Name: Open Platform Advantage: Elevate People & Money Data Across the Enterprise with Workday Data Cloud
Uploaded: 2026-03-26T18:16:13.376Z
Duration: 53 min 45 s
Description: Open Platform Advantage: Elevate People & Money Data Across the Enterprise with Workday Data Cloud

Transcript for "Open Platform Advantage: Elevate People & Money Data Across the Enterprise with Workday Data Cloud": Hi, everyone. Welcome to Workday Data Cloud opening up the platform with accessible, secure, and AI ready data session, session as a part of the broader Workday looking forward webinars. Today's webinar is part of our broader looking forward webinar series designed to give you insights into how your organization can do more with Workday, including additional ways to support how you manage your people, your finance and your businesses. We have a few forward looking statements. Please note this is under our safe harbor agreement. And a few logistical things, a couple of standard housekeeping items to keep in mind. First, we are recording this session, and we will be making it available to you via email up to forty eight hours from the the session. So please be on the lookout for for that email to receive the recording and watch it again or share it with your colleagues if you want. We are using Goldcast platform for our looking forward webinar. This allows you to submit your questions, get access to resources that are provided to you, and provide feedback. Feedback is really important to us, so please please do that. Goldcast operates most effectively when using Chrome. So if you are experiencing any issues at this time, ensure you are using Chrome. That that can help you to resolve some of those typical issues that might arise. If you have any technical issue during the event, please notify us using q and a function that you can see on your screen. You can get even more out of this webinar by using the tabs in the top right corner of the screen. Docs has links to some valuable and related resources, and Q and A is where you submit your questions via the q and a function. We respond to questions directly via the chat. And at the end of the session, if time allows, we will take some questions online. If for whatever reason we don't respond to your question during this session, we will get back to you with an email. We will send a reply with complete answer for for sure with with the context of your question. During the webinar, we will also kind of encourage you to provide your feedback. As I mentioned, at the end of the webinar, there will be a survey. So please make sure that you complete the four question survey at the end of the session. We appreciate your feedback in advance. So let me, introduce the speakers of the today's session. First, I want to introduce two of the greatest leaders that we have on the product side who are leading all the innovations related to Workday Data Cloud, Krupa Natarajan, senior director of product management, and Brian Carlo, senior director of product management. They will walk you through the key functionalities and the capabilities of Workday Data Cloud and how it's going to help you to establish a solid data ecosystem around people and finance data. And I'm Babak Ghoreyshi from product marketing, supporting them and helping you to get on board and, like, leverage the Workday Data Cloud upon much of the solution. Today's agenda includes talking about the capabilities of the Workday Data Cloud. We will introduce it, break it down for you to different elements and different functionalities, and then we will discuss how it's going to help you, what values you're going to get from Workday Data Cloud. We will have a very good comprehensive demo that walks you through different steps of connecting Workday with the ecosystem. And then we will talk a little bit about what is coming soon and what's next and what you can expect as the next steps. So let's dive deep and go into the conversation. Let's start with the shifting mandate for the IT and the mindset shift that IT leaders across the board are experiencing. Regardless of being in corporate IT, HR IT, Fins IT, or the other parts of the organization, we're all facing some similar trends. We want to safely adopt AI across the board, across the enterprise. We want to make sure that we are unifying data and the context of that data in the best possible way. We want to simplify and respond to the needs of the business and respond to the needs of the business functions across the board. These these are the similar trends that we see across the board. But all of these require a solid data foundation, a data foundation that helps you to have a good data flow across the board, and you can fuel all those AI solutions and agent solutions properly. So, let's let's take a look at the pain points and challenges in the data ecosystems that we are facing today and many of the organizations who are using the systems that don't leverage these modern technologies might be facing. The first bucket, very typical, very common, the burden of ETN and custom integrations. We are all dealing with extract, transform, and load problems. We are all dealing with data duplication risks that come after that set of integrations that are heavy from the beginning, from the consultation phase to design phase to implementation and deployment phase to maintenance phase. And that then that creates another sort of problem that you have multiple copies of data in different systems and different applications and different data warehouses that you need to keep up to date and you need to maintain as secure. That's a lot of work. Then there is kind of a typical problem that we are totally aware that some some trusted working data were previously isolated from the enterprise analytics and AI. And many of our customer base wanted to make sure that they can get the best out of their people and finance data. The last bucket is about the value, the ROI that you expect to get from all your investments that you have made, either in Workday or the BI tools that you have in place from Tableau to Power BI and so forth, or the data systems, you know, with Snowflake, GCP, and other applications that you platforms and infrastructures that you have in place. And we want to make sure that all of them are working in the best possible way together so you maximize your ROI. So with with all those challenges and all those data ecosystem management problems that we we talked about, let's talk about Workday platform because that's our strategy to solve all those problems in the audience level and in the the data ecosystem. We are bringing in the Workday data platform to you and opening up our platform with AI ready solutions. We are bringing data that fuels intelligent decisions wherever those decisions are made. We're offering tools and ecosystems to build an action with AI and create and develop in the way that you want, leveraging all those familiar experiences, security models, and so forth. And also, you're connected wherever you work. So data and information and processes come to the place that you're familiar with, you're comfortable with, and the work is taking place. So users get excited about the things that they can do. And all of these are happening on top of a foundation that's based on trust, compliance, security, auditability, governance, and all of them are globally available. That creates a solid foundation, and that gives us the opportunity to expand and open up our platform. So now Workday Data Platform is the most trusted people and money data foundation that you can have to open to the broader enterprise and complete your data strategy and have seamless connection between Workday and the rest of your ecosystem, whether it's a BI tool, whether it's a data warehouse, data lake, analytics tool, apps, and so forth. This opening up strategy and approach that we have been taking helps you have a kind of a solid foundation that reduces your risks. It maintains governance and security without duplication of the data. It helps to lower integration complexities. You don't have to deal with multistep integrations anymore. It reduces custom integrations and ongoing maintenance coming after deployment of those integrations, helps to accelerate the time to value and get trusted people and finance data where your decisions are actually made, And it helps to have greater value from existing analytics and reporting tools that you already have in place, and you are in control of your contextualized data connected across the enterprise. So Workday Data Cloud helps you to connect with some big names, some big data platforms that you already have, Databricks, Google Cloud, Salesforce, Snowflake, and many other partners in future. It helps you to unlock the value of your data, your most valuable, precious finance and people data. Now let's start looking at what the data cloud. Let's see what components it has, what elements it has, and how it looks like. So you can see on this chart that you can basically divide into two important sections that completely aligned with each other and work together. On one side on the left, you see the key elements of the product. We will talk about the details of them and we will double click on all of them, but let me have a quick overview of that first. So Workday Data Lake, it basically helps you to leverage OpenSanders. It's it's a great technology to get the best out of, you know, big big data analytics type of things. It helps you a lot in that area. Then we have worked in live data query. Enables you to have SQL queries and, you know, we basically have a SQL interface to have queries for specific data and interactions that you need to grab some data from the system record or another system that's sitting somewhere else. And then we have Prism Data Management that helps you with all those ingestions, transformation, drones, so forth. All those great capabilities that come to data inside of the story for Workday and helps you to bring in and blend in the data in the way that you need. On the other side, on the right side, you see some trusted partner platforms. They play a key role here, from across the data lakes, data warehouses, application, and media tools. They are working hand in hand with the elements that we have inside the product to make it happen, to make a good, solid ecosystem. And they are talking to each other with zero copy access, bidirectional zero copy access. Let's talk about zero copy access. What does it bring? What does it mean, basically? So zero copy access basically removes the need for having multiple copies of the data on multiple systems. It helps you to eliminate complex and costly ETL pipelines, helps you to maintain governance from the system of record, helps to reduce the data movement and redundancies and multiple copies that I mentioned, accessing data, where analysis and AI actually live and where you need to access the fresh data is is possible with that. And it helps to preserve that context of freshness, especially when we talk about freshness, are referring to that live data query, we will talk about it more in the following slides. The other concept is that that is very important to tap into it before getting to the discussions around functionalities is the security and governance. Security and governance in Workday Data Cloud is by design. It's the same trusted model that protects the Workday applications and protects your data. It helps to lower the risk with real public connectivity because data is queried in place rather than replicated, and it reduces the sprawl attack surface and exposure. It helps to have a kind of consistent security model across the board. You have the option to adhere to the same Workday permissions, access controls, and governance policies inside and outside Workday. It helps to centralize your compliance. A single source of truth simplifies auditing and supports regulatory requirements. And also, you have governed openness, open standards like Apache Iceberg with Workday governance enforced on every query. So with that in mind, let's dive into the key elements of Workday data. So I'd love to invite Brian and Brian to walk you through the next chapter of this presentation. Thank you. Great. Thanks, Babak. So as Babak mentioned, I'm one of the key product leaders who's helping to bring Workday Data Cloud to life. And and and let's dive a little bit deeper into some of the the new products as part of this this amazing new product suite that we're excited to bring to market. So this is the architecture of Workday Data Cloud. It is an entire product suite designed to let data flow. So on the left, you'll see our ability to flow data into Workday from partner platforms. And on the right, you can see how the same technologies let Workday data flow out virtually to data lakes and BI tools from those same partners. So whether you use Databricks, Salesforce Data three sixty, Snowflake, Google Cloud, and more in the future, we're going to provide the flexibility to choose the right tool for your specific data needs. So let's zoom in and take a look at three key elements of Workday Data Cloud. The first is the Workday data lake. In the data lake, you'll find curated tables of the most critical people and money data from Workday. Think worker or journal line, already structured, governed, and ready to be queried. That data is exposed as Apache Iceberg tables. Now Apache Iceberg is groundbreaking technology. It's the open standard for managing big data, and it powers the biggest technology infrastructure on the planet, including Workday Data Cloud. By embracing this open standard, we get interoperability across all our platform partners. Iceberg allows for queries to quickly and consistently pinpoint the exact data that you need before the query does the work. It's incredible. And what that unlocks is astonishing performance gains. The query gets just what it needs just in time. So for performance at scale inside Workday or outside Workday, this is gonna be a huge game changer. When you only get what you need, you don't have to play the ETL game anymore. Now the trade off is that the data in the data lake is materialized. What that means is that we refresh the data on a schedule. We do all the work up front on behalf of our customers to make sure that those tables of data are structured, governed, and ready to be queried, and that will be configurable by each customer. Every week, every day, every several hours, we will refresh the data for you. For exploratory AI and analytics, this is the way to go. But for some use cases, data that's a day old or several hours old, that's not gonna cut it. And that's where another Data Cloud product really shines, Workday Live Data Query. This is a SQL interface. It sounds complicated, but it's not. It's just SQL. But for our customers, we know this is gonna be a revelation. SQL is the language of analytics. SQL is the language of agents. And for the very first time, we are gonna speak the same language as everybody else, opening up a standard SQL connection for Workday. When a live data query runs, it runs directly against your tenant for live results, honoring all the contextual security that we know is a must for our customers. When freshness matters more than volume, things like operational dashboards or workflows that need to be up to the second, up to date with the full power of Workday contextual security on a per user basis, this is gonna be the fast lane. Now there's another technical term on this screen, JDBC. That's Java database connectivity, which is another open standard. Live data query is a JDBC driver. And what that means is that you can plug that driver into your BI tool of choice. So maybe you're also a Tableau shop along with Workday or a Power BI shop, and you want those tools and those users to be able to leverage Workday data too. With Workday Data Cloud, you can do that. It's SQL. It's live data with no clunky pipelines honoring contextual security down to the user level for access control. You choose the customers that you want to use. That is the power of the open AI ready platform. Now what's really cool about these two technologies that power Data Cloud, JDBC and Apache Iceberg, is that data flows out, but it also flows in. And that's gonna open up some amazing new possibilities for our customers. Krupa, why don't you come on stage and tell us what you think about that? Great. Thank you, Brian. Brian's exactly right. Now imagine taking that power of SQL and the raw scale of iceberg that Brian talked about and flipping it around so you can put it directly into the hands of your HR and finance leaders directly within Workday. I want you to feel the gravity of what you're holding here. You now have the keys to data from across your entire enterprise right within Workday. Think about the world that this opens up. For the sales manager, you can now see real time deal status from Salesforce Data Cloud sitting directly inside your people manager dashboards. For payroll specialists, no more data scavenger hunts. You're able to now pull data from stock platforms in various benefit systems alongside payroll data with zero copies. This isn't just the data access. It's an unlock. We're talking about suddenly opening up access to the entire universe of enterprise data ready for AI and for agents and for deep analytics within Workday for HR and financial professionals. And here's the kicker. We're not only unlocking enterprise data for HR and finance, but are giving you the entire power of Prism data management. Now HR and finance can take the whole gamut of enterprise data, can join it with Workday data, apply Workday security context on that data, perform calculations, publish curated data sets as sources of truth, track the entire lineage, have automated governance, and so much more. All that goodness just automagically unlocks on your enterprise data. Now that's super powerful for HR and IT. Now let's talk about evolution. We as Workday have evolved from a unidirectional data story, one where Prism was our only offering to ingest external data into Workday, to a strategic bidirectional data story and augmented it with the latest and greatest innovations in the data industry by embracing open standards. Data cloud introduces a new complementary access pattern. Now no matter where data resides, no matter who the user is, and no matter what the consumption tool of choice is, Workday Data Cloud provides that capability. Prism is not being replaced but enhanced. Prism remains a critical component to the data cloud story. Prism provides self-service for HR and finance to be able to define and manage the data that you all need to achieve the level of insights and answers at the speed of thought and the speed of business in today's demanding world. While traditional Prism focused on data ingestion, Workday Data Cloud now supports both patterns of zero copy data access and ingestion. For existing Prism customers, this is a pretty neat upgrade and protects all your investments in Prism. When HR and finance need to own and manage data, data in Prism remain the correct and proven approach. What changes with Data Cloud is that ingestion is no longer the only option. Zero copy now introduces direct native connectivity to data where it already lives without needing to copy it into Workday and support data freshness and minimize data movement. The important point is this. We're now avoiding the old extremes, either everything copied into Workday or everything left unmanaged outside of Workday. Instead, you can now choose the right pattern for each of your use cases. And this evolution has been intentional. Now let's take a look at how we've evolved to this point. Starting from the left, this starts with data right within Workday. Workday has rich, trusted data. And from day one, Workday hasn't just been about storing records. It's about embedding business context, identity, skills, roles, organizations. This context is what makes Workday data inherently trusted and meaningful. Context is native and not reconstructed later. On top of that, Workday unified people and money data into a single consistent model that eliminated the need to constantly reconcile HR and finance data across disconnected systems. This created a core foundation for scale and trust. Prism Analytics was the next step forward. It allowed customers to bring external data into Workday and analyze it securely and governed inside the platform. For many customers, this is a powerful way to enrich insights without losing control. Now with Workday Data Cloud, what's changed is where value needs to be created. Analytics, AI, and decision making don't live in one place anymore. They live across the enterprise, and Workday Data Cloud extends the value of people and money data beyond the Workday boundary without losing the context, governance, or trust that we started with all the way to the left. So when we talk about Workday Data Cloud, we're not talking about abandoning what made Workday strong, but talking of taking that same trusted foundation and making it work in a modern open data ecosystem. Now let's bring this back to the architecture that Brian started off with. On the left, we have the various partner data ecosystems that we now have direct zero copy access to. We have the power of Prism Data Management with its data transformation, data lineage, security, and governance. All of these features added on top of it. We have the Workday data lake that brings together all the Workday data in one place for external access and live data query that completes that loop with direct SQL access to Workday data from all the same partner ecosystems. Together, this powerful platform supports analytic, AI, and agentic workloads within Workday and beyond. Now with that, I'll turn it back to Brian so he can walk us through a demo. Great. Thanks, Krupa. Okay. So I'm gonna share my screen for that demo now. And this is the this is the fun stuff because this is the kind of stuff that I do in my spare time at work as well. I'm a data professional as as well as a product leader. And so we wanna kinda step into the shoes of of someone who might be on your team or maybe you're a data professional yourself. Right? So let's imagine that you are a data scientist working for a major retailer. And, your boss comes and says, hey. We do most of our sales at the second half of the year. I want you to make a take a look at the data that we've got available in Snowflake and see whether our, current staffing levels are gonna be, in a in a great spot for that big, sales push in the second half of the year. And so this is what I see. Right? I've got a bunch of different, tables related to store sales and inventory, and and maybe a store staffing table. And the question, I guess, that I would have as a data scientist is, like, is this gonna be enough? Right? So, I mean, I could take a look at some of that, data and see, well, here's sort of what I'm seeing from from the past related to the data that I've got in those snowflake tables, but I don't know if that's really what I want. Right? Like, what about the data from Workday? What about the hiring that might be in the pipeline right now that's ramping up? Maybe, hires that have already been made, but they haven't showed up on-site at at at at the store level. And so, ideally, you wanna look at data that's not, stale data that's reflected in the, of of the past. You wanna look to the future. Right? And so as our Workday customers now, this is what you've got available to you. You've got a Snowflake connector, to to Workday using reports as a service with Rats. And, again, as a data professional, I know what this is like. Right? As a data scientist, you want data from Workday, and that means that you have to go to your HR function and beg for someone to create a custom report, enable it as a web service, then you're babysitting some fragile pipelines, and then comes the wait. You've got hours of extraction time. You're hoping that it might land correctly here in Snowflake. And anyone who's ever dealt with this knows the reality. By the time you've cut through all the red tape and you've designed your ETL, that might take months. And for a business that has to move fast to make sure that it's got the right staffing levels, that could be a nightmare. But now with Workday Data Cloud, we're gonna see a new option here, Workday Data Connect. And Workday Data Connect is the product that will allow for you to make that Apache iceberg connection into Workday Data Cloud. So data connect avoids that RAS call, goes straight into the Workday data lake using Apache Iceberg. And so once you've done that, you see all of your Workday data tables here now in your Horizon catalog. It's kinda like magic. Right? Instead of building custom pipelines, you've got this full catalog of Workday tables available for you virtually. Instead, in the past, you would have had to lift and shift all that data into Snowflake before. But here, I just see it instantly. And when I run a query against this table with Apache Iceberg, before any query processing, we fan out to the Workday data lake. We know exactly what data that you're gonna need, and we're gonna ship only the precise data you need over to Snowflake so that you can do your work right in memory. And that allows for those blazing fast performance gains. So okay. So now that I've used Workday Data Connect connecting to the Workday data lake through Apache Iceberg, this is what I see. So before, my previous model was here in red. That was, like, the the old data. But here in blue, this is the data now using Workday Data Collect Connect through Apache Iceberg to the Workday Data Lake. And so what you see here is there's nearly a 4,000 worker gap here between what your model had predicted based on the old data versus your model, using the the fresh data from Workday Data Cloud. And so without your actuals, you you might be in a scenario where you would have kept on hiring into a massive surplus of workers. And you can even see work that, Snowflake's, Cortex agent chiming in up here with the same exact insight. So because of this insight, I, as a data scientist, I I've got I I realized I've got a really big problem. And so I show this to my manager, and my manager gets really excited and says, oh my gosh. This is a big problem. I I need more data. I need to get even more granular. I wanna per store analysis, and I don't wanna have to rely on you. I wanna be able to to to analyze that data myself in real time so that I can share it with executives because they're probably gonna have questions, and I wanna dig into that. The problem, though, is my manager isn't a Snowflake person. Right? But he is really comfortable with Tableau. So with Workday Data Cloud, that's not a problem. All I need to do is connect to Workday Data Cloud using Workday Live Data Query. So here, you see all the different connectors that are available within Tableau. And as I had mentioned, Workday Live Data Query is a JDBC driver. So here, I make sure that I have connectivity to that driver. And then I see the same tables from the unified data catalog within Workday Data Cloud with all of that worker data and hiring data that I might need. And so now if I wanna drill in on a per store level, I can actually see that same, previous forecast in red and the the new forecast in blue. And so I can see which stores are actually we might be behind on our hiring targets and some that might be woefully ahead of time. So okay. So data scientists found an insight. Management has confirmed it's a problem. Right? The data scientist knows it's a problem. My manager knows it's a problem. He's shared that with the executive team. They really understand that it's a problem. And so what do we do? How do we make this, insight turn into something that can, like, totally overhaul your business? Are you going to train all of the regional managers and store managers on how to use Tableau at scale? I don't know. Maybe there's a better way. So, Krupa, why don't you show them what that might look like? Of course. Thank you, Brian. So just connecting the dots here. So Brian is the the high paying data scientist up in corporate IT that's done his amazing analysis. And they're as identified that hiring is planned versus actual is not where it needs to be. Now we're gonna bring it down at the store level. So I'm gonna play the part of a store manager. I've been told that we need to take a closer look into what the hiring status is and understand if there's a gap in in terms of either needing to hire more store employees or less and then figure out how to go about actually actioning on that. So I'm here as a store manager within the Workday experience. And from here, I can now connect to Snowflake. And just like that, instantaneously get access to the results that Brian had created all the way back in Snowflake from his modeling and data science exercises. Just as Brian was able to browse Workday data within Snowflake, I simply need to click and can browse data from across Snowflake, Databricks, and Salesforce, and many more partners all within the Workday experience. So here, as a store manager, I'm interested in that in understanding what the store performance is. And I also have access to customer sentiment data, labor hours, and so on. All of this use this useful context now sitting in that enterprise data lake, I now have instantaneous access to. So I go ahead and select the data that I need, blend it with worker data that I have access to within Workday with just a few clicks. And now I have access to this to this dashboard that provides me with a complete picture of everything that I need to know for my store. So here I have customer satisfaction scores, which was data that was available in the enterprise data lake, sit accessible for me so I can get the average CSAT across my store employees. I have the revenue metrics by store. I even have a mash up of the skills that my store employees have against the impact and the CSAT that they've created, which is data coming from outside of Workday. Now I can drill into this combined view of data that combines my worker data with their skills, with the commissions that they got, with their average CSAT scores that they gained, and how much they attained against their quota in terms of sales. All of this information matched up and available to me in a simple view within Workday. Now here's where it gets super powerful. With Workday Sana analytic agent, now I not only have access to this data, but I can ask pretty insightful questions such as what are the common skills that my top employees, the top performers are having? And now Sana can come back to me and tell me the results, is blending the skills data and Workday with the performance data that's coming from the external system to tell me exactly the skills that my top performers had. Now remember the analysis that Brian did? It turns out that my particular store is actually understaffed for what we need. So I need to go ahead and hire new workers to make sure that we're staffing up to our needs. And now not only do I know how many people to staff, but because of this mashed up data and and Sana giving me insights, I know exactly the type of skills that I need to to have in terms of who I need to hire. So now because I'm embedded into the Workday system, I can go from insights to action with just a few clicks. So right here within my conversational experience, I can have a very simple natural language command to say, let's open go ahead and open up a job rec with those top skills that are producing the highest performers. And within the Workday system, this integrated experience takes me from insights to action with just that single click. So now I can go ahead, not only gain those insights, but take action by creating a job requisition with the relevant set of skills that ensures that my store employees are going to be successful. And just like that, we've gone from external data mashed up with Workday, providing broader insights to natural language questions leading to insights and not only insights but action. That's the power of the blended data ecosystem with Workday Data Cloud. Now that's all great. Now I'm going to bring us back to some of the value that you can gain from real world use cases. To see how this works in practice, now let's take specific value that Workday Data Cloud can deliver to each of your functions. For the CHRO, you can now build high impact predictive models for attrition, for internal mobility, etcetera, by leveraging Workday's rich HR context. By combining this with external engagement or learning data, you get much deeper insights and understanding of your talent than ever before. For the CFO, the platform allows you to drastically improve forecasting and scenario planning. By blending Workday finance and spend data with external market datasets with zero copy access, you can support complex finance financial processes without the need for manual data moves. And last but not least for the OCIO, we're fundamentally simplifying your enterprise analytics by eliminating custom brittle ETL pipelines from Workday to your data lake and the other way around. You can now connect directly for JDBC and Iceberg, accelerating AI experimentation with performant access to trusted data that teams need. Let's put this into a few different example scenarios. The ultimate goal of this open platform is to provide a complete picture across every corner of your enterprise. For HR and people, you can leverage data such as competitive wages, accident reports, labor statistics, sentiment analysis, and drive insights such as reducing turnover, closing skills gaps, or reducing safety incidents. In finance and strategy, you now have instantaneous access to supply chain data, bank feeds, market volatility streams, and even sales performance as we just saw, and improve accuracy and forecast profitability as well as control the costs. When it comes to operations and quality, you can have access to point of sale data. Have if if you're in the hospitality industry, even look at occupancy rates or fleet management in in transportation industry, call center records, more. And all of this can lead to optimizing staffing, increasing customer satisfaction, and boosting efficiency. And when it comes to IT and transformation, access to legacy systems, subsidiary records, policy analysis, and regulatory details can lead to accelerated scenarios in terms of m and a's, derisk your m and a situations, as well as streamline compliance. All of this is now simplified through the bidirectional zero copy data access that Workday Data Cloud offers. Now I'll turn it back to Brian to walk us through the road map and what's coming up next. Great. Thanks, Krupa. So here's where we stand with our current road map. This month, we just opened up our first early access program for Workday Data Cloud for a catalog of HCM and talent data. So you can think about just like we talk about Workday being the open platform for, people, data, money, data, and and agents. We're gonna, lead with our Workday Data Cloud offering with our people catalog. So we're in the early adopter phase now for that, and we expect that Workday Data Cloud will be generally available by rising of this year for that same catalog of people data. Next, we're gonna follow it up with money data. So a financials catalog will be made available at that same time frame for our general availability release date. We're gonna work with early adopters and get that catalog ready for general availability by twenty twenty seven r one. Now what's also very exciting is Prism data will also be available to read out of Workday, data cloud using those same Apache Iceberg and JDBC connectors that we mentioned before with the same release cadence, as our as our financials data. So Prism data will be available to read out of the system through Live Data Query and Workday Data Connect, for early adopters by twenty twenty six r two. And then by twenty twenty seven r one, that will also be generally available. Now you may also have some questions about pricing and packaging for Workday Data Cloud. We're happy to share with you two new SKUs for Workday Data Cloud, Workday Data Cloud Core and Workday Data Cloud Pro. Now this will have a hybrid pricing model that combines those SKUs with our new Workday Flex credits so that as you scale your usage of Workday Data Cloud, you can take advantage of those Flex credits. So for Workday Data Cloud Core, this is gonna be designed for low data volume and simpler use cases. It's gonna provide bidirectional zero copy data cloud access without advanced data preparation. Workday Data Cloud Professional will be designed for enterprise scale data usage. This includes Prism data management for ingestion, joins, and advanced transformations. This will be required for customers to define and manage complex, high volume, or multisource data products for enterprise way wide analytic and agentic consumption. So for Data Cloud Core, you can think about this as a natural entry point if you're a customer who's eager to try out Data Cloud, but you wanna experiment before you go all in. Maybe you're still early on your journey ramping up with a platform like Databricks or Snowflake. But Data Cloud Pro, this is where we think most of our customers are really gonna wanna go. It's all of the features and functionality of Prism today, plus those new zero copy connectors with Iceberg, plus live data query for live SQL functionality and your BI tools of choice. This is where you'll see the bulk of our innovation investments headed forward. And as we onboard other Workday products into our unified data catalog, it will appear in Pro. When we talk about the open AI ready platform, we're really talking about Workday Data Cloud Pro. Pricing details will be shared ahead this summer ahead of our GA launch in the fall. Now I'm gonna ask Vivek to come back on stage and share a little bit more information with you about Workday Data Cloud before we enter our q and a section. Bye bye. Thank you, Brian. It's great. I'm excited about this. I'm pretty sure lots of our customers and prospects and partners, they're all excited about it because this is really the way that we are opening up our platform. Workday is not just a system of record. It's more than even action and engagement. It's a open trusted platform. And in openness, it's built on a solid foundation. So we we have had more than 75,000,000 users, more than 1,000,000,000,000 annual transactions, a unified data and processing model. It's it's a solid foundation that's built on twenty years of trust and experience. And with that, we are ready to open up the platform. We are ready to make sure that all our customers get the most out of their valuable contextualized data for people and finance. So to wrap up, let's let's have a quick look at kind of the key fun kind of dimensions of the Workday Data Cloud and the great values that it brings to you. Let's think about the first one, zero copy bidirectional access. We talked about it in-depth a little bit. So you can share and query data across systems without replication or loss of control. That can help you a lot to maintain all those connection points. The real time fresh data access with live access to transactional, operational, and AI driving use cases, you can definitely take the next step. When we are talking about this, we are particularly emphasizing the live data query or SQL driver that we have. Faster time to insight and action now is possible. You can eliminate ETL bottlenecks and accelerate analytics and reporting and AI and operations across the board. And AI analytics, are using the data that's ready for the operations, the data that is contextualized and carries all those business context and relationships. And people and money are fueling your enterprise AI and innovations that you have. So to get ready for Workday Data Cloud this year, keep in mind a couple of, important kind of foundational requirements that are, you know, tied to getting the most out of the work, the data cloud, obviously. First of all, you need to be a public cloud customers. You need to be on AWS or GCP. Now we have started our EA program with AWS, and soon we'll be expanding to to GCP. Obviously, to use the upper GI spoke and do it walk the data connect for those kind of activities in the analytics and big data scale, you need to have one of those trusted partners. You know, Databricks, Snowflake, Salesforce, and very soon, GCP. And, now that we are getting to the end of this presentation, please make sure if you're a customer that you visit our community page. We have a very good set of resources there for you that you can leverage, familiarize yourself, share with your teammates and colleagues about Workday Data Cloud and how you can start and prepare for the global availability of that later this year. If you're an if you're not a Workday customer, if you're a a kind of you're familiarizing yourself with all the possibilities that Workday platform brings you, we have a very good web page on Workday.com for Workday Data Cloud that can be a good starting point for you. And please let us know if you're interested in Workday Data Cloud. If you have not filled the EA interest form, it's available on community page again. Please go find it and share your feedback and share your interest with us so we can consider you for the future cohort as we get closer to the GA as well. Workday Data Cloud is how trusted people and money data becomes enterprise wide value, and it's basically the next step in Workday's journey. So I want to invite you to join us at DevCon, the developer, kind of, event and conference that we will have later this year in June in Las Vegas. Please join us there. There are lots of things to explore, lots of things to play with and experiment with from the build tools to AI and agentic capabilities and, obviously, Workday Data Cloud. Come join us there to build with Workday Data Cloud at DEFCON so you can experiment with live data query that we talked about, data lake and data connect, and agenting solutions that you can leverage on top of them while using the data platform and BI tools you already know and you already trust. So please register, and we will see you at DEFCON. Now we have just a few minutes at the end to to answer some questions. I want to ask Krupa and Brian to come back to stage so we can take a few questions live, hopefully. Thanks, Vivek. I think some excellent questions on q and a. Most are answered on the panel. I'll take one live here. There were a few different questions around Prism pricing, packaging, and data cloud. So for customers that already have Prism today, we are working out the details of Workday Data Cloud packaging. So please stay tuned. We'll come back to you with that. In general, we want you to take away that if you have Prism and you upgrade to Workday Data Cloud, all of your Prism investments will remain intact, meaning that you don't need to reimplement or migrate anything over. So if you've defined Prism published data sources that you're using in reporting within both API, those would remain the same. What you can now do is expand into live data access to additional data as well as expose the Prism data that you've created to external reporting tools like Tableau or Power BI or or external partner ecosystems through Workday Data Lake or Live Data Query. So it's an expansion. You would not need to do any migration from a technical perspective and and then expand the capabilities. When it comes to packaging, we're still working through some of those details of what upgrade from Prism to Workday Data Cloud would look like, and we'll get back to you with those details. I see there were several questions about getting on board with EA program and information related to that. As I mentioned, please go to community page. We have a page dedicated to data cloud when we share the resources. The links and directions will be included, obviously. But you can you can find lots of good information there, and you can you can fill that the EA form there. I see that some the people ask about her requirements and being on AWS or GCP. Brian, do you want to kind of just expand a little bit on those type of requirements and the the the value of being a public cloud customer? Yeah. Yeah. Absolutely. So, we've been talking about, the value of, running your Workday tenants on on the public cloud for quite some time here at Workday. There's lots of great benefits for running on the public cloud, including a a reduced maintenance windows, follow the sun type, maintenance windows. So if you're a global customer that you're, based outside of of the the few key time zones where we run, your tenants in our private data centers, it's really great to be able to minimize the amount of disruption, to to your business, by by running your, tenants on the public cloud. But the the big reason why we're excited about the public cloud is it gives us access to all sorts of different types of innovations from those hyperscalers, AWS and GCP. And Workday Data Cloud's architecture is built using many of, those public cloud native technologies. So that's the reason why it's required, to migrate to the public cloud to take advantage of Workday Data Cloud. I know we've gotten lots of really good questions about what's the best way to prepare for that. We've got some dedicated resources available, on community as well, to think through what would it what would it look like to to manage your migration to the public cloud. And we think that Workday Data Cloud is actually gonna play a really key role for that, for you, as as you think about a migration if you are running in in the Workday, private data centers. One of the reasons for that is as part of that public cloud migration process, we ask that you go and revisit all of your integrations to make sure that they're gonna work seamlessly when you move from a private data center to one of the, public cloud, providers that we partner with. And it just so happens that Workday Data Cloud is also probably gonna be a great resource for you as you're rethinking a lot of those integrations. Right? Maybe you set up some ETL jobs a long time ago that you haven't touched in a very long time, and, you'll you have the opportunity to go and revisit that and think about it from a data cloud native perspective on on day one of your migration. So feel free to, take a look at some of those resources on community to think about how you might prepare for your migration into the future. Wonderful. Thank you, Brian. Krupa, I'm going to combine a couple of questions that I saw in the q and a section. So you talked about Prism very well. There are questions about, hey. Is Workday Prism Analytics needed for Workday Data Cloud? Is it a requirement? What happens to the private cloud customers? Can you elaborate on that and clarify the relationship between Prism Analytics and Workday Data Cloud and things like that? Thank you. Sure. Sure, Rebecca. When when you need when you decide to purchase Workday Data Cloud, you would not be required to purchase Prism. So it'll be an independent SKU. Unless you're an existing Prism customer, then we'll have some options for you to upgrade from Prism to Workday Data Cloud. Workday Data Cloud will be offered public cloud only, as Brian mentioned. Prism will continue to be offered on private and public cloud. So again, if you are looking to purchase Workday Data Cloud, we do have some options to accelerate you into the public cloud migration journey. So please talk with your account team and we can definitely you know, we heard someone on q and a say they're waitlisted until next summer. There is potentially an acceleration path when you're taking up Workday Data Cloud. So definitely talk to your account team. And then for whatever reason, if you're not able to get onto public cloud, then Prism will remain an option. That's it. Prism if you're an existing Prism customer, you're gonna continue you would not be forced into an upgrade. You can continue. So no no panic there in terms of timelines, but it is a very neat upgrade path into Workday Data Cloud. And no prepurchase of Prism necessary for Workday Data Cloud. That's great. Thanks a lot, Krupa. And with that, I think we come to the end of this session. The presentation is concluded. Thanks a lot for joining us today. We look forward to seeing all of you at DEFCON. Thank you. Have a wonderful rest of the day.