Optimize Your Enrollment Processing with Constituo’s Slate/SIS Integration Solution

Hello hello good afternoon everybody.

Welcome, welcome today's slate stage. Uh, we'll give just a few minutes for, UM, folks to get in and get settled. Happy Friday to those that are joining us. Thank you for joining us on a Friday. I know after lunch on a Friday is not always that easy if you're on the East Coast, it's lunchtime. Suppose if you're on the West Coast, maybe it's a nice mid morning break for you.

If you wanna shout in the chat where you guys are all coming from and.

That would be great to see some some messages there. We'll get started in just a minute.

There we go. Thank you Matthew. Appreciate you being the first very nice.

All right, well, welcome to today's late stage I'm Sarah McGuinness. UM, most of you probably have seen me talking in these webinars before. I am the general manager of slate.org here at technicians. I'm just gonna do a couple quick intro slides and then as you know I will kick it over to our presenters. So today's title of the webinar is optimized your enrollment processing with constituents, slate, and SIS integration solutions so.

Then again.

Uh, our presenters today are Joe Kirkland, who's a sales director at Constituido Michael Carmen, who's a senior consultant at Constituido and Yvonne Brightness. I think I did that all right. Director of Admissions and Technology and operations at Kansas City Art Institute.

Real quick, a few housekeeping slides. As y'all know this webinar is being recorded and will be made available for viewing at to Festival pass holders after. After some point today in home Sleep, closed captioning can be enabled by clicking the CC button in the top right hand corner of the share window. Full screen viewing can be enabled by also clicking that expand button with the arrows in the upper right hand window should you need to resync your audio video, just go ahead and refresh the whole screen and that should help out. We've been getting some reports of some like echoing and tininess, so if you hear that.

Just refresh the screen. Uh, it could be a browser issue, and if you have questions please post them in the chat and these guys will hopefully be answering them at the end. If we have enough time. So without further ado, I'm gonna kick it over to Joe and team and we will see you guys in a little bit.

Keep trying to get to my first slide here.

And not having much luck.

There we go alright again, great to be with all of you today. Thank you very much for your interest in learning more about constituent and the services we provide to automate your slate and student information, student information system integration. Again, thrilled to be with you today. Michael Carmen is going to be providing a quick solution demo at the in the second half of the presentation today and we're absolutely thrilled to have one of our great customers join us.

Today, can't Yvonne Gronis from Kansas City Art Institute to talk about her experiences working with us.

First, a little background on constituido.

First and foremost, we are an integration platform, so we are what Gartner and other analysts would refer to as an I pass an integration platform as a service. So we're a modern platform. We're born in the cloud.

All of us at constituent, practically all of us at constituent, prior to prior to founding constituent in 2015, were members of our founders of a company called Knowledge Corporation, NOLIJ that some of you out there might be familiar with. Knowledge provided data integration tools as well as enterprise content management solutions specifically to higher education at the time of our sale. In 2012 we had about 225 customers, all higher Ed and we got the group back together in 2015.

To build the next generation integration platform specifically for higher education and that is constitutional.

Like our previous life, our exclusive focus remains on higher education, so the product you're gonna be seen today continues to approve, continues to evolve based on the feedback from your colleagues in the higher Ed community. And we're very proud to be a slate preferred partner for data integration. You'll find us on their on their partner page on the technicians website and hopefully we'll see many of you in a couple of weeks in Nashville at the Slate Summit meeting, which we're very happy with, all getting back. Getting back together in person.

So as I mentioned, we're an integration platform, so while the project we're going to be talking about today is far and away our most popular.

Our customers use us for a wide variety of integrations, so we've done integrations across every major SIS and ERP out there today in higher education, including some of the newcomers like Slate and Unit 4 and anthology. But customers will often use us for additional integrations once we come in to do the initial project, which very often is slate. SSIS customers will recognize that constituent can be utilized for other integrations across their enterprise, so we have done integrations.

With fundraising systems with HR Solutions, expense management systems learning management systems, really this list goes on and on and it grows every day.

Again, some of our customers. We recently eclipsed 100 customers over the last seven years. It's been very planned growth planned and measured growth on our end and really serve all every segment of the higher education community. Like to use the example of we provide the slate banner integration at the University of Georgia's main campus in Athens, and we also provide slate banner integration at Covenant College, also in Georgia that has about 700 students. So really everything in between.

And again, our exclusive focus is on higher education.

Little bit on a little bit on what we did last year. As far as volumes are concerned. Last year we processed about 331 million records across our platform, which is a great testament not only to the scalability but also the fact that customers do use us for a wide variety of integrations.

OK the.

Constitute integration sites are going to be seen today. Consists of three major components. First constituent gather, gather is our electronic smartform solution. You're going to be seen at an action today and providing the user experience for data remediation next constitutional map map is a self service data preparation tool that enables you to take data from one source, translate it, transform it, repackage it for some downstream import process, and then finally constitutional. Unite is the integration.

Engine that powers the entire platform.

OK purchasing constituent again, it's the licensing is simple. That's by design. All the three components I just described are included and customers license us as the constitutional integration suite. We have flexibility in our licensing. Customers could license us just for a specific solution like the one we're going to be talking about today, but as many customers have recognized, constitutio can be utilized as their integration platform for across their entire enterprise. So we have a very affordable.

An easy upgrade path to the to our enterprise license and customers deploy us for at every end of that spectrum so we have come. We we have served institutions that come to us and say just please take the slate SSIS integration off my plate and then we have customers at the other end of the spectrum that basically have run with the platform and use it as their centralized integration solution and manage 2025 different integrations across their particular enterprise.

OK, quick rundown of features and benefits for operational staff.

If non programmatic data preparation that's constituent map which I described a couple of moments ago, flexible and accurate duplicate detection, the product comes delivered with a very robust set of matching routines that answer the question. How do I avoid the creation of duplicate records, customized exceptions and remediation form that's constituent gather which Michael is going to show you in the demo today?

Dashboards that can be created at the micro and the macro level that enable you to monitor how data is flowing between sources. A very robust scheduling tool that's that basically everything going to be seen today can happen behind the scenes at the schedule of your choosing. Then finally, we're going to asynchronously load records so those records coming from slate into your SSIS that meet all of your business requirements, they're simply going to go ahead and update an existing record in your SSIS or create a new one. We're only going to hold back that small number of records.

That needs some level of human intervention.

Quickly, quickly on it in the cloud we were on Amazon Web Services. We provide all the security and scalability that they do provide and being in the cloud minimizes the IT support that's necessary. And we support bidirectional and real time integration. When the systems were working with supply, that and again, many of our the vast, vast, overwhelming majority of our slate, SSIS customers do, they are. But the integration is bidirectional, so they're not only sending slate to the slate data to their SI.

But they're also enriching the recruitment record with SIS data.

OK quickly on Technical Support again, unlimited Technical Support is included with all of our licenses 24/7 via a number of channels, phone, email, portal and again our support team really is more more than just a break fix crew if you will. Every issue that's brought to our attention, we're going to bring our experience of doing 7080 plus Slate SSIS integrations to the table, and we're going to talk about best practices and what other customers are up to.

I am going to turn it over now to our special guest Yvonne talk a little bit about her experience.

Thank you so much Joe again, my name is Nan Brianna. As I am the director of Admissions Technology and operations at the Kansas City Art Institute.

I started at KCAI in 2013 as we emissions technical assistant. I was hired to not only train under and replace our director when he retired, but also to streamline our processes and bring us into the digital age.

We made some good strides my first few years, but we really accelerated our progress in this initiative. When we migrated to Slate in 2018 and then again in 2019 when we partnered with Constitutio so I'll touch on that more in a moment, but first let me tell you a little bit about KCAI for a little context. KC AI is the oldest arts institution in Kansas City and we are a leader in arts education. Our mission is to prepare gifted students to transform the world.

Immediately through art and design.

We offer we are located near the Plaza and in Kansas City, MO and we are in between two world renowned museums. The Nelson Atkins Museum of Art, to our east and the Kemper Museum of Contemporary Art to our West. Our President, Tony Jones, likes to say that we are the factory in between two showrooms. We offer a 13 majors and four minors. We have a rolling admissions process for both spring and fall terms. We process between 11.

To 1400 applications a year, we also offer two summer residency programs, one for our educators and another for high school students, and that generates about another 250 to 300 applications per year. Our slate instance is managed by my office and which consists of our initials, technology specialist and myself, and then we also have a semi slate captain on the admissions team who helps us with forms and communication.

So as I mentioned, we migrated to.

Sleep in 2018 and one of our goals was to eliminate the manual data entry into our systems bar.

We started exploring our options for that and of course we started with JENZABAR, but they proved to be cost prohibitive and scheduling was just too difficult. We considered hiring an independent contractor to build out the bridge, but we saw the value in the need for having ongoing support, so we started looking at Slate partners and it's important to note that we had just upgraded from jenzabar ex to jenzabar one and this proved to be a considerable.

Back in our search for a data integration solution.

Because at the time none of the slate partners had experience with J1 and they basically no quoted us. But then we met Joe and Michael from Constitutio, and while they didn't have experience with J1 either, they didn't shy away from the new challenge and we value that pioneering spirit and so we partnered with them and it's been one of the best decisions my office has made.

We started implementation and it did go very smoothly and relatively quickly. Our constituent service person went above and beyond. So first example I didn't have any experience setting up on SFTP data transfer and let alone setting it up in slate. And so while Slate wasn't our service person's software, he still jumped on board and got into Slate and helped me set that up. Another example was help with data.

Transformation, and while I was mostly comfortable building the extract query, there were a few transformations that I couldn't get quite right using the export values values, export formulas, I just couldn't figure it out and that's when our service person used the map tool, which Michael will demonstrate shortly. But all those transformations are service person did on our behalf in that map tool and it now runs like a well oiled machine.

So Joe touched on this a little bit earlier. One major concern that we all have with automating our data transfer our duplicates and again constitutio has a solution. Our data is evaluated with multiple data points and if there is a suspect match, it's brought to our attention and I can look at it before it's added to Jens Bar to see if it needs to upgrade a current record or be added as a new record.

It works marvelously so.

Excuse me one moment.

After R slide.

So after our BFA implementation was running smoothly, we started exploring what other options we had for automating our data transfer, and we spoke with our business office and discovered that they were manually entering subsidiary codes for all of our applicants. So we added that to our Constitution workflow and that was taken off their plate. We also this year brought our summer programs into our workflow and so now all that data is added to Jensen.

Start with us without us having to do that manually.

Future projects that we have on the radar is the bidirectional transfer of our financial aid information as well as on campus housing. Application information. We value our partnership with Constitutio. They have streamlined and created significant efficiencies and we look forward to continuing working with them and new and exciting ways. So with that, I'll pass it over to Michael for a demo.

All right, Yvonne, thank you so much, Joe. Thank you. Hello everybody, thanks for joining.

So constituent integration suite I'm going to show you a brief demo here. Constituent Integration Suite is a large full featured integration platform hosted on the cloud. All of that sort of stuff. It does a lot of things, has a lot of capabilities, but what I like to do is make a smaller, more focused.

Demonstration for your particular area of business, so just a small thing, just a small snippet of what constituent does and then if needed. We can get into some of the more advanced features, but to start with the question I like to answer is what am I going to do all day or what am I going to do with this product on a day to day basis? Hopefully not all day, but on a day to day and so to that end.

What I'm starting this off with is just a sample admissions operations dashboard. So I'm wearing the hat right now. If an admissions operations person and it's my job for the purpose of this demo to monitor my integrations, make sure that records are flowing through OK from slate to my SIS and back the other way.

Et cetera, and also to manage any records that require some remediation. So with this dashboard here, you know these things are totally customizable per user. I've got these little widgets that I can move around. I can kick off a workflow sort of ad hoc if I need to, though of course, as Joe mentioned, most of these are scheduled or triggered in some way. I can of course add additional dashboards, switch around between them. What I'd like to do as an admissions operations person is basically.

Use these dashboards as sort of my To Do List. What is my task for this portion of my day here and so you can see these sort of statistical items sort of interesting to sort of monitor the integrations. There's not much I have to do because most of this is happening automatically. Running into the SIS running from the SIS to Slate, and I'm just making sure nothing goes terribly wrong, which it generally doesn't. However, the one thing I do need to do a sort of.

Recurring duty.

Especially with an admissions, loud admissions applicants prospects you know, alumnus. You know what have you loading from slate to my SIS.

Is I need to monitor any sort of remediation items that come up and so you can see my batch of my list of recent batches here. These are records, most of them over the last few days have gone straight through to complete state. I don't need to worry about those. Those records have populated my SIS. We're all set. We're good to go. There are applicants or students or whatever in the SIS. I don't really need to worry about them this batch here though is incomplete and so my job now that I'm going to take you through.

Is to get this incomplete batch into a complete state, so I'll go ahead and dive into here.

And I'll go ahead and collapse this now to give myself a bit more real estate.

Now the idea here is that this is fairly consistent across our solutions, as customizable as we are, we like to keep these consistent, so the idea is our services team, after deploying building this, we're going to show the folks who are going to be in this regularly. How to use this product. The idea here is that you're in. You're out. You've done your remediation work and you don't have that much more to do. I'm going to spend a little bit more time talking about it than a typical.

Operations person would we would expect spend working on it just to give you guys an overview so to start with I've got this grid of records. They're all in awaiting status. They've got their messages about why they're waiting.

I can see some other data here. This is pretend to data. By the way, I saw nothing is real here at all, but I've got this data here. I've got a filter set by default to waiting. This is to showcase that I'm only worried about these waiting records again as a day-to-day operations person, I can remove this filter I'd like.

And I'm just running this on a small admissions operations admissions operation from my desk here, but I've got just a pristine database here, so I've got a bunch of new student records being added, but in the real world you'd see a combination of applicants being updated, added, et cetera, and a very small amount of folks on a waiting status.

Just to show you briefly my other filtering options we've got, I can look across all batches that have run through. I can sort by various items, filter by record number, partition thing out by inboxes, or other fields like this. I can add a few more fields here. Again, this is just a small operation that I'm working on here, but various filters here to search for this I can of course export all of my stuff if I need to report on it later, etc. But for now, for the day to day.

The operational stuff my concern is about these waiting records.

So I'm speaking to an audience who probably completely understands this whole search match process. So I'm going to go through it briefly here. The idea is, and with any integration you have, you're pulling in potentially new applicants, students, person data.

And so the first question we have to ask is of your SIS is does this person exist in your SIS and the answers that we get from your SIS are one of three. It's yes, no or maybe. So yes, they exist. They definitely exist. We found them. Let's go ahead and update their record in the SIS as needed based on changing data and based on what your individual rules want us to update, the second answer is no, they don't exist. So go ahead and make a new record.

And in this case you know your mileage may vary on SIS, but in general we're making the person record or signing them an ID in your system a Sprite, an ID or a Gen support ID or ID number whatever, or making the student record potentially the application record that that backwards. But you know, education history, enrollment history, test scores, decisions, attributes, all the stuff, all the usual suspects were adding that new record there, so that's easy enough and you don't really need to touch those.

From a data perspective, they're not in a queue. They're not waiting, they're just in your system. They're done. They're ready to be matriculated or actioned upon enrolling courses and all that.

The third answer. So we had yes, no. Or maybe yes, they exist. No, they don't exist, and then the third answer is maybe maybe they exist. We think they exist. We found some potential candidates were not 100% certain and so we want to user someone who understands the data to take a look. And that's where we are now. I've got these three waiting records.

This top one here I can see I've found three potential matches. Let's go ahead and look at that and see what these matches are.

OK.

And so let's go ahead and full screen. This what we're what we're looking at here is a matro mediation form. An example of a match remediation form that our services team might deliver for you. So this entire form. Everything here that is in between this border was built and modified in constitutional gather. So this is a form builder tool. This is a tool that our services folks use, and in certain cases schools are interested, they train.

Up their staff, their IT folks for power users or whatever to build and adjust these forms. The point here is that this isn't baked into the product. This is part of our solution that we give you and what that means is that you have the ability to add more remediation forms for other items, adjust the look and feel of these forms, or tell our services, people to, etc. So I'll just give you an overview of this. This is something our services folks built based on our own experience doing this actual match remediation.

In the field, so to start with, I've got this little bird's eye view here of my incoming record from Slate. In this case, and then my potential matches in my SIS.

So looking at these briefly over a handful of matches here, I can tell that this top match here is a slam dunk. I've got a full name match, birthdate match, email match. I can see the first matching world that caught it. Last name, first name, date of birth city.

Easy enough, great. I've got another couple of matches that are less likely. I can see pretty clearly that this is the slam dunk, so I'm gonna go ahead and click that drill down and see a more detailed side by side comparison. So I've got color coding to show which fields match which fields don't match.

With a match like this, frankly this probably would have gone straight through in the real world, but I wanted to pause this so that you would see a very very close match. I can see they don't have an SSN in the banner record they've moved, but this is really what you spend most of your time on when you are in constituent on a day to day level, I believe Yvonne you had some thoughts on this. I just wanted to check with you.

No.

Thank you Michael. Yes, I this is the one one of the areas that we had biggest concern about was the duplicates and what I love about the remediation tool in Constitutio is that it's very similar to slates consolidate records visually with the colors popping out at you and so it's really easy to just get through these quickly every morning. If you have any available or remediation. Thank you, Michael.

Awesome, thank you so much Ivan. So the happy path here. I've clicked this. This is a slam dunk. I just go ahead and click on update record and be done with it and I will do that I promise. But just for fun this is a very close match and by comparison.

This is a not so close match, so very a much smaller number of fields are matching and I can see that really clearly. I can see that very quickly if I didn't see it up in this bird's eye view. I can see it here that this is not a match. This is a great way to discover issues. Perhaps you had duplicate records previously. At some point you find them everywhere. This helps. Also, this is a concocted example of Braden, half a Miller and.

And a half a half a mirror. So I've got this matching role. It might be hard to see, but basically what I'm looking at is.

Partial last name, partial first name, date of birth. So those three data points. I'm checking on that other matches include other combinations of fields, date of birth, city, zip, email, what have you know, various items like that. We might even look at school attendance based on the incoming record and the SIS record. All of that sort of stuff to help you make a quick and accurate decision where this really comes in handy. It comes in handy on the relatively obvious ones.

Here like this guy, but it really comes in handy when folks maybe have entered your system earlier a handful of years ago as a prospect or as an applicant or as an undergraduate student or something like that. And then they come back, they reenter your system. Let's say through Slate, and since the last time they have moved they have changed their contact info. They've changed their name, they've done all sorts of stuff. So what we do with our matching roles is we try.

Very very hard to find that person so that we're not creating a new duplicate record. So that's the idea here with the matching role.

You shouldn't be spending. You know you shouldn't be dealing with more than you know. Maybe 3 to 5% anecdotally, of records matching most of them are just going adding or updating, and then of course we're going to take that slight idea and put it in your SIS and also take your SIS ID and put it back into slate so that you're never going to have to manually match someone more than once. And so I'm going to go ahead and take this happy path here. Go ahead and update this record.

And that's it. I've updated them. I see their ID 37291, so I know that they're in the system again. I can report on that if I need to look at all of my records that have gone through really helpful for UAT or other sorts of reporting, and that's essentially it from a day-to-day perspective. For this solution, the one other thing I'll say on this, I know I want to leave time later for questions, but the one other thing I'll say is that potential matches is the most common.

Remediation item, so that's why I'm showing that it's universal to everybody. But we've seen all sorts of things. Let's say someone has. I don't know, tried to change their SSN or birth date and slate, and it's different from what it is in the SIS. And you want someone to take a look at that and vet that and see what's going on here? What's real? These are legal pieces of information, so you can't just let a student change that name changes all of that sort of stuff. Let's say you've got a school record coming in.

And it's a school that does not exist in your SIS in your validation table of schools. Some people say, yeah, just put something. Put a default in there. That's totally fine. Some people say pause it. Let us look at it. That's another thing it could pull up a form and say, oh, this is the school. Let's match it to here. Let's create a new school record what have you. The important thing here is that our services team builds this for you, starting with some common features. But we work with you on adapting to your.

Workflow and your processes.

So if I pull back a bit, I can see that I am in constituent units and I'm in a workflow, so this workflow is really the engine of our integration and behind the scenes of our workflow we manage displaying forms for people for their remediation. It's a full featured tool, has some scripting, I won't get into that today, can do a lot of stuff, touch a lot of databases, APIs, all of that good stuff.

And.

That's not terribly unique from any other integration solution that you might look at other vendors homegrown integrations, all of that sort of stuff. All of them have a component of the high tech the pushing data into databases, making API calls, all of that sort of stuff, and we deliver this to you as part of a service, and we have experience with all of this stuff.

Also, in every integration solution, in addition to the high tech stuff, there's going to be an element of data preparation, data cleanup, validation, transforming all of that good stuff oftentimes.

Yeah.

That that stuff is going to be buried in the script somewhere buried in some high tech stuff that only one or a couple of people can look at. Only services folks can look at only your one it person on a basement. Speaking from experience, can look at so constituent aims to change that all of that data prep stuff. All of the data transformation, validation, all of that stuff. Clean up that belongs to you in admissions.

And alumni, wherever you're working that belongs to the business more than it. And So what we introduced for that is constitutional map. So I'm going to move away from unite, go into map and map is not a day to day thing like what I just showed you. Map is a periodic thing. It's something our Services team delivers as part of a deployment. It's something that we can train folks on. It's a data transformation tool that is built for, not necessarily it people, folks.

You know the data, but aren't necessarily scripters, or IT technicians or what have you. So in the small amount of time we have, I just want to show you a couple of things in map. It's almost going to be like a mini training because I want you all who are watching this to get an idea of who at your institution might find use out of this might enjoy this. This is going to be an admissions context, but it can be used as sort of all over the place.

So to start with here, I've got a map that I'm going to look at this applications source to map kind of a mouthful there. I've got this map here. I've got an input data source and I've got an output data source, So what a map does is it turns one data source into another. Now what is the data source? Let's go ahead and take a look at that. So a data source is basically this. Let me go ahead and edit this input data source that we have.

Think Excel file thinks CSV file. Think other delimited file fixed with the results of a query into a database. The results of a web service call any sort of table of data. And here's a table of data right here that I'm going to show you and I want to assure you that this is pretend data. So Rosario Hamad Pamela. These are fictional people. Those birth dates. Those lessons are not real, I promise. So we've got this data here. We've got a little bit of definition about what this data source is.

It's coming in as a common delimited. It's got some headers. Here's a sample file that I uploaded earlier to just auto fill all of these columns. And here's some sample data that's going to come in handy later. This file preview here. That's it. That's what a data source is. Just a table of data. So my goal here is to turn this data source into this data source.

And this data source is similar. It's a different kind of file, different tab delimited. I've got a different set of columns and So what I'm my goal is I'm going to transform basically what is that Ross Slate query into a sort of cleaner set of data.

To make the load into my SIS a little more straightforward, make it a little less complex. OK, so I'm going to go ahead and open up this map here.

Edit this map and again.

Be mindful of time, but I just want to show you a few things here. I've got an input data source that's that data source with the sample file that I showed you. I've got my output data source and I'm going to map them together.

So and what I'd like to do is sort of slowly increase the spicy level on these transformations. So get really, really dull early planned, really uninteresting transformations and get a little more interesting as we go along. I'm going to show you three, at least, so to start with, let's take this middle name and my job here is to turn that middle name into a middle initial, not a common use case, especially not anymore, but it's an easy one, and that's why I'm choosing.

So I'm converting my middle name to middle initial. I've got my field, my input data source field mapped to my output. I'm going to add a transformation.

And I'm going to choose from my handful of transformations. Functional, numeric, text base, and I know in this case I want to go ahead and just take the left one character of my middle name.

And there I go. Marty turns to M easy enough. I've got my sample data here, so all of my pretend middle names I can scroll through packs and turns to peak. Catlin turns to Kay, I can get a little bird's eye view of all of these transformations. Perfect, easy enough, and I can even type in just a made up middle name here Jones or something.

As expected, Jones turns to Jay, although I see that this J is lower case, so let's go ahead and add on a new transformation. I've already turned Jones into J, so let's turn lowercase J into uppercase J.

No.

And there we go. So that's a simple middle name transformation. Not too exciting, but hopefully you got you're getting starting to get a glimpse of what is possible here with this plus button you can string together as many transformations as you wish to do quite a number of a lot of stuff going to show you this one here. This is totally possible and slate totally possible in here. I'm going to talk about a bit more about the sort of power of a slate query and a constituent.

App combined, so let's go ahead and add a transformation here. I've got a date thing. Let's just say I want to reformat this date into something else. I've got month day year. Let's just turn it into. I don't know year, month, day. Oops, that's going to be my new format and my old format is month, day, year.

And I've got capital M Lowercase D's. I don't necessarily know what's what, but thankfully I've got this nice little help guide inside the application that tells me all the stuff I can do day stuff, month stuff.

Day and week hour stuff. Time zone, AM PM. All of that. Easy enough click OK click run.

And my data is transformed perfect all right one more that I want to show you those were both one to one transformations. What I'd like to do next is show you a 2 to one transformation just so you get an idea that you can do many to 11 to many all of that good stuff. So let's go ahead and add our US based ZIP codes. I happen to know that in my incoming data my slight query in this case I've got a zip and I've got a zip plus 4.

So let's take these two fields and combine them together. There's a good sample, so I first want to clean this up.

Let's go ahead and do a format number.

On this.

I've got a little bit of help there as well for various formatting masks, click OK. Click run my 8840 turns into 08840. Easy enough, I'm going to go ahead and do that for my second zip code. The ZIP plus 4 here.

Change its inputs a + 4 click OK, click run OK. I've got 603 turns into 0603 and now it's fine. Time to just concatenate these two things together. Let's go ahead and do a concatenate. Hit our gearbox.

Choose a IE a dash sorry delimeter. Click OK.

Click run and there I go. I've got this perfectly formatted US zip plus five. Let's just finish that off by saying, well, I've got to do that again already in this map and I might need to do this.

Over and over again, and other maps, maybe we go beyond admissions and we've got other things of data where I'm I'm mapping this thing, so let's go ahead and save ourselves some time in the future. We'll save our colleagues some time. Save this and call this combine us zips or something.

Click OK.

And justice to demonstrate that I'm going to undo all of my hard work.

Start from scratch here.

And I'm going to instead of doing all that stuff I did earlier, I'm going to go ahead and do a custom transformation and choose my combine us sips. I could have done that a couple times. Well, I've got my zip, my zip plus 4I click OK, I click review and just like that I've got my zip combination and we have several of these. We've got interesting cases for, let's say banner. Some folks here are banner schools and you may know that you have to store your phone numbers as area codes.

And then the rest of the number and then international access code and all of that sort of stuff.

And various other things like that that we've just over the years, developed these custom transformations for our experienced with that. Again, this is part of our services deployment, but we can also train folks on how to modify these and build new ones as needed, and then to evonne's point earlier I wanted to speak, she mentioned and I agree in services here. We love slate. We love the options that folks get in the slate query.

We always push the export values. Export values are glorious.

A wonderful invention here from Slate where you got your programs exporting as program codes, your races, ethnicities, countries, all of that good stuff coming out for Slate is perfect, so we push that and so there's a lot you can do in a slight query to produce clean integration ready data. And we don't shy away from that. But the rule of thumb that we give is something's a real easy to do in sleep and some things take a little bit more.

Maybe some custom sequel, maybe a new field, maybe something like that. Chances are constituent amount might be able to take it to that last mile and clean up that data a little further, like the dealing with phone numbers and the potential chaos of oddly formatted phone numbers. We've got that covered various other things. We're combining multiple fields, doing a lot of logic, so constitutional map, plus the very powerful slate queries are perfect.

Yes.

Combination seen in just about all of our deployments and then that leads to constitute, unite and gather which pushes that data into your SIS and allows you to manage that. And then. Of course, we're also sending data back for Slate source format to pick up as needed right away, scheduled whatever works for you all.

And so I think I have a few more minutes, but I'll go ahead and stop the show now and.

Let our moderators take over.

Great.

Next we will go into our Q&A and I have been taking down all of the questions so I will start out the questions and then Joe, I will let you piggyback off that.

Great.

With the answers. So the very first question that came in was from Speta and that was for Joe. What is the highest volume of data records you are moving through constituent constituent at the moment?

The highest value.

Michael, what would you say our highest volume shop is between Slate and the SIS?

Highest volume and this is anecdotal. It's just me looking around, but probably around 100 or so thousand daily.

That's about the highest.

But again, the platform, the constituent platform really.

The limits are set extremely high for the for the data that you can flow through the platform and no customer, even our largest customer, has ever come close to our thresholds. So as mentioned in my slide, we processed 330 million records last year across our across 100 customers, so we expect that number to grow and we have the scale and a WS can scale with you so.

I should also say the couple 100,000 is for one integration that I'm thinking of so that customer might be compounding on that with additional integrations so.

Possibly millions anyway.

Great, so the next question came from Yvonne Thomas. We use colleague here at Carlow University. How do you handle things that require multiple screens such as transcripts with degrees or temporary addresses?

So we are populating that from the back end and colleague case. It's we're populating the unit data, that sort of thing, so it's not the idea here is that we're populating this data such that you can see it on the UI and the screens, like a colleague for example, but we're processing it all from the back end. There's no, our solutions aren't interacting with your UI. I hope that I hope I understood that right, but.

OK, next question came from Denise Wilson. Can you integrate Slate and PeopleSoft as well as slate knowledge?

Sure, yes.

Absolutely.

Knowledge is a familiar name to me actually, but yes, yes.

OK, Wonderful Matthew was next. Will SSN always be redacted or are there security procedures to show hide based on the user?

We can yes, yes. Ultimately yes. My demo here has it redacted, but we can. We can get creative with who gets to see it and who doesn't get to see it for sure, and that's a common use case. Yes.

Perfect Mark Perrillo is next. Can you match process? Also evaluate other multiple email addresses from the student. For example, compare work email, personal email and other email addresses.

Absolutely yes.

Great and our absolute last question that came in was what happens when a data field is blank instead of containing a value, will those records be set in waiting status? Or if the data comes in formatted incorrectly with the value that is not anticipated in the mapping?

That depends. It depends on the data. If it's blank, it's possible that you want to pause the record and have someone look at it because you expect something. For example, if I get someone coming in and I'd expect at least one.

Of address, I might pause the record and say, hey, this person doesn't have an address. Let's double check this kind of a smoke test. Sometimes blank records come in and that's a clear signal. OK, blank this out in the SSIS. If it's in there, sometimes they come in and we don't want to overwrite the SIS. So this is a field by field setting that we want to do. So the ultimate answer is depends on the field, whatever. Whatever you need us to do, we'll do.

Great, that wraps up our questions. I'm actually going to move over into the next slide for Joe.

And it's like you're showing Nita is the.

Implementation overview

Yeah, so Michael if you could maybe take take the group through that. What a typical implementation looks like and then we can kind of wrap things up if that works for you.

Hey, that's excellent. So with the implementation overview, let's talk through that. Here we start every implementation with a kickoff call and email and with the call and the email both we go over everything required to start the project. That is some technical access for us, all of which we describe and explain and work with your folks on that and then mapping requirements so business mapping.

I know Yvonne has direct experience with that. Yvonne did a tremendous job with that mapping as well. We provide folks with examples, advice, all of that sort of stuff, so we've got technical requirements.

Business mapping requirements, that sort of thing.

Once that is already in, the project is scheduled. Typically now this depends on the integration, but it typical standard slate to SIS integration that first flagship bit or you want to create applications and student records and all that is 5 days from starting the project to getting you something that you can test. So you're testing by the end of that first week or very beginning of the next week. Once we've done that, we.

Have another call with. You give you some documentation we handed off. We say here's how you use constituent. It's useful to know how to use it, not just for testing, but eventually when you go into production.

You do some testing. We do a little cycle here of UAT and remediation and we go back and forth. Maybe you missed your requirement. Maybe we misunderstood the requirement. Maybe we had a typo somewhere. All of that sort of stuff as part of the project get you to the point where you are comfortable going into production. Once you're ready for that, we will meet with you to do a go live cutover. We'll get you into production. We'll help you with all the scheduling stuff, making the dashboards if we hadn't already done that. Just get you to the point where you're operational.

And automated, so that's my perspective, Evan. I don't want to put you on the spot, but you may say something you'd like.

That no, that that's you explained it very well. It took us from I believe contract to go live right at a month. It was relatively quick.

Yes and now. But like I mentioned earlier, above and beyond because when I had questions about Slate.

And I like to say, even though technology is in my title, I'm not as technically savvy as Michael for sure. And so Institute was able to help me work through different areas that I just had trouble getting through myself. So yeah, a month for us and then future future projects that we were on, it went faster than that with adding like the applicant data for our summer programs and the subsidiary codes. So you guys are very attentive to our needs.

Would appreciate that.

Thank you.

Maybe need if you could put up by my contact information for the for the slide that your next slide.

OK, go on. So that's I think that's the that's all we've got, Nita. There's my contact information to everybody, so please feel free to jot that down if you will. But again, pleasure being with you today and really hope to see many of you if not all of you in a few weeks in Nashville. So thank you all. Thank you Nita. Very much from tech illusions.

Thank you, thank you guys as well.

Thanks I'll.

OK yeah bye bye everybody.

Right?

Bye bye have a good one.