Name: The Prism Edge: Turbocharge your Enterprise Data Insights
Uploaded: 2025-12-11T18:16:25.996Z
Duration: 41 min 44 s
Description: The Prism Edge: Turbocharge your Enterprise Data Insights

Transcript for "The Prism Edge: Turbocharge your Enterprise Data Insights": Good morning, everybody. Welcome to Workday's webinar. We are gonna get started at two minutes after the hour today. We're gonna give everybody a little more time to join. So we will kick things off shortly. All right. Hello, everyone. Thank you for joining today's webinar. I hope you are gearing up for a fun holiday season to wrap up 2025. Let's get you charged up with Prism today and how it can help drive your enterprise data insights. Just a quick reminder that today's event is part of Workday's looking forward with Workday. This series is designed to give you insights into how your organization can get the most value out of the Workday platform. My name is Callie Sharp. I'm on the Workday office of the CIO Product Marketing team, and I will be your host for today's session. So during this session, we may share a few forward looking statements that are subject to change. So please note these are covered under our product statement agreement. In addition, we have a couple of housekeeping items to go through today. So first, we're recording the session. So the recording will be available to you in the next twenty eight twenty four hours. So, please keep an eye out for the recording. Also, Workday uses the Goldcast platform. So this works best with Chrome. If you are having any technical issues today, please let us know in that q and a function. You can get the most out of our webinar on the tabs on the top right corner of your screen. So there are docs available, which will have valuable resources for you to reference. The q and a is where you could submit questions. Arvin and I will try to get all of your questions answered live today, but if not, we will get back to you promptly with an answer on email. Last but not least, we'll have a four question survey at the end, so please take the survey. We love to hear your feedback. We use your feedback in future, events and content so that we can deliver the most valuable information, to meet your needs. So joining us today, is Arvin Shondrakasan, our senior manager focused on Prism Analytics. So today, Arvin and I are gonna break up our agenda in a couple of different categories. So we're gonna set the stage with common pain points shared by the office of the CIO. Then we'll share Workday's open platform strategy and how it delivers value to the CIO. Arvin's gonna dig into Prism and how it delivers value followed by a demo, and then we'll wrap things up with which is coming next, which is Workday's data cloud. As a quick reminder, don't forget to submit any questions you may have, in the q and a. So let's dig in. So we know that the CIO mandate has shifted. You're under immense pressure to deploy AI and drive innovation. But here is the reality of the situation. Data readiness is the backbone bone of AI value. And right now, many organizations are held back by siloed systems and off platform applications that fragment data context. So you need to bring all your data together to fuel intelligence, but legacy architectures make this incredibly difficult. So today, we're gonna show you how to solve that data readiness challenge. Workday's platform strategy is open and AI ready. This addresses the many challenges faced by CIOs, including data silos, data readiness, ungoverned AI, integration challenges, and disjointed experiences. Our data is grounded in high context and is accessible where you need it in Workday and also beyond. Our builder tools and ecosystem of builders help you meet your business needs as they come up. And interoperability across your enterprise enables you to connect Workday wherever you work. Workday's open platform delivers secure, resilient, and a flexible foundation for all Workday offerings. But these are not just afterthoughts. They're foundational design principles of the entire platform, ensuring trust and operational stability. And Workday's build opens up our platform to developers to harness the power of applications, data, and AI to build the future of work with AI, all backed by the trust and security of Workday. Workday data cloud, which is part of build, governs how data is managed across the enterprise. I will walk through Workday Data Cloud later today. But first, we're gonna dig into Workday Prism capabilities, use cases, and a demo with Arvind. So now I'll hand it over to you, Arvind. Alright. We are having a couple of technical issues with Arvin's video, so I am gonna give him a second to see if we can resolve that. But let's see. I think he should be back on shortly. Can you hear me okay? Yes. I can hear you. I was about to dig into Prism, but I think I think you're ready to go now. Okay. Perfect. Yeah. Thank you. I don't. know what the technical, Arvind. yeah. No worries. Yeah. So let's get started. Again, going back is, let's let's zoom out and look into, the entire suit of products at what they offers as part of our IT, lead to support our IT lead leaders across your HR and finance functions. So starting from the left is Workday core reporting. That's your out of the box reporting toolkit that makes up standard reports, custom reports, dashboards, and the popular drag and drop discovery boards too. This is available for every birthday customer. Second is people analytics, which is your turnkey AI powered natural storyteller format product that helps your people leaders. Third is your Prism Analytics, which is the focus of today's session that lets you bring in bring in external data with Workday data to derive three sixty degree insights. Adaptive planning is your forward looking strategist. Pick on employee voice is your employee sentiment platform, and what they extend is your application developer platform. So let's dig in and look into Prism Analytics today. So what is Prism in a nutshell? Right? It's your workforce data work based data hub that lets you blend in and in any external data source with workday data. And you can derive insights through this. Let's try this to an example. Right? If you have payroll or recruitment data, which is sitting outside of Workday, Prism lets you ingest it, secure it, and then eventually blend it with Workday data, and essentially create datasets and pipelines to answer business critical questions. So what questions are these? So let's look at three different personas in terms of the outcomes that they are trying to drive. First off is for employees. This helps answer questions around the total compensation in their worker profile. For HR team, this is about answering questions around total workforce visibility without reliance on IT. And for finance team, this might mean to make better decisions and data driven decisions and forward looking plans. I'd like to use this analogy of comparing Prism against a Swiss army knife. It has various applications in your enterprise, but there are three common areas. First, it lets you blend in external data with Workday data. Second, it lets you build complex calculations that are needed for your reporting and insights. And third is you can actually run reporting analytics on top of the blended data source with Workday Security Model. So let's switch gears and talk about what are the top reasons why customers choose Prism. It's threefold. First off is strong security. When you're talking about blending data from multiple sources, one of the most common challenges that we have heard is about handling security. It's costly and time consuming, and it's very challenging to maintain different security models. With Prism, you can repurpose your workday security models that you have already built in and apply that on your Blended data source, taking care of that security aspect. Second is the flow of work insights. Once the data is in Prisma Analytics, you can seamlessly embed it directly into the flow of work across your Workday platform. This might mean within business processes, within employee profiles, within your manager dashboards, or even within your Workday extend applications. What does what this does is it enables you to be truly data driven. The last one is the streamlined experience. No enablement, no onboarding needed for the people consuming the data, bringing all relevant insights right in your fingertips in one day. Now when I talk about this with my customers, one of the common things I ask is well, one of the common things that I get asked is, hey. Can you talk to me a little bit more about how Prism works with other data warehouse or PI tools in my enterprise that you currently use. So I wanna flash up this slide here. To the right side of your screen, you see a bunch of tools you might currently have in your analytics ecosystem, ranging from data warehouse tools to the BI tools. So many of our customers have used Prism alongside the data warehouse systems tools like Snowflake, BI tools like Tableau, and Power BI. So nothing to worry in terms of what Prism does in terms of complementing your existing analytics ecosystem. We understand that you do have tools that you're currently using, and you wanna use it beyond the scope of HR and finance. Prism lets you do that with the analytics ecosystem of connectors. Now speaking about connectors, customers, let's talk about what their growth is. Prism has seen stupendous growth over the last six years with the current count reaching over 2,000. This is a massive number, and there's a reason to it. It's because Prism platform can process over a million monthly active users and process over 200,000,000,000,000 data rows. Prism has broad applicability across multiple industries regardless of the industry and myriad of data sources. So what value does all these Prism customers actually get? I wanna highlight a few of the customers and the value that they're part. Now just keep in mind that whenever we talk about value for Prism, it's two folds. First thing, it's might be to do with the time savings, or second, it might be to do with the cost savings. So I'm gonna highlight a few customers in that bucket. We have customers such as Memorial Sloan Kettering Cancer Center in New York who expect to save close to $25,000,000 to $30,000,000 over the next three to five years, Thanks to that actions based, taken based on insights, they were able to pull together using Prism analytics around overtime, missed meals, and vacation liability. Now our friend in The UK, which is Rolls Royce, used Prism to improve forecasting accuracy and reduce budget variances by millions of dollars. Talk about a banking solution, Huntington Bank. They've automated all of their user access reviews and reduced time to complete semiannual reviews from sixty hours to two hours. Oops. Speaking of customers who have successfully used Prism, and are continuing to see the value of Prism, We have customers across every single industry using Prism. It is a mature, robust, and value driven platform that our customers love. For all the prospects out there, we are happy to put you in touch with any customer references, so don't hesitate to reach out to directly to us or to your working account team. So what are these customers actually building with Prism? For that, let's talk about some of the most common Prism use cases. Starting off from the left, total workforce trends. Driving this through an example right now. Assume you acquired a company in the last year, and your acquired company uses a non Workday system to manage all their people. Since you're in Workday, you're tasked to bring all of these employees and their profiles from the non Workday system to your Workday system. By doing this, your entire workforce population will be consolidated in one system through Workday, making it much easier to manage retention and attrition. And how do they do that? It's via Prism. Second, compensation, near and dear to many of our customers. Even at Workday, as an employee, I can see my payroll details and total rewards in my employee profile by bringing in benefits data, stock plan data, all in via Prism. And not just these use cases, but Prism has become increasingly popular across all other workforce areas, like time tracking, involving branching system data, absence management, employee sentiment data, recruitment, and external learning data as well. Now you all have made it to the exciting part of the presentation, which is the demo. I know you all love demos. So what I'm gonna do is I'm gonna flash up a demo where there are gonna be two parts to it. First, I'm gonna be setting up the context for the demo as to what are we trying to build and what are we trying to achieve. And the second is the actual demo on how you can achieve that through, Prism and discovery ports. We have picked a very common compensation use case for this demonstration, so that's what you will be seeing as part of the demo. So let me roll that in. Hello. And welcome to the Prism demo. Today, we will be building a discovery board with three different dimensions of total cost of labor. So let's dive right in into the demo context. The three dimensions that we'll be looking at are stock pay information, benefits, and base pay information. The stock pay information will be coming in from Amazon s three, and Workday already host the benefits and base pay information. We're going to use Prism to ingest the data, prepare and apply some transformation, secure and govern the data with Workday Security Model, and finally publish a Prism data source. Just as a quick note, we will be using the Prism data source in a discovery board. But you can repurpose the exact same data source across extent applications, dashboards, employee profiles, and business processes. So let's dive into the demonstration. As part of the first step to go into the demo, we are going to go to the Prism landing page, which is data catalog. We need to load the stock pay data sitting in from s three to Prism. Within the data catalog, I go into the connections menu and click on the AWS s three bucket connection. It's very easy to set up the connection with an key ID and an access key. Since I've already set up the connection, I'm quickly going to test the connection. Now once the connection has exceeded, then I'll go and create something called as data change task. Once I click on the data change task to load data from Amazon s three, I go through the connection object to choose Amazon s three. And then I need to go into the specific object pattern where I need to look for the stock pay information file. I go and specify the object pattern, and I try to bring in the CSV file, which has the employee stock pay information. I go ahead and click on next, and I select an option to create a table. So tables are constructs within Prism where you store the data. I provide a table name, and then eventually, I click on finish and run now. Once I do that, Prism is going to talk to the AWS s three instance, bring in that specific data file, CSV, and load it into a Prism table just like that. We have loaded over here 781 employee records with stock pay information. The next step is to create a derived dataset where you will be blending the work database and benefits pay data. For that, when you create the derived data set, you use the workday data as the base. So this data is already sitting in workday, so you start off with the data and then start to build your transformations. So you're going to click quick actions and click on edit transformation. As you can see from the pipeline view, we only have the workday benefits data, but then we need to combine it for that. We need to join it with the data that we just brought in with s three. So I click on join stage and then choose the AWS s three stock pay data that I just loaded into Prism. Once I do this once I do that, Prism automatically gives you AI and ML based recommendations and suggestions for the join keys. So I see a worker ID as a 100% match, so I use this as the preferred joint key that the system has automatically given me as a recommendation. I choose an inner join, but I'm just looking for matching rows between the two pipelines. And I have an option just to select the fields that I want to report on. So I only choose the ones that I need, specifically the stock category and stock USD. Perfect. So we just blended the data with our s three data. So let's look at the pipeline. So we had the workday data coming in from the left. We combined it with the s three stock plan data, And boom, it's ready for consumption. But wait. Before that, we need to apply the right security controls. So I go into the data source security model and select HCM all organizations and reports manager as the default security model. What this means is I've secured all of the secure user groups for this data source. And that's it. Click on quick actions and click on publish so that you can start to use this data. So once you click on publish, it'll give you an overlay. And then when you click on submit, it'll take a few seconds to actually publish the data rows. The data is now ready. Now let's look into the last step of how to visualize this data. For that, I'm gonna go into my worker profile and click on drive. Within that, I have created a folder structure that I can repurpose. And I'm gonna create a discovery board, which is the purpose of this exercise. Once I create the discovery board, I have an option to choose the data source that I just published with Prism. So I'm gonna search for that data source. Once I click on that, the builder panel opens up. With the builder panel, I'll be able to drag and drop and build my visualization. So here, I'm gonna choose a chart, which is the bar chart that I want to build, but then I need to fill out the x and y axis. For that, I'm going to drag and drop the total comp amount, the sum of the rolled comp amount in the y axis, and the rewards category in x axis. Now let's see how the Prism data source gets run-in the executed in the background. So you see here, we have the visualization built up, the base pay, the benefits pay, and as well as the stock pay information, all loaded from the Prism data source that we just blended. And it's very easy to duplicate and adjust the visualization based on your needs. So what I'm doing right now is I duplicated the whole chart, but then I can convert this into a doughnut chart so that I can view the same data in a slightly different form. So that concludes the presentation of how we have built a total cost of labor discovery board with Prism data. Thank you. Can you hear me okay now? Okay. Perfect. So I'm gonna continue. Awesome. I know what what you saw in the demo was super interesting. Right? So this this is great because we saw a demo where we brought in the stock plan data, from Amazon s three. We use Prism's suggestions framework, to actually blend both of the data together with workplace employee data. Then we secured it to HR managers and, the reports manager security group. We did that and then eventually published the data source. So Prism with when you publish the data source with Prism, all fields are by default indexed, giving you the best of performance. And the last step we did is we created a discovery board where we visualized the data that we just blended with Prism. Pretty simple. Right? And it's pretty straightforward for you to build the exact same thing. So this is just a sneak peek. Right? So what you saw in the demo was just an AWS s three connector. Prism has a slew of direct connectors to Salesforce, Snowflake, Google BigQuery, and many other commonly used enterprise data warehouse and data lakes. On top of this, Prism offers generic file upload and SFTP capabilities to supercharge your insights. Now, we talked about demos and connectors. Can we get through any presentation nowadays without speaking about AI? So let's dive into what's coming in front of us, with Prism. So the next feature that we will look into is AI powered conversation reporting. This feature allows report users from data to decision making ready decision ready in just seconds. So let's walk through this with an example. As a people leader, I wanna quickly check on my team and answer questions, but I don't wanna dig through spreadsheets or bug an analyst for additional metrics and details. What this feature does is I can ask questions in natural language format and get responses. So in this example, I looked at my team's compensation report and discovered that 41 people had lower comparable ratio score. I can then ask additional questions and it keeps the previous context. So I can ask, like, how many are at retention risk? So I can quickly get an a view of employees with lower compensation who are also a retention risk. Next, I wanna look at high risk employees who are upskilling themselves. I wanna focus on high performers who don't have the necessary AI skills to power up their job. And then I can get a list to target for a learning campaign. Each question gives me clear, quick answers creating a live interactive view of my workforce. Now this feature is currently in early adopter program, and we are getting customer feedback and adding capabilities as we work towards a general availability. Perfect. I know we spoke a lot about data, prism, insights, and how you can supercharge that. I'm sure you're super excited about it. With that, I will pass it back to Callie to talk more about our future with StataCloud. Off to you. Awesome. Alright. Thank you, Arvin. That was a great demo. Alright. I am going to reshare so that we can jump into the Workday data cloud. Alright. So today, we talked a lot about Workday's open platform strategy. So Workday is pivoting from self contained analytics model to an open best of breed ecosystem approach. So this is not just about getting data out to the lakes. It's about bringing context in to enrich Workday. This architecture is designed to feed AI models with high quality contextualized data at scale. So this brings us to Workday Data Cloud. So it's more than a feature. It's an open ecosystem designed to connect your data to the broader enterprise landscape. So once you're on Workday and you have your people and money data unified in one place, we open up the platform so you can adopt and grow your capabilities. We deliver this through four key pillars that you can see here. So first is our zero copy bidirectional sharing. We're breaking down the walls between systems so data flows freely without replication. Second, we provide AI ready data at scale. So we don't just give you the raw data, we give you the semantic richness needed to train your high value models. And third, this leads to faster insights and smarter decisions. So by removing the friction of the data movement, you can answer your critical cross functional questions immediately. And finally, real time connectivity. So whether you need deep analysis or instant operational reads, we assure that your apps and your BI tools have the freshest data possible. So the architecture that connects Workday to your modern data stack is shown here. So at the center is the Workday data lake. It provides efficient, scalable, and governed access to a curated catalog of Workday business objects in the unified data catalog. This exposes our core business objects like worker as queryable tables, and you have two ways to access this. So the first way is through Workday Data Connect, which leverages Apache Iceberg for zero copy sharing with partner platforms like Snowflake and Databricks. This is perfect for large scale analytics. And second, Workday Live Data Query provides a direct JDBC connection for virtually real time SQL access to transactional data. So whether you need deep analysis or instant operational needs, we have a standardized protocol that that's for you. And then Prism continues to power the the high volume data ingestion and transformation. So how do you take advantage of Workday data cloud? So when it arrives, there are a couple of prerequisites that we should talk about. So first, your Workday tenant must be running on the public cloud, specifically AWS for the initial release, and then GCP will follow that. And then second, for data in scenarios, Workday Prism is required. And, naturally, you need to be a user of one of our launch partners, which is Databricks, Google Cloud, Salesforce, or Snowflake. So I know we covered a lot of exciting things today. We covered Workday's open platform and how it provides a secure, resilient, and flexible foundation for all Workday offerings. We saw Prism use cases from Aravind, and we saw connectors and a great demo. So what's next? We invite you to join our Prism community. You can learn more and you can stay engaged with us. We invite you to also sign up for a free virtual Prism test drive and also join our Workday data cloud early adopter program. So now we will kick off our q and a session, of our webinar today. I think we've have a couple of prism questions that have already come in. So, Arvin, I don't know if you had a chance to see those yet. But, if not, I can read them. But, yeah, let's let's kick off the q and a. Absolutely. Can you hear me okay, Kelly? Yeah. Perfect. Perfect. I know there were some technical issues. Sorry about that. But, yeah, I think we got that going. I'm I'm glad it ended up. So I'm gonna take a a stab at a few questions that came. up. I'm I'm reading the questions as we speak. The first question that came up is, is there a limit in terms of how much data we can bring in bring over into Prism? The answer is no. Right? You can bring in any amount of data that you want. Prism entitlements and licensing is structured around how much data you report on top of Prism, which is structured as entitlements, meaning, as part of the demo, as you saw a step in terms of publishing the blended data source, that's the number of rows of data that is counted against your limit or entitlement spottism. So in short, the answer is no limit in terms of how much you can bring in. It's amount the amount of data that you publish out is where you're competent. K? I'm gonna mark that as answered. Next question that came up is, is there a setting to have the AI come up with the suggested charts? No. This is by default given for all Prism users. So when whenever you use the join stage as I showed in the demo, when you blend in two datasets together, you will automatically see a link for suggested joints exactly as you saw in the demo. You click on that. You will see, like, the top three suggestions. We Prism, as a platform, produces the data in the background, look at the two datasets together, combine them, merge all of the data, look at their, enum types and the data types, and then look at their values and then provides you with the suggestions. So, no, you do not need to do any configuration on top of your Prism, tenant model. Perfect. I'm gonna click on that. Answered. Okay. The next question is, how often does Prism refresh data? Can it be more than once per day? Yes. So the answer is we are actively working on a feature for hourly scheduling, but that is more of a future looking road map. For now, we have seen a lot of customers use DCT, which is the data change task that I shared as part of the demo, to schedule it as, every day on a daily basis through the UI. But you can potentially use an API route to schedule it more frequently than once a day. Next one is, can, will data cloud be available on private cloud later? So for that question, yes. We are starting off with public cloud right now, and we are expanding to our other public cloud partners or infrastructure partners. We, I'm not sure if there are any plans to expand it to a a private cloud, infrastructure, but that's something that we can take back, and explore. But for now, it's, mainly the public cloud, customers, the joint customers. Perfect. Can you please send the links for each element of the top three takeaways? I'm I'm sure you're gonna get, the, reference links and all the decks and the recording, everything back, for you as part of the webinar. So, yes, you should be able to take that back. So you're gonna see links like, the three things that Cali touched upon in terms of our takeaways. I run a, a Prism customer community group made up of, like, more than 1,400 plus customers. We meet. We it's a very collaborative and thriving group. A lot of questions come up in terms of best practices, earlier doctor programs, recruitment, and even product feedback. So, again, highly welcome you to, recommend you to join the group. Just search for Prism community on, on your Workday community profile. Search for Prism customer group, and you'll be able to find them and click on request to join. The second one is Workday data cloud. Definitely, you'll have a link to that. You'll be able to sign up for that one. And then the last one is to build the exact same demo that I showed you right now. You can do that exactly free in a virtual test drive webinar setting, so you'll be able to sign up for that one. Mhmm. And, Arvin, I saw a couple of questions on Workday data cloud and how. to join EA for conversational reporting and for data. cloud. So we can put those links under resources as well if people are interested in the EA program for both of them. I also. saw a question on data cloud for availability. So we're targeting, generally available twenty six r two. But as I mentioned earlier, the early adopter program will start, in early March twenty twenty six. So I'll have the links in there for the EA program too. Okay. Yep. Yeah. That'll that'll go out. Anything else, Cali, that, strikes you? Okay. So how do you join the early adopter program for conversation reporting? It's already on course right now. So we do have, customers who are already validating the conversation reporting feature, but we will post community updates, in terms of where we are progressing and how it will be made generally available. No. Anything else? Workday Prism has specific limitations regarding the number of rows prod that can be processed. So, no, we do not have any specific limitations. We Workday Prism serves our HR and finance audience. Finance, as you can imagine, has huge transactions scaling up to billions and billions of records. So we do have customers using Prism for those natural use cases as well. I I think Like, it's The SIL, technical difficulties, can you all able are you all able to hear me okay? Yeah. Okay. Got it. Just wanna make sure there were a few questions, like, I could hear Cali, but not Arvin. So Oh, I also wanna mention one thing. I just saw a question come in, that was general very general. So I'm excited that, you know, today, we talked a little bit about Workday Data Cloud. The question is, can you tell us a lot more about Workday data cloud? Great, great question. We can't wait to do that. As we get closer to EA, we have another looking forward with, Workday scheduled for, I believe, March. That will all it will cover Workday data cloud in much more depth. So today, we're just introducing it. So we'll be sure to let everyone know on this webinar what that exact date is once we launch that registration page. So that is a great way to learn more. Yep. And, thanks, Kelly, for filling that in. And, there was a question on how will we be charged with that compute cost. Yes. All of that is being worked out right now, so more details will be coming out to you, as we explore the Yep. program. Perfect. I think, we can I I don't think there's anything more to add to this? So should we close out? I think thanks all for joining. Kelly, do you wanna close it? Yeah. Thank you. Yeah. I think we got most of the questions, but, again, you know, under resources, we'll make sure that everyone gets access to all of their, you know, how to learn more and community links. So, yeah, thank you, Arvin, so much for covering the use cases and the excellent demo. And we thank everybody for joining, and we look forward to our next webinar in March that will be a deeper dive into this topic. So thank you. Thanks, everyone. Have a great work day, and happy holidays. Mhmm. Thanks.