all right welcome today today's webcast we've got cern solutions and perspective this is the the first of a couple and and uh you know we've got uh michael christiansen here from from perspectium joining us i'm josh cesaro i'm uh the practice manager for securing risk at cerner solutions got lots of experience in the platform uh just a quick sound bit i guess again about certain solutions uh you know we're one of servicenow's elite partners we're one of the few partners that's a you know a certified application developer partner so we make a lot of store apps do a lot there and we provide services across the entire platform michael do you want to go ahead and introduce yourself thanks josh uh mike christiansen with prospectium i'm a solution consultant there and just by way of introduction to this perspective if you don't know us uh we are a process integration solution for servicenow our founder david liu was one of the founding developers of servicenow and that naturally gave him uh you know complete understanding into the intricacies of servicenow and the need for a solution like ours to really complement and extend service now in making it easy to get data out of servicenow and then extend processes to other systems so in a nutshell that's who we are and uh we're glad you joined us today awesome glad to have you here so uh as i mentioned the very beginning you know this is part of a series it's right now a three-part series that might grow you know depending on on how these conversations go but uh the series is solving servicenow data challenges we're in the the first episode today which is achieving data transparency or servicenow data transparency and um you know our next two episodes are going to be securing servicenow data against the unexpected and extending service now workflows to partners uh we've got kind of a couple slides to go through have a nice conversation about kind of you know what some of these things mean and and you know what are some things customers are doing if you have any questions as we go through feel free to stick those in the q a and we'll we'll either answer them kind of naturally as part of the conversation or we'll circle back as part of a q a at the end so uh thanks for joining and uh we'll get started here with the first one so um you know we talk about data transparency you know what does that mean um you know organizations have lots of data sources right that have important or critical enterprise data they've got stuff coming from their erp they've got environmental or operational data about their infrastructure or other things they have work management data or workflow management data which is often going to be you know at least for us in servicenow and then they've got employee and data and customer and vendor data and there's lots of things that describe operational or company health that are that span multiple data sources right so organizations have a need to be able to get those things those that data in one place in a near real-time fashion in order to create um you know reports and dashboards and that aggregate things and give them views to make decisions quickly michael i don't i don't know if you want to add some color to that around you know what you've seen or what this means to you yeah i think you know with with a lot of the customers and the people that we deal with uh and we work with on a regular basis we find that within the tools like servicenow there are there's great functionality that helps them get a glimpse into their data right and it gets the report out into the hands of all of the end users and and what we find is that there's kind of another level of analytics where there's a little bit of help needed and that's where perspective steps in and and this next level really is where we're starting to look at combining data with other sources maybe it's servicenow data with avaya data right call data for a call system uh or a call center or maybe it's combining with an hr system or or maybe a cmdb that's stored in another place so so that's that's kind of the next level that we find that most people want to go to they want to get beyond just showing a list of incidents that came up today and they want to go to more of a machine learning approach or more ai approach to their their data and go big data with it so we find that to be the case in a lot of situations there's additional functionality that we see a lot of people come to us with that they want to just do like hierarchy reporting or other things that are a little bit more difficult in inside of an application like servicenow so um that that's some of the things that we see a lot of a lot of the problems that people face where there's a need to enhance the functionality of what they have in their their tools yeah i actually had a customer i think uh i think it was the beginning of last year that you know they they they were uh implementing servicenow they were using quite a bit of the platform and as part of that they you know as an organization they had tableau as a reporting standard for all their kind of business analytics and they were they were trying to get all the servicenow data into to blow for some of the things where you know servicenow data was just a small component of what what they're trying to report on and they they found that to be challenging right i mean there's all the referential and schema complexity in servicenow right you got referential data how do i how do i export data to like a tableau database and make it reportable when i've got sis ids referencing things and and that that ended up being uh you know a pretty big effort and a serious time commitment and and you know we had to decide what things uh were critical data to happen to blow right because it it became very hard to to dump everything and um you know this is something that we're seeing more of as as you get all these uh as as businesses like you said kind of take more of an analytics or or data focused approach to make decisions there's there's more and more need to be able to find a an easy way to to make that data part of your your reporting roll up yeah exactly and and what we see you know a lot of as well is in addition to the aggregating and uh you know getting the data down to tableau is just the need to scale and you know if you're creating a hundred incidents a day uh in servicenow and that's all you're doing a lot of people will approach that with a you know an api connector a homegrown api connector yep right probably not a big deal not gonna be in the impact on servicenow and or on your development team things like that not a lot of complexity there but where we see a need for a solution like prospectium is when we start to scale and we're talking really large numbers of data and we have some customers that are are moving you know upwards of 10 million records a day and and on a busy day even higher than that and so that's the other complexity we face is the idea of scaling our our data movement from servicenow yeah let's let's actually take a look at a couple of those those kind of customer specific scenarios so you know servicenow is just as we saw the previous previous view right servicenow is just uh a component of enterprise data typically but it's a component that you know can be hard to incorporate into into a centralized uh data warehouse right so um there's some big names here these are all i i guess you know current current perspective customers um right can you tell us a little bit about uh paypal for example that's that's one that that you know i think has been around forever right yeah paypal's been around a long time and uh this is this is one that's near and dear to my heart i started working with paypal uh from the beginning of our relationship and so i was able to watch them uh transform as they implemented our solution but they were faced with performance challenges when they were trying to extract data out of of servicenow and they had had a homegrown solution that they used and they found um just they have several different problems that came up from using that and you know performance is one you know reliability of data is another one and and most companies face this so this is not something that's specifically unique to paypal yep but they also need to combine data like we talked about earlier with data from other apps and report on the performance of their online payment processing system now during the year it's not as big a deal as it is this time of year we're facing right now we've got holidays coming up everybody's doing our last minute shopping and an outage is is extremely detrimental and so by pulling the data out combining it with the other systems they're able to get a clear picture you know what's going on they were able to find out because we're pulling data out in a real-time basis they're able to find out hey we've got a problem that started and we can tell it started because we have these three tickets that are related to it already and they're able to address it but not only that once you get the data out you know paypal is able to do more machine learning where we're starting to get into the predictive behavior and identify uh we are in a scenario that it looks like we might have a problem let's get some resolution in place before that happens and then there's zero impact to our you know it's a financial impact right it's a it's an impact to the bottom line so then they can say zero impact to bottom line right so that's so that's really interesting i heard a couple things that they can be a struggle with with some of these you know if you were to take the homegrown approach like you described right so one of those was the the large transaction volumes in a way that is not impactful to servicenow performance right you know the users aren't going to perceive an impact there i also heard that that it's a real-time connection so if you're using something for like dashboarding or monitoring uh like paypal is you know they have they have near real-time data that allows them to kind of see impact quickly and then the other thing you mentioned was effectively um lossless a lossless data feed right we're confident that things don't get uh dropped or or um you know are failed to be delivered without some type of notice or intervention yeah exactly and there's there's several components that go into that guarantee of data from different levels of monitoring at the customer side and at the perspective side and then some receipts capability where a message is actually sent back to verify whether the data has made it or not and then from there you can either resend the message or do you know troubleshooting and try to figure out exactly what's going on so so there's from the data guarantee side that's that's kind of the level that we we look at from the monitoring and and the receipts and then you know again from the scaling perspective the way we're approaching it is technologically it's quite different from what a typical integration the homegrown integration style might be where a homegrown approach you would make a call into servicenow and so the more data you have the more calls you're making and that's where we start to see the performance impact but instead we're pushing data out then the minutes it's adjusted on a or the minute a record is adjusted we're pushing that record out to the database and so it's a different approach to getting the data out that allows us to uh preserve the the functionality performance of the servicenow instance that's very cool you you mentioned um well i mean it has to be working right because it looks like servicenow's a customer do you want to tell us a little bit about that that's that's pretty interesting to me to see them on there yeah yeah and they're they're probably one of our biggest customers um if you're familiar with the high system they they use us to keep their high system up historically if you've used it for a long time you may remember they had outages for a period of time when they did an upgrade and those outages were pretty costly from a customer service perspective it was costly and and so with perspective coming in saving out the data into a queue and preserving that data they're able to do upgrades without in any downtime and that was a significant impact on their business and then they also use uh perspective to pull data out uh on a sales data out and then they're able to do you know analytics on that and put dashboards in front of their executive leadership that show exactly what's going on in a real-time basis so they know uh you know at any given time what's what's happening in their their sales department and it's in a clear concise uh display for their executives so they've they've been a customer for a little while and uh and and there's this bit it's a big installation just because the sheer number of or the quantity of data that they're pushing out we're looking at probably 10 million to 100 million per per day records per day which is quite significant yeah those are huge numbers i think when we've when we've seen stuff like this in the past right you're looking at trying to get servicenow data somewhere else you know hundreds of millions of records a day is is is almost always you know impactful to performance so it's interesting that that you know you guys have a solution that allows people to still get the the servicenow experience they expect but we we can you know replicate that data somewhere else um you know there's there's a huge variety of of looks like target databases here you know i think some of it's even in the cloud i see snowflake on here which is really interesting to me because we're all hearing all kinds of things about snowflake do you want to kind of talk about that real quick yeah that's one of the you know the big trends i think a lot of people are moving to that kind of a data storage system uh you know a cloud-based and we have a customer that's a a global sports apparel company and they use us to move data from servicenow into a snowflake database and when they approached us it was a couple of reasons again it was similar to what a lot of other people had they have there's complexity in the integration and there's the scaling issue but they also just had a mandate inside their company that all data in the different applications and tools had to be backed up and consolidated for their machine learning and ai initiatives and so that was one of the driving [Music] reasons for them coming to us and talking about this type of an integration so they have a very large amount of data as well i don't have the exact numbers but they're very significant you know i actually came from a customer site prior to working for prospectium i worked for intermountain healthcare out in salt lake city utah and it you know it's a hospital network at the time it was about 31 hospitals and over 100 clinics they just joined with another hospital network in the midwest that'll double that i believe but but we were faced with very similar challenges we needed to bring data out we needed to look at it in in depth but we didn't have the scale that we're talking about with these other companies yeah and and so we were looking at about six to 10 million records a month so it wasn't it wasn't a huge deal but it was big enough deal that it was not something that we could safely and and efficiently do ourselves so we use perspective to pull data out in many different scenarios and for different use cases but um but that was kind of the size of of our implementation there so there's quite a range that it that it fits the perspective fits the bill for yeah that's very interesting i mean one of the things you know i mentioned that we've had some experience with this with customers right you know it's a growing need and one of the things we've run into is is even if you even if you build up you know the custom integration and and you've you've got your data flowing there's kind of a a big overhead i guess around um you know maintaining kind of all the schema changes right we we we know that as as servicenow developers we're constantly adjusting things in service now to kind of you know meet the need of the customer and and then you've got to go figure out what are all the downstream data sources and i got to go update those and it becomes this big process and i've seen customers dedicate like multiple full-time resources to maintaining some of these feeds i'm just curious kind of what your experience has been with perspective in that area yeah that's a good question and what we find is that we don't need to add any additional resources for this most companies they've got a servicenow admin and maybe maybe a handful or more servicenow developers and this uh the the integration that perspective provides uh it really is comprised of three parts you've got a native application that installs inside of servicenow and that's what packages up the data pushes it out it looks for changes yeah it's where you would set any filtering criteria where you'd say i only want to send data to our local database when it's assigned to uh group a b and c yeah you would set up all that logic there the second component would be the perspective integration mess or it's basically a message bus and that's the queuing mechanism so the data would be pushed there and that's that's in the cloud either a google cloud or a a an aws and and then from there on the customer side in their data center they would have an agent that would reach up and pull the data down and then make the insert into the the appropriate database and tables and so so when we implement you've we've got to to gather a few different people we're going to gather you know your network guys your your server guys to set that up and then your your servicenow admins and and from there typically it's just the servicenow admin that manages it from there going forward so you have another team let's say another team realizes they can get at the servicenow data and they say yeah that's great i need access to it you play into the database their tableau developers write their reports against it and if the data is not there that they need they contact the admin say hey i need you to send out the cmdb data so we can start writing reports off of that and then within a couple of minutes he can he or she could set up that share and begin sending data out for the cmdb uh tables in servicenow so it's a pretty quick and efficient way of of sending stuff out and and really puts the control in the hands of the servicenow team yeah that's always nice right because then you you can see you can see the downstream dependencies of all of the things in servicenow right from servicenow because you're configuring the the data streams from servicenow and that kind of puts the power back in the hands of the servicenow administrator which is cool um exactly i guess just a reminder to folks uh who joined us you know if you have any questions there's a there's a q a um well we've got michael we want to kind of pick his brain and make sure that we we get all our questions answered so feel free to feel free to post anything there and we'll make sure to address it um well this is very cool it you know it from uh from a database a target database perspective you know do you guys have limitations around uh where we send the data or is it pretty much hey if you've got a a mainstream database solution we can accommodate it you know really all the mainstream database solutions out there we accommodate um several years ago we typically would send data out to oracle sql server and sap hana and maybe a postgres sql database that has been expanding as demands come in and we're seeing snowflake a lot more like we mentioned earlier a lot of customers wanting to go there maybe an s3 bucket we've got customers asking for that and we have implementations there so that yeah it's expanding and uh it's typically just a configuration that we set up in the agent that tells the data where to go so it doesn't affect uh it doesn't really affect anything on the servicenow side unless there's transformations that need to happen before you send the data out but typically it's just a configuration that needs to be set up on the the agent side that tells it where to go and any special connection or credential information for that data store type very cool and then then it keeps everything up to date for you from a schema perspective which i think is one of the things people people run into quite a bit yeah and that's a good point you know that's one thing that's been coming in a lot lately we've we've been getting a lot of questions about this concept of being schema aware or schema automation where it picks up any changes that happen in servicenow let's say we add a column um you know perspective automatically picks that up sends it over to the database creates the column and begins to populate it with the new data or if you make a data type change it's automatically picking that up so that makes life easier on your dbas and they don't have to to go and make those changes those are picked up automatically and so really the only involvement from your dbas might be some of the typical maintenance they would do on any database creating indexes or you know that type of work yeah that's pretty cool i mean that's just that's just i guess another way you get that sort of uh real-time data transparency right it's it's one less thing you got to wait on to happen in order to see your data where you need it which is which is pretty cool yeah exactly um time is money and we we try to eliminate eliminate any delays that we can and that's that's one that could crop up very cool so we've we've got perspective in place that has you know helped us achieve achieve our data you know data transparency so if we've got data flowing into kind of a common repository as many of your customers do and then we can feed it into kind of any of our our organizational uh you know bi preferred bi tool right and and make sure that we're getting all the reporting we need that's i think i think the objective everybody wants and perspectives the missing piece yep absolutely very cool well um i think that was i think that's most of the things we plan to cover today if anybody has any questions feel free to post them see we did have one here that's a good one so servicenow has permissions controlled via acl how do we replicate or enforce these rules once we take the data out of servicenow using perspectium okay good good question so here's here's what we did as a customer of perspectium we had data that was coming out of servicenow for multiple teams and some of the teams wanted to control their data and say only we can get at this so in that case the data is locked down at the database level so permissions would need to be created or granted that would control that now if there there might be a scenario where let's say an hr team they have their own database and they want to put all their data there and maybe you have a server team that wants ticket data or or something like that perspective can allow you to create different cues that will send the data to different locations so that way you can isolate it and meet the security needs of the teams that are requesting the data so so that's one approach that or another approach that could be taken in addition to just managing rights and permissions at the database level yep okay so there's there's some you know there you've got to think about that actively as you're you're figuring out how you're where you're sending the data and how you plan to present that through your your reporting tool of choice yeah exactly and and perspective it's an integration as a service we're not throwing a tool kit at you we're we're providing a service for the the length of the contract and and so perspective at the beginning would sit down uh with your implementation team and we would identify what do you need to share where does it need to go does it need to go to multiple locations do we need to fan the data out or do we need to send one piece of data to one place like we mentioned one to another and so that would be part of the service is identifying you know exactly what do we need to do here and how how can we really meet the needs of the widest audience at your company with the servicenow data sounds sounds like it's a it's a pretty white glove approach right you're getting kind of um all the help you need from start to finish yeah absolutely yeah very cool any other questions feel free to put them in the q a and we'll address them here um we are coming to the the end of our our first session we've got two more so um you know please go and and subscribe to uh the additional uh you know parts of the series we've uh you know continuing the conversation kind of around some of the servicenow data challenges um you know pl please do uh subscribe obviously on linkedin or or like on linkedin for for any of the posts and then also for both prospectium and serna let me give you a little sneak peek into what we'll be talking about in our next uh webinar we'll be talking a little bit about the backup and restore capability and and that's commonly being used by people that are upgrading from older instances of servicenow like that are on oracle they want to move to a mariadb we have a major bank that's that we're working with right now to do that or maybe you need to have an archive of your servicenow data and so that's another way that that we're providing those services so we'll explore that a little bit more in depth uh in the next webinar yep very cool well uh thank you for joining us guys hope to hope to see everybody here uh on the next session and um thank you michael for for lending your your expertise you know hopefully everybody has a wonderful rest of the day yep thank you everyone