Dive Deeper with Human Capital Research Corporation: Maximizing Your Slate Instance Using the Power of Datasets

Man, as we wait for everyone, will you enable the screen share feature?

So.

I don't see it in my control panel.

That that should do it, Chris.

Perfect, perfect. Let's see.

That may have dropped drop off as well.

Yeah, probably reboot.

Do you see an Arab?

I still do not see it, Matt.

Yeah.

Alright, another another minute and then we can get started, I think.

Cool.

Chris Robin, if you guys are still having issues though, just reload the screen and reboot it.

Refresh I should say.

There we go. That didn't matter.

Thank you.

That wasn't fun. I would have been like the weather meant just put a monitor behind me.

All right, well, I think we can get started and welcome everyone to this week's edition of Dive deeper. This week we are.

Welcome to have human Capital Research Corporation. The topic today is maximizing your slate instance using the power of datasets. Thrilled to be with Chris Browning and Rob Galarza, both of Human capital research. My name is Matt Imperato. I'm a senior program manager with technicians and you know, without any delay here, I'll let Chris and Rob get right to it.

Fantastic. Thanks so much for the warm introduction, Matt. And today, we're going to be talking about maximizing your slate instance using the power of datasets. So it's going to be all about what is datasets and some examples. But before we get started, we'll just do quick introductions of Rob and myself. Rob and myself lead the slate services practice app, human capital and we are the ones that run the slate team for all sorts of different services that we offer.

That human capital, one of the many different product lines that the firm has.

So as part of this presentation, we'll talk just really briefly again for those of you who aren't familiar with HCRC, who we are, what we do and then dive into why use custom datasets, what are custom datasets, what are the use cases for them, why are they powerful in your slate instance? And we're going to explore in depth three particular use cases. We're going to talk about academic program management and utilizing datasets to centralize program management and logic around different programs.

Going to talk about how you can use datasets for parent and delegated access records and the associated portals that can be built off them, and then talk about how datasets really are the backbone of slate for student success and how it allows you to build your slate student success model exactly how you need your data structure.

And as we get started, just a reminder that if you have questions, please throw them in the chat as we go. We've got folks moderating the chat. If we can answer the questions during the presentation, great. If not, we'll wait till the end. Hopefully we'll have 5 to 10 minutes to do some basic Q&A at the end.

Thanks, rob. So human capital, we've been around for a long time as a firm. We were founded in 1991. We're based in Chicago, but we have a national, international presence in higher Ed and we focus on four different.

Major areas of higher Ed services are our Slate Services division, our quantitative analysis and consulting division, anything from financial aid, leveraging yield prediction, market development, student retention studies. We do a lot of survey development and deployment work and then we also have some executive consulting services. So wide range of different things that human capital offers.

But let's dive right in and talk about what is a data set. So Rep what exactly is a data set?

Thanks for asking, Chris.

Ohh, so most of you on the call are gonna have some familiarity already with what data sets are and how they function in your slate database. But at their core they're just constructs that allow for unit level data in an area that's different and separate from your person and application records. So again, if you've been to Slate user for a while, you're going to be mostly familiar with the organizations and organization context datasets and so those comprises delivered standard out of slate, but they represent.

The site idea that it's a way to track information and store data on records that are not person records.

They functioned very similarly to person records in a lot of different ways, but they're they obviously are a little bit different. And as Chris mentioned, there's gonna be 3 different areas that we look at. Custom data sets for academic program management, parents, delegated access management, and then student success.

Last quick note about datasets is that just like the orgs and org contact datasets, they can have a parent child relationship, and that'll come through in some of the examples that we shared today.

So why should we use datasets? Datasets are a great way to expand the data that you're storing in slate, and they're extremely flexible. You can create datasets just or about anything. And most importantly, datasets can be related to different things in slate. Natively in the field editor, you can have a field that is a related data set row, and that can connect datasets from one data set to another, to entities to person records. And if you can think of some sort of relationship, that can't be accomplished through that.

Standard field related data set row functionality you can create, with configurable joins, your own set of relationships between datasets and other data and objects within Slate. So this creates a really powerful framework for relating data to one another to power all sorts of different processes. Additionally, datasets, because their records in the system come with all the powerful built-in functionality that you get with record data in the system. A dashboard timeline, the ability.

Which is an example #2 that we're going to talk about the really important the ability to have a login capability to have an account.

It also allows you to connect to other standard slate tables and slate. Just like a person record. You have the device table, the address table, interaction table. So you can collect similar standard data and information on a data set record just like you would a person record.

And there really, as I was saying before, they're really easy to relate to other records and objects in the system. And when you layer data sets with entities, they become infinitely more powerful because you're no longer limited to 1 to one relationships. But you can utilize the power of entities for A1 to many relationship or even a many to many relationship between different data elements.

Alright, easy example we'll see you later on is having a person scoped entity that looks at student course enrollments that has a related field to our courses data set that then allows you to unlock storing all sorts of metadata about the course itself.

And lastly, since it is a record, it means that you can sculpt all these other functions in slate to a data set, whether it's a form, whether it's an event. Again, entities or portals can all be sculpted to that data set, and you'll see examples of all of that as we go through the presentation.

So, large question, it often comes up, especially at the graduate admissions level, is how do I manage all these different program specific requirements? The University of Kansas has over 400 different graduate programs. They all have not only different application requirements, but different deadlines, different people that are involved in them. So how can I centrally manage all this logic in one place without having prompt conditions that are a mile long or infinite or statements?

In comes a custom data set that centralizes all the data for program management. So here you can store application requirements, what checklist items should be required for that program, personal statement, number of recommendations or resume.

Additionally, you can store contact information about that program so you can easily then direct students to the correct recruiter or program director, faculty chair, specific website, all against stored on that data set, record in store deadlines. So perm specific deadlines for when a program might open their application, close their application, extend their deadline, and then it's a great way to store SaaS or other integration data. So Slate has some great tools using translation codes.

Other ways to export values to store that sort of SIS data, but if you go the data set approach, you can all store that in custom fields scope to the data set as well, and ultimately it's all about improving efficiency.

Limited number of staff resources trying to manage hundreds of these programs really can simplify and centralized the ability to manage that application logic your rules your deliver with the dynamic deadlines for communications. So I'm going to go in and show you a few examples at the University of Kansas and how they're utilizing the program data set.

So like all data set records, you have a query base. You can enable lookup on that query base. So when you go to your records tab in Slate, you can see that programs are appearing here.

Zoom in, make it a little easier for folks to see, and you can search your programs just like you would.

Any other record, you can see it counting. There's four different accounting programs at Kansas.

Or, for example, if I were to go into computer science, you can pull up my computer science PhD and now here's our data set record, which represents the program. You can have tags associated with it. You can have details associated with it. Here's an example of who the admissions contact is, who the faculty director is, and you'll notice that these are hyperlinked because these are actually related to another data set. There's a user's data set that has data about different users, different personnel at the University of Kansas, and you can click.

For that, and it takes you right into that data set record of the user. So the interconnectivity, the relatedness of datasets that are easy to set up really make them even more powerful. We're collecting different data about the program, the type of degree, that level which campuses it's offered at, information about their website or other data and then moving on to the requirements tab. Now this is where you're actually able to centralized what is required.

For that program, now that can be used to power different content snippets different parts of the application parts in your deliver emails. Because you're relating the program at the student selected back to the data set, that gives you access to any of the data that's stored on the data set record. One of the most powerful ways to utilize this is by attaching a terms entity. So here we have an entity that is sculpted to the program data set and that allows us to have one row for each term.

And within each term.

You now have a series of term specific data for that program. So not only now are we at the program level, but we're at the program level for an individual term. And here we're keeping track of when should that program be available for a given term. When's the application open date? Is there a priority deadline? What would that be? What is the final deadline or an extended deadline? When's the final date for review where reviewers have to have all their applications?

Reviewed by you can use this for infinite number of date tracking or any other term specific program specific by term data that then you can utilize in your business processes.

So what does this mean? What does it look like? It means that you now can enable the programs themselves in a decentralized model to come in and have a form that updates their data for their particular program, and it results in the ability to have a dynamically updated portal of programs, their degrees, locations, and then their deadlines. So now you have a central repository that can be updated when you update the data set to point students to when is the priority.

Deadline for my program? When is the final deadline for my program? So it's great that now you have an easy place to see this information, but how do you actually put it to work in that application to streamline that back end efficiency of your cycle?

Here.

In the application itself you can select your different programs.

What sort of computer science?

And you'll see that it's showing me spring, summer and fall as available entry terms if we return back to the computer science program. That makes sense because both summer, spring and fall are all open and the final deadline has not been reached. But say we want to go to.

Civil engineering, civil engineering. Excuse me.

Say we want to pick a program that does not have a certain term, the final deadline. We'll use aerospace engineering really quickly. For example, maybe the summer 2023 deadline.

Already passed.

I go back into.

The application.

And pick.

Aerospace engineering.

You'll now see that only spring and fall are available because the deadline for summer has passed if I change that deadline back.

Refresh my page.

And now summer is back available. So no more having to edit prompt conditions every time a deadline gets updated. Deadline gets changed through the power of data sets, the entities, and configurable joins. There is one filter on your prompt condition for each term that dynamically manages it based on that central program data set.

Saves you a lot of time.

Hey, Chris.

You also can use that then for your different drip communications and dynamic communications. So for example there can be a sort of.

Yes.

Sorry, real quick, just back to your earlier point about the the dates for the terms. This goes back to something you said earlier is that the this is now going to be enabled for end users at the program level, whether program department, departments, program chairs, etc, to go in and manually change those dates through a form that directly updates the data set. So that means that your staff don't have to intervene at all if you don't want to. If a program says, you know what, we're extending our deadline.

15 days, they can go right in there and change it themselves without actually accessing the back end of the system, but through a form that is tied through URL parameters to that specific data set.

And also means that you can leverage this for deliver campaigns. You can have dynamic emails that can go out a set amount of time before one of those deadlines. So by program, anyone that is an inquiry or in progress applicant for that program can get these emails at dynamic set times before the deadline for their specific program, again all with the use of configurable joins relating back to that data set. And you just have one filter that.

How dynamically sets the dates for when these messages should be delivered instead of managing huge, complex or statements in different logic?

So that is an example of the power of program management datasets.

And of course, if you have any questions about how this works or other functionalities, drop in the chat and we can address them at the end.

So the next example that we're gonna walk through is apparent data set. We're called, we call it parents delegated access. Because of course we know that not every person that a student is related to in some way could be a guardian, it could be someone else in their lives is not necessarily a parent. So we'll use those terms interchangeably. But just as a heads up, that's what we mean by delegated access to somebody else that a student is saying is cool to look at their record, because what we hear a lot is that schools want to recruit, improve their relationships with.

Parents to say.

Not only information about deadlines and things happening on campus, but how to securely provide information to those parents about their students, and specifically in information that a student has said is OK to share with their parents.

You know, one of the schools that we work with change the terminology from helicopter parent to a lawn mower parent, right, that there's this level of.

Just oversight that parents want nowadays over what's happening with their students. And what we've done is built a series of portals and a data set to manage all of this.

So we partnered with High Point University in North Carolina to to help develop this and I'm going to walk through a couple of screens here in a second. But again what this allows us to do is give parents the ability to see a curated view of their students information and their student success journey. So at any point along the process, the parent has insight directly into this and doesn't have to bug their student necessarily to get access to. They probably all have their credentials anyway for their.

Students, let's be honest. But this way they'll have their own set of of credentials to log into a place and see what's happening with their student.

They can also do things like register for events on behalf of their students, as well as send various notes and nudges to their students through these different portals.

So with that I will share my screen.

And walk through.

What's happening with high point?

Is the screen flickering for anybody else?

It is rob.

OK, let's try this again. Take 2.

Alright, should be good now.

So the Panther parent page is what was called they're the Panthers if you couldn't figure that out and so stop one on the journey, here is an application scoped portal for a student to help manage their parents ability to see the information. So again, simple application scope portal.

And on here there's a couple of different things. One is a button to add a new user.

To enable access to to share their information, they can toggle it on or off as needed.

They can select what type of information they want to share, so it's not a one-size-fits-all solution for parents. So five point we're just designating between financial aid and application info.

Provide basic info. I'm going to go ahead and fill this out real quick and say Gandalf.

The Gray.

I'll just use my e-mail again.

And he is.

And legal guardian. OK, I need to tell you what.

Give me access to everything.

And So what will happen is.

When this page refreshes.

OK, well, you can imagine what it'd be like if I did.

What will happen is that record will show up here under the accounts pending activation and what literally happens in that moment is that an entity row is created, a person scope entity on that student's record.

So parent Panther, parent access management, you can see the different relationships that I have established with my test record and so this will get added to the entity and then a process will kick off that essentially sends this data back out of slate and then back in to create a corresponding data set record with this parent or guardian information.

That process, as it details here, can take up to 24 hours. It's usually much, much less. It just depends on when slate our windows of opportunity to send data out in through SFTP or through different web services.

Then if you go to then again part of this process is to create a data set record for that parent and if you go to that record under their data set you will see again dashboard and similar other items. But at the end you also see another entity on the data set record that establishes this relationship between the data set record and the student.

And what this allows you to do is have a many to many relationship between the data set records and the student. So that way if there is a parent that has multiple children they have the ability to see all those.

Children all their children's records that they have now given access to through the parent portal or vice versa. So by using entities and datasets layered upon one another, you can create a robust many to many relationship.

And that same student can belong to multiple data sets as well. So here you have my test record belonging to Chris's test record as well as old Bilbo.

So if I go in here as Bilbo into their side of the portal experience.

You'll see something like this where as Chris mentioned, if Bilbo worked to have many students related to them, there will be a different section for each one of those students. Here you see a breakdown of buy application. That's the lens we're looking through here by application. The record for in this case, Rob.

If I go into.

You follow application.

This is the main the main space for the parent. So a welcome from the Dean or director of admission Admission Counselor Info, the ability self-service to update their username or password.

Um, we've developed this idea of a bulletin board, which is a way for both internal staff and also students to be able to put things out there for the parents to see while they're exploring their record.

The ability to to send a note directly to the student.

From here.

Oftentimes this will be something along the lines of.

Hey, I see your checklist is incomplete. Didn't we do this thing? Blah blah blah right? So just provides another opportunity for parents to bug their kids basically about the stuff. But this uses a form and form communications to deliver this message to the student.

At the bottom of the page you've got a variety of different tabs to display other information for parents, and so in this case it defaults to our enrollment checklist.

So again, it's exact same checklist. It's just pulling a CJ query to help power the display of this checklist information.

There's an overview tab where parents can see again what type of information has been shared with them, other general information about that student's application.

They could also see, if the student has been admitted, what their admission letter looks like.

And other information about other decisions that would be on the record.

Um, also just links to other resources and then just again more information about what's happening with the student.

And those tabs through liquid markup can all be dynamic based on where the student is in the funnel, but more also important, which permissions the student has given the parent. So again, thinking about if you transition this from admissions, you can apply the same concept to enrolled students and current students. And when you have to worry about FERPA, the ability of having the student to be able to control and delegate the access, revoke that access, change permissions at any time.

Allows you to have the student be in control of their data.

Yep.

This.

Um, event information. So it's going to provide you both with a list of upcoming events that are relevant for this student, and that's curated also on the back end, it's also going to provide a list of events that the student has previously attended and filters recordings and other things associated with those events. That can all be displayed here.

And of course they have the ability to just click through.

These different lists.

As needed.

Also built in the ability to manage different honors and allows applications things related to scholarships and such. So gives a status what the four in this case, my record is eligible for four different things there. I think it's upwards of 12 different possibilities here, and it tells you more information about it in this accordion and lets you know what the status is for each one of these respective opportunities for the student.

And then it could be simple information like this, just information about paying for school. This is very much intended to not completely duplicate information that's already available on your school's website. It's designed to supplement and really be a guide to point students and parents when this case point parents to those resources that already exist on the web. When we do these portals, we're really careful not to duplicate all kinds of content that exists that people already spent a lot of time building elsewhere.

Just it's important to point people to those different web pages.

Same thing for residents. Life and then.

Other summer programs, et cetera, et cetera, right. So you can see here, it's just a very customizable way of.

Delivering content to a parent or guardian, whomever that is specific to their student and what and characteristics about their student.

Alright.

Christopher.

All right, so student success, student success. One of the most powerful parts of slate for student success is you have all the tools that slate provides you at your fingertips to really build your own platform. It's your blank canvas and datasets should be front and center.

For that canvas, as you're building and integrating data from your SIS from other campus systems, data sets are a great way to layer in all the data that you use to track a current student's journey. So things like course catalog courses, term data that's coming in to support the academics that you have with you so you're able to see the students coursework in progress. Their past course is how they're performing in them, having that employee data set that faculty and staff.

Data set that we saw at the University of Kansas for programs again becomes important here. So now you can relate which course is being taught by which Professor. So you have instructors, buildings and locations, which is really cool. You can layer on buildings and locations so you know exactly which room that student has that class in and where that student is right now. And then very important to student success is this idea of case management, this early alerts, early warning system. And then.

Getting cases and one of the most powerful reasons to do your cases as a data set is it gives you the ability for each case to have its own record that can be used in workflows, can have forms sculpt to it associated with it, and then you can build out all sorts of associated workflows for your business process for the different types of cases that you may input for a student. So you're creating your own data model that fits what you need as a student success office.

Has different offices across campus and utilizing data sets and entities on top of the student records and the relationships between them to build a really robust system.

So Albion College wanted to deploy slate pristine success to really have their Cutler Center for Student success, to have much more data at their fingertips to allow the student success coaches to allow faculty to be able to quickly identify students who may have different needs, students who are showing those early warnings and be able to then deploy different interventions and techniques there. So we're going to share and look at.

Albion College student success instance.

So here we see a number of data sets, so students is our person record, just our standard person record. But then as I mentioned on the previous slide, you have building and rooms data set, the case management data set, courses for the catalog as well as individual classes, the course instances of those courses that employee data set terms data again about that individual academic term.

And applying them all together, you can build different student records with these different relationships built in. So our good friend Tommy Matterson here you can see he's currently registered for two courses for the fall term showing up right here you have who the instructors are. You can e-mail the instructors when the meeting pattern is for that course, even what is midterm grades, what is final grades are, what the enrollment status is. And again the relationships allow you to easily connect through from.

The student record to the course instance so I could click on the course.

And now I'm in.

My course instances in the data set record for this specific course section and I have details about the course.

An entity, because at Albion you can have multiple instructors teaching the course that shows who the instructor is. The instructor. Again, another data set here with a related field and the course instructors entity takes us yet another layer into the employee record themselves.

But.

Time and location, same idea. The buildings go into the building, look at anything on the building, record what's being taught in the building, who's in that building, etc. And then also student enrollment, so you could actually get a updated course list. All this data is being fed between the SIS and slate nightly. So you're getting refresh data from the SIS that's working in parallel with additional data you're adding in Slate to provide a really comprehensive view for.

That users of the student success database.

Also, if we look at Tommy here, we can look at any cases at Tommy has open, so we can look at has a case been open. And yes, Christopher Berry opened a poor performance case.

Tommy yesterday and we can actually click into that case and now that case itself is a data set record and we can look at the case management details.

Again, it relates back to the student, relates to the case manager, all sorts of notes what's being done on that case.

Also can have a workflow that looks at case management review that the student success staff can have to see new cases coming in, assign them, review them, see what interventions are being applied and then closing the case.

All of this comes together not only for the administrative user since late who have access to the records themselves, but in an easy self-service portal.

That faculty and other users across campus can use and the.

Different buttons, the different tabs that are available are unique again through set of permissions to what your role is at the university.

Faculty members can look at their enrolled student list. At any point in time they click in enrolled student list, they're going to see the ability to search on those courses, search and those students.

Provide advising notes. Open up different cases on them. Advisees. Same way if I'm an advisor, you can see my advisees see it. Ohh. Tommy has an open case. I could submit a new case. I could submit a public advising note. I could submit a private note that's available just to myself. You know, also if I'm a case manager's ability to look at what are my open cases, if I run a specific program, what students are in my programs? Coaches for athletics, and then Cutler centers, those student success staff being able to just.

A quick view of all students.

I click in all of these. I'm going to see the students that are part of that, but I can click in and now I get a unique student record view that connects back to the SIS. Connects to Degreeworks, allows me to have deep links into other enterprise software that's being utilized on campus, but also get a quick hits of data that I need on the student, including maybe academic course history.

Or academic standing.

Advising updates.

And all the way to cases where again I can review, add new cases, add things here that can be shared then with the appropriate parties also in this portal for.

Student success, student retention efforts.

So the portal becomes a really powerful way to bring all those student records, all those data sets together into single spot that where you can find actionable data and take action for the purpose of student success.

Back end, again, it's just utilizing the tools that are available across all instances of slate, whether it's admissions, student success or advancement, and putting them together at work to be able to come up with a comprehensive solution for different business processes at the university.

Again, layering data sets along with entities makes them that much more powerful. Almost all of these different data sets again have entities then attached to them. That allows you to have more one to many relationships or many many relationships that can click through between the different data sets, records, system objects.

So these are three examples.

Of how datasets can be applied, the really the opportunities are limitless. There only by your imagination, your business processes, your business needs, other things that have been approached and with great success before. Financial aid tables, reference lookup tables. You bring in individual awards items into your database from your financial aid software. So now you have data on each scholarship or each loan. You have metadata stored all about that again can relate to which.

Rooms have those awards which students have awards pending. So you can layer that with entities on the student record to really create some robust financial aid integrations. Human resources, same thing. There's some schools out there that are using slate for human resource functions and datasets and entities tied to those make that really powerful inventory management. Another one for admissions offices, you can design an inventory management system with a datasets that can control inventory for your.

Print. Print pieces and when interaction codes are assigned for those print pieces, it can automatically update then the counts in those data set records for your different print pieces. Preferred partners. There's a lot of preferred partners, including us. We use datasets and entities to manage contracting, to manage our different service services with different institutions, with our partners. So the list goes on and on and how data sets can really be used for all sorts of unique.

Purposes that can a make slate more efficient, but B just expand the power of slate into all different facets of the university ecosystem.

Yeah, absolutely. Great to great questions. Perhaps let me pull that back up in Albion.

So here we're back in Albion. We're on a specific class and we're looking at either the instructors or the time and location. Do you notice that little icon right there that says look up here in Mason and then if you click on the icon, it takes you to that employee record on the data set. So here this instructor name is a related data set row field.

And in this case, the field is actually sculpted to the course instructors entity and that entity is then scoped to that course instance or that class instance. So if we look in our fields.

We'll see.

Our instructor name here.

And our data type is a related data set row, and the related data set is the employee data set. So now when you have that field if we were to.

Add a new row I can look up.

Because it's a related data set row and instructor and anyone in that employee data set is going to pop up and it will autocomplete for me.

And what's being done behind the scenes is the IDs that the GUID behind Darren's data set record is what's being stored to make that linkage and slate as part of its standard feature set. If you have a related data set row field that you're displaying on an entity row on a field, it's going to automatically create that lookup link for you. So if you set up the fields to be related, slate is going to do the work and make it easy for you to jump back and forth.

Between those related records.

Yeah, absolutely. So when you create a new entity.

In databases you have the ability to set.

The scope of that entity record. So for example if we do our course instances instructors.

So I'm going back again to our class. We have our instructors, our course instructors entity.

The scope of that is going to be to the course instance. So each row on the course instructors here is going to apply back to a single data set record of course instance and.

That's all configured when you're creating your entity. You can insert your scalps and you can see with entities you can sculpt them to any records object in the system. So person and application or any custom data set then that you have created.

Yeah. Now I I think you covered that really well. I always just add as kind of in layman's terms, if you're looking to collect more and more complex data relationships than a data set is the way to go. So in simple terms, the more complex.

Amount of data or relational data to something you have, the more you should be thinking about data set versus entity if you're thinking about a collection of related data points.

That's great for an entity. So I think of the classic example in admissions is financial aid items, right? So a student financial aid offers made-up of multiple items. Each item has multiple data elements to it. It's name, it's amount, the term it applies to. That's a great use of the entity, which is just a row of data that's all of multiple data points all related to one another. Going back to Rob's example is doing success case management. Now you're talking about.

Potentially dozens of data points. You're talking about workflows, you're talking about wanting to submit forms that are sculpt specifically to that. And when you get into more of that complex data model, that's where datasets really shine because they have more features that can be tied to.

Oh yeah, so if I understand the question correctly.

And in Albion you see that this class instead of having anything on a dashboard, there's this student enrollments tab. I won't click it because it actually has live data, but what it is, is it is a related data set row query, but we've simply placed that related data set row query field on a custom tab instead of on the dashboard tab so that can be configured in.

Fields.

And here we have our data set real query.

That is connected to our student enrollments tab. So we've created a custom tab that is scoped to our course instance data set, and now we've placed that field that is that data set URL query and that student enrollments tab instead of the dashboard which results in that.

Query listing of students who are enrolled in that course at a separate tab instead of having to display on the dashboard record.

I understand that question correctly, Katie.

Perfect. Cool.

Noel has a great question about when for student success example in particular, we're bringing in a lot of data and also in Kansas bringing a lot of data from the SIS or other systems. So talking about the integrations piece of that and that's where really planning things out with your IT partners, whoever is managing your SIS on campus becomes really important and starting to talk about what does that data exchange look like, how is the data structured in general.

Yeah, once you're able to talk through, all right, we want the data structured in this way to come in the slate to fit into using upload data set are different data set records or entity records. Then using whatever reporting tool, whatever query management tool out of the SIS becomes.

Easier to manage, but it's typically we've done it on a case by case basis with campus partners. Sometimes the middleware is involved, you know there's some great middleware providers that are preferred partners of slate and sometimes it's just driven by the IT group at that university working with us directly on what should these files look like, how should they be scoped out and what should the cadence of them be.

Absolutely.

So much like uh, the default organizations and organizations contact which parent child relationship when we built our.

Datasets for.

Course and course instance. Course is the parent data set and course instance are the individual class sections.

Is the child data set, so we've just related on course instance to course to build that parent child relationship and then.

In here you can see that you have math 312, this specific instance going back and.

You can look up the course of math 312.

Here is the actual core, here is the actual course. And now on the dashboard here you have all the instances, so there's actually. This is the first time mathematical theory of interest was because we brought in like 20 years of historical class records, so new new class for them. But in a class that's taught every term, you'd see the multiple instances here, just like you'd see multiple org contexts tied to an organization.

Yeah, so that's really important. When you're creating data set records, you're creating entities that you want to make sure that you're either using a key already my echoing that again, sorry, OK, either on datasets utilizing the data set row key and storing a unique key and creating one in that value to merge and to relate the things or creating your own custom fields that are set to be unique for merging generally.

You know, you're you're wanting to put together data that is truly going to be unique. So going back to our LBM.

Example of course instances.

We're taking our term code.

And matching that with the subject, the core subject, and the course number. So this is math 312.

And this is our fall 2022 and then our section number. So this way we're generating a unique key for each data set row that then can be used. And it's coming from data that's all available to us in that upload. So going back to like Noel's question about integration, we have three different columns coming in from banner in this case, that's providing us what term this class is for, what course it belongs to in the section number. And this way we can always match that up and be very deliberate.

About what we're setting our keys to to relate them to the different objects.

And Matt, I know you've been monitoring the chat too. Anything that we may have missed that you want to bring bring up for us as well?

I sure know you guys have been on top of things, so.

Uh, but if there aren't any more questions, if we can wait just another minute or so. But.

Thank you all for attending and we hope you have a great afternoon and our rest of the week. And make sure to check out Mark Perlow in costume for all about entities for student success next Monday on Halloween.

Ohh, alright. Well Chris, Rob, thank you so much. This has been an incredible dive into datasets today. Thank you everyone for coming and asking great questions and we'll see you all next time.

Take everyone.

Thanks all.

Bye, bye.