bar chart so you can see the actual numbers when you export? Not sure I understand.

Because that's.

Same here. I know you can utilize like formulas, isn't that correct and you can aggregate?

You can use formulas, yeah.

Yeah, in fact I did that. Uh. In some of the charts that we were looking at, I used formulas to kind of group different elements together so they displayed as as one thing. But you know, if you don't do that, they would just display as however you have the data element set up in your in your slate instance.

And I saw this question earlier, it was about can you drag two items into rows and have them not nest. Now I myself have not played around with that in particular. Rob, have you?

Yeah, I'm not sure that you can do that. I think based just based on the the the the function like the intent of the the the pivot tables, I think the idea is to have them nest.

But you can. What you can do is if you wanted you know an option that you have is you can do you can create more than one data Explorer part within the same report, right? So if you did want to have multiple elements that weren't nesting right, you may want to create similar data Explorer parts on top of each other in the same report and that way they wouldn't nest with each other.

That's true. That's true. That's a good workaround there.

Um, if you just read the question I'm seeing here, if you go back and change the overall filters, the tables don't automatically reload. The best way I've found is you just refresh your page.

And that it will it will reload.

Customizing and export to PDF settings. I think it's pretty limited, but what often kind of toggle around with sometimes with that because clients are not actually printing it, but instead of just trying to make it something they can share with colleagues through e-mail or whatnot, it's just play on the page settings in your browser. Try landscape instead, legal document just to fit stuff in. That's often a good way to get things to fit in a clean format that might not be available in like the standard letter size portrait.

I guess is what you would call it. At least that's what you call it in photography, right? Output there.

Yeah, Chris, I don't know if there's one or two other questions that we want to tackle. I know we are coming up on our.

Time here.

We are um.

Let's see.

But these pivots work similarly as Excel pivot tables. For example, if you double click on a field, a list for those records would appear. Not quite yet. And this tool is very, very new, so there's not like too much feedback that we've received from clients yet and know what to build off of. So stay tuned, we'll see what it comes about. For now, the tool is very, very powerful, but as well, we want your feedback on where things can.

Go forward.

And as always, I would think, Chris, right, if there are some of these features that we really want to see added, that sounds like a great feature request for for the future, right?

Yeah, absolutely. Our feedback forms are there and you're always welcome to add your ideas there and upvote existing posts that folks have made. It is a very new feature, so we are in that area of just hearing your feedback, saying use cases, and then obviously trying to make the tool a more usable thing for every institution out there.

Maureen, are 100% stacked bar charts available are coming soon. I can't speak to the coming soon part and I have not. I haven't played with that specific example, but I know that you can make the data up here as a percentage of the whole and you can switch over to stacked bar charts. So you might be able to do that. I have not played around with that yet, Chris. I don't know if you have an exact.

Answer.

I don't. I myself am not a product manager here. That's that's one of the things that if we throw it in the into the feedback forums, eventually you'll get a comment back from our team telling you what our thoughts are on that or if we want more information on your use case so that we can build out the product in a way that works for your team.

Yeah.

Perfect.

All right. We are nearing the top of the hour. I think we probably cut it off about now. Rob, is that correct?

You wanna answer one or two more questions?

Yeah, so my you do have my contact information on the screen here if anybody wants to chat more about data Explorer, this is something that I've started working with a couple of campuses already with and intend to continue working with them because personally I think this is a great tool. I think it's a great step in the right direction as you saw, I think some of the comments mentioned, does it have.

The full capabilities that you know power BI or other programs have maybe not yet, but it's moving in the right direction. And I think you know I think that as we continue to use it, we'll technicians will hopefully continue to add to the features and the functionality and and and we'll have an even better opportunity to kind of manipulate and visualize our data within sight.

Seconds here act.

All right. Yeah. Thank you.

Alright, well thank you everyone. Please, uh, please do be in touch and happy slating.

Have a great day everyone. Bye.