Name: AWS & Workday: Data into Action with Zero-Copy and Agents
Uploaded: 2026-09-17T17:30:52.368Z
Duration: 59 min 16 s
Description: AWS & Workday: Data into Action with Zero-Copy and Agents

Transcript for "AWS & Workday: Data into Action with Zero-Copy and Agents": Hello, everyone, and welcome. Thank you for joining us today agents webinar. We're excited to have you here morning. Very quickly, before we get started, just make sure you read the product statement before signing any any agreements versus, it's posted speakers today. We have Archana Bansal, senior manager of product at Workday, who will introduce our Workday data cloud offerings and discuss a a bit about the Workday data cloud ecosystem. We also have Poornima Chand from a principal solutions architect from Amazon Web Services, and she'll be talking to cloud and Amazon Web Services provide value for customers. And excited to have Alex Mednick, principal account executive at Amazon Web Services with us, who will share about the Amazon Web Services and Workday partnership. And by way of introduction, my name is Brian Marable. I'm a principal product marketing manager here at Workday, and I'll help guide us through today's conversation, connect the dots across the business value, demos, next steps, and and q and a. And wanted to just call out that in your dashboard here, in the webinar, you'll see a chat and a q and a function. Please please use those throughout the webinar. We we will try to answer them in real time for you, but if we don't get to those, we're gonna have an interactive fireside chat style q and a, with our speakers. So we wanna make sure to cover, all all those questions and and get to those. So what are we gonna cover today? Well, we're gonna talk just quickly about the overview of Amazon Web Services and Workday data cloud. We're gonna dive into some of the technical capabilities and the business values you can get from those. We're gonna show you with some demos how it works both in Workday and in AWS, and then we'll have that q and a. So I wanna welcome, Alex up to talk a bit about the Workday and AWS partnership, the value. We're really excited to have Alex and AWS here with us today. So, yeah, Alex, if you don't mind kinda taking it away. Yeah. Absolutely. Thanks so much, Brian, and thank you all for being here with us today. AWS and Workday have a long standing partnership. Over fifteen years of partnering together to deliver results and delight our customers. And just a few of the highlights that I'll point out to you folks is the global availability and deployments for Workday on AWS. See across multiple countries and regions, US, Canada, Germany, all all across Europe, Japan, and Singapore, Australia, and India, Workday is available on AWS globally, and we're so proud of those global deployments. We partner to innovate, to co innovate together, and to bring new solutions together in the world of AI to delight our customers. We're gonna be talking about data cloud today, but also our partnership around agentic AI and agentic interoperability and bringing the agents together you build in AWS with the great agents in Workday to deliver more value for your businesses. The ability to use AWS services within Workday build for Workday customers to build more robust Workday applications. And for those partners that are on the webinar today, we are a founding partner of the built on Workday program, and maybe you've attended one of our hackathons and workshops at an AWS office to help partners create their built on Workday applications for Workday's customers. Workday is available on the AWS marketplace. We're super proud of that and the value it brings to our joint customers and transactable in a variety of global currencies. And the value that brings to our customers being able to drive down on AWS spend commitments, speed up their procurement processes, and purchasing Workday on the AWS Marketplace. And for those of you folks that will be at Workday Rising, and I certainly hope it is all of you, Give you a second here to make sure you grab that QR code, and if you have colleagues or friends at other organizations that use Workday and are gonna be at Rising, share that QR code with them. That is a link to our public facing site that's gonna talk about all the things that AWS is doing at Workday Rising this year and the ability to book meetings with members of our team to talk more about data cloud, AI, migrations, the marketplace. Whatever is important to you in the world of AWS and Workday, we'll be there on-site and look forward to meeting with you. So I'll just give you one more second on the QR code. And the last thing I'll cover here is many of you folks have heard about Workday migrating customer tenants to the public cloud and benefit and the benefits of migrating your Workday tenants to AWS. And just walking through the highlights here, that near zero downtime, user experience, and regional maintenance windows, nobody likes downtime. And when you migrate your Workday tenant to AWS, you reduce from those 52 downtime events a year down to four, giving you that near zero downtime user experience and those regional maintenance windows. Being able to host your Workday tenant in one of those AWS global regions allows you to have a maintenance window aligned with the time zone that you and your employees are based in and also abide by those data residency laws and have reduced latency by having your Workday tenant closer to where you do business. And the last piece here is that AWS is the only cloud that you are able to run Workday on that is FedRAMP, moderate authority to operate. For so for all my friends in the public sector that need that FedRAMP authority to operate certification, running your Workday tenant on AWS is the move for you. And, also, we're super proud that Workday is a launch partner, with the European sovereign cloud. And that that's we have more information coming out this year and a webinar next month around the ability to run Workday on AWS's European sovereign cloud. And with that, I'm gonna pass it over to Archana to dive in to more on the data cloud. Thank you, Alex. I'm gonna just get situated, share my screen. Alright, everyone. I'm Archana Bansal, and I'm very excited to share all about Workday Data Cloud with you all. So when we speak, with the IT teams, there are three consistent themes that emerge. The first, and which is apt in the latest AI emergences, I need to safely adopt AI. Everyone has a mandate. There is immense pressure to deploy AI, but it has to be done safely. The concern I hear most often is governance. How do I adopt AI without exposing my enterprise to risk? The second theme is I need to bring my data together but with context. The data is fragmented across lakes, warehouses, legacy apps. The challenge isn't just access. Data needs to come together with context to make it more meaningful. And the third one is I need to simplify my tech stack. All the engineers would resonate here. Legacy architectures are creating operational friction. The goal is to free the IT teams from managing the technical debt so they can partner with the business on innovation. The role of the IT teams has evolved from managing rigid technology stacks to architecting agility. The pressures are real. Hi, folks. Just given us a few seconds here while, we we lost Archana and Archana. There she is. Awesome. Alright. Am I back? I'm sorry. The pressures are real. What's important is how Workday is responding to this shift. Workday Data Cloud is a fundamental evolution in the Workday platform. It's about taking your most trusted people and money data in the enterprise and making it safely usable beyond just a core system. On the right, on the slide, you see Workday Data Cloud playing a key role. From there, trusted Workday Data connects seamlessly to the existing data ecosystem, analytics platforms, data lakes, and external BI tools. This isn't about pulling data out and losing control. It's about connecting Workday into the enterprise in a governed, intentional way. Here's a high level view of all of the components and the partners we support today in Workday Data Cloud. This new product suite is built on a zero copy architecture that connects Workday with your modern data stack. This makes your Workday data securely accessible for AI and analytics with zero data application. Our current list of trusted partners is AWS, Databricks, Google Cloud, Salesforce, and Snowflake. And with the zero copy architecture, the dotted lines that you're seeing there flowing back and forth between Workday and data platforms, you will be able to query not just Workday data, but external data that you can read inside Workday Data Cloud from these partner platforms as well. All your most important data will be connected inside of Workday and outside of Workday. Today, we are focused on AWS, and we are privileged to have the rest of the AWS team to also support us in this webinar. They'll talk more about the use cases and go into details of that later. So what does this do for you? It gives you reduced risk, meaning no copying of the data. There is lower integration complexity, no custom integrations and ongoing maintenance. There is a faster time to value, which is short apart from data to decisions. And lastly, the greater value from your existing investments. You've already invest invested in these data platforms and BI tools. You use the tools that you have invested in, and we could come meet you there. At the end of the day, this is about contextualized data connected across the enterprise. So let's look under the hood. How are we delivering all this? We're going to start with this complex smart architecture diagram that we have. Here's a detailed architecture showing all of the different components that come together to make Workday Data Cloud a reality. So from left, this includes the data platforms that we talked about, including AWS, that support open formats for Workday to be able to establish zero copy connections to data in these platforms. These links to tables from AWS then become just like any other table in our Workday Data Cloud product, except there was absolutely no need to do an ETL to get it in Workday. From then on, you can join that data in Workday within the with the Workday data that's already available available there and do all the analysis you want. We're gonna see some demos and examples of this in the in the webinar today. So let's move from left to the center. In the middle, you see components like core Workday data, which is nothing but all of the core products, Workday products that you are used to, workforce management, payroll, talent, financial spend, etcetera. On top of that, we have unified data catalog, which is a carefully curated list of objects from the core products that we serve in a catalog for our customers to use. And just like we were able to establish connections to the AWS data inside Workday, the reverse would be possible using Workday catalog in AWS. That completes the picture of bidirectional zero copy federation that we are offering in the product Workday Data Cloud. I'm sure you have thousands of questions, and we will take them later, but let's double click on each of these components just to understand them better. I'm gonna start with Workday Data Lake. In the data lake, you will find curated tables of the most critical people and money data that we talked about earlier. You can think worker, journal, procurement tables, invoice payments, you name it, everything is gonna be there. And these are already structured, governed, and ready to be queried. That data is stored in your public cloud as files. So these are Amazon S3 or GCS, wherever your public tenant is. And then they are exposed via Apache Iceberg tables. Apache Iceberg is a groundbreaking technology. If you haven't read, please go and read. It's it's very interesting. 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 partner platforms. Iceberg allows for queries quickly and consistently pinpoint the exact data that you need before you do 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 going to 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, that you choose as a configuration that we provide to you. We do all of the work upfront on behalf of all our customers to make sure those tables of data are structured, governed, and ready to be queried directly. And that will be configurable by each customer. You can pick a day, pick a refresh cadence that you like. You can even pick the tables you wanna materialize in the data lake. You don't have to materialize everything. And with that, we will refresh the data for you. For this is perfect for exploratory AI and analytics, and that's the way to go. The second, let me do a demo of AWS, integration and Workday integration for Lake. Here's a video that shows how this works. So we go in Amazon SageMaker. And from here, I'm gonna just open SageMaker Unified Studio. Inside Studio, I'm going to look to establish a connection, so I'll go into connections and create one. So you notice two tabs, two tiles for Workday, but I'm going to go to Data Connect, which is the data lake connection. I'll provide the different connection properties that I have to give to make this connection trusted between Workday and AWS. And once I've created it, I can test the connection. And voila. With this, I'm now able to see all of the different catalog tables that Workday has to offer. See here, I'm going into a catalog that was established with the zero copy connector connection that I just created. And I have all the tables at my disposable disposal to start working. I already have a Python script created, so I'm going to start showing what is possible with this connection now. So go ahead. Pierre, I'm just establishing the catalog to show. This is where I'm seeing, hey, can you tell me what are the different tables that have skills and worker data? So even if you don't know the tables, you're able to explore the catalog this way. And once I know which tables that I have to use, I can then start exploring that data inside this notebook. See here, I'm seeing the tables I should be looking at. I want to explore the skills data, so I run that script. And it tells me all the employees with the skills that they have. So I have these available skills that I can use, and then I move on to a upcoming project data that I have in AWS with the project names and the required skills, that I need for those projects. I can now join the data in Workday from Workday, which I haven't ETL'd with this AWS data, and come up with the skill match for the projects. And I can go further and say if my resource allocation is appropriate or not by looking at their project allocation today, and the new project allocation that I'm proposing. So what we saw here is we saw zero copy access of Workday data via Apache Iceberg REST APIs, and you could join across AWS and Workday data. You could do further analysis, on that data and come up with a plan for what you want to do. Let's move on to the next component. This is Workday Live Data Query. This is slightly different from the data lake portion that we talked about just now. This is real time access to your people and money data via SQL. So data lake is perfect, materialized, performance, great. But for some use cases, data that's a day old or several hours old, it's not going to cut it. And that's where another data cloud product really shines. Workday Live Data Query is a is just like a SQL interface. It sounds complicated, but it's not. It's just SQL. For our customers, though, it's going to be a revelation. SQL is the language of analytics. SQL is the language for agents, and we are moving towards agents, all of us. And for the very first time, we're going to 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's a must for Workday customers. So 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 and textual security on a per user basis, this is your fast lane. And how do we achieve this? We we provide JDBC and Python drivers, and we're working on more drivers, which are also open standards. And what that means is you plug in the driver into your BI tool of choice. Maybe you use a Tableau, Power BI, you use it within, AWS to establish that live connection as well. And and and well, your your same catalog that we saw before is available here for live data query. There are no clunky pipelines. This honors contextual security, just reiterating that down to the user level. So if I'm running, if Archana runs a query inside Workday and Archana runs a query externally, I see the same data. That's what live data query brings to you. So let's do a demo for LiveDataQuery inside AWS again. Same thing. I'm going to go to SageMaker Unified Studio and hit the other child that you saw earlier on live data query. Say create connection. I'm gonna choose live data query this time. And just like the other connection here, I provide the JDBC URL and the different parameters that are needed for establishing a live connection with Workday catalog. And I can test this connection. And same thing, I have a notebook ready where I have used the same connection and using the catalog that this live query connection exposes to me, and I'll be able to write queries on top of that data. See here, I'm querying a procurement supplier table, and that brings back the results to me. And it gives you the same power. You can join this downstream if you want to, but it really brings the live data to you directly without any ETL again. So, really, there are two paths you can access the catalog. And one distinction which is important is in the data lake path, you get to choose what you want to put in the lake versus in the live data query path. The whole catalog is available to you. All right. I'm going to talk about the third big component, which is Prism Data Management. And it's an important part of our Workday Data Cloud product. Prism Data Management has been a product which is existing, and it brings all of this power of ingesting the data, transforming the data, and then massaging the data to make it more available for analysis, that whole, functionality is weaved into Workday Data Cloud. So once you've established zero copy connections to your external AWS data, using Iceberg, you can then do build some pipelines within Workday and use that for downstream analysis, either in a report or a dashboard board or even an agent within Workday. So let's look at this connection inside Workday and how that works. Here I'm in the Workday data cloud product in the data catalog. I have the AWS tile, which I select, and then I'm gonna provide the connection details, which basically establishes the connection to AWS using their catalog URL and the different things. Once I have that connection ready, I can test the connection. And with the connection established, I can then create external catalog by providing the different details. So this is the namespace that is present in the AWS Glue catalog that I use here to establish that connection, to establish the catalog connection directly. And once I have this, I can then, save it, which then triggers a schema sync, which means it brings me all the iceberg tables that are available in the AWS Glue catalog. In here, I'm seeing employee stock pay information table that has come here. I can then use this table to build a pipeline inside Workday, data prep tool that we talked about. So I'm here combining the total compensation data with the stock pay info data and bringing a complete compensation picture for my employees because my stock information is sitting externally. Next, I can then use this prepared, dataset to build a report, and the report shows me a full compensation detail. And with the core reporting agent that is embedded inside the report, I can ask it simple questions, exploratory questions about this data that is actually a a combination of the Workday data and AWS data without the need of doing a single ETL, a single refresh, no IT tickets to get to this point. That's the power of Workday Data Cloud integration with AWS. Alright. I do wanna talk about the knowledge layer really quickly, before I give it to Poornima to take it over on the AWS side. So once we have all this data and the connections established and lined up, we don't want the agents inferring that context from raw data alone. That's generally probabilistic. Workday Data Cloud's content context and knowledge layer will encode relationships between people, money, orgs, roles, skills, and more. When I said at the beginning that word data models exact models exactly how your organizations run, this is exactly what I want what I was talking about. The semantic layer or the knowledge layer will be a series of purpose built models that provides the ground truth, the meaning behind all of your data based on about two decades of business logic baked into Workday. The business logic you trust to manage your most important assets, which is your people and money. That's the context you quite literally can't find anywhere else. So here's a quick demo of an agent that I've built using, again, Workday data along with the AWS data just to show you the power of, the developer agent, which is part of our extend product. So I'm in developer agent here. I'm gonna give a prompt to this to build a sales performance agent by bringing, data from commissions data from AWS and workday data, worker data from workday. I'm giving it some example questions of what I want to do with that agent. I want to identify my top sales performers. I want the sales skills for top performance and so on. So once I give it the prompt, it's gonna build the agent for me, without having to write any code, any APIs, or anything. So this is my agent, which is built in the developer agent. I can then deploy it to my Workday tenant. And when I'm once I'm inside the Workday tenant, I can then go and interact with the sales performance agent. And I'm showing a very, example interaction with this agent today. What I'm asking is, hey. Which sales reps have low CSAT and low commission attainment in in this quarter? So I'm I'm a sales rep manager, and I'm I'm interested in knowing what's going on here. So it comes back with three employees. Pedro, Jacqueline, and Betty have a low CSAT and attainment rate. So I'm curious, and I ask, show me their completed workday learning modules and recommend what they should do next. And, well, with the with the data that is complete with the external data and workday data, I can now see the recommended learnings as well as the completed learnings. And from within the agent itself, I can assign these learnings to Pedro, Jacqueline, and Betty. That's, again, a lot of products coming together to make it work. There is Workday Data Cloud that's bringing the data together between AWS and Workday. There is developer agent, which is letting you create, an agent really quickly. And then all of that is happening behind the scenes with no ETL, no pipelines, no maintenance, and no, IT tickets to get this done. So that's that's that's Workday Data Cloud. I'm gonna hand it over to my friend, Poornima, from AWS to go deeper on the AWS side. Thank you, Archana. Hello, everyone. I'm Poornima Chand. I'm a principal solutions architect at AWS. And I have had the privilege of doing a lot of innovative, work with Workday over the years, and I have to say this one is extra special because this is a feature that you all have been asking us for a while, and I'm really excited to talk to you about it. So continuing from, where Archana left off, I'll go dive deeper into the AWS side of these integrations. To do that, let me first quickly walk you through the AWS analytics and AI services that are most relevant to this integration. So going from the bottom of the stack, you have at the foundation, you have s three, which is where you have your data lakes and the iceberg tables. And above that, you have your analytics and machine learning engines that consume this data. And some examples include SageMaker, EMR, Athena. Then you also have, catalog and governance layer, that is provided through Glue Data Catalog and SageMaker, SageMaker, sorry, Lake Formation. Then there is a data connector layer that lives in SageMaker Unified Studio and AWS Glue. Then you also have your agents. There are two key services that I want you to focus on when it comes to this integration and that is AWS and AWS Bedrock Agent Go. This is where your agents, live and run depending on your specific business requirements. Now the point that I want you to take away from this slide is that this is not a single tool or a single service. It is a complete start that spans across storage, governance, analytics, AI on all of it working together. Now this is the slide that, shows how the two worlds come together. On the Workday side, you have Workday Data Cloud holding, your HR and finance data. And Archana already talked about, what are the key components on the Workday Data Cloud, site. You also have Workday, which is Workday's, AI and agent layer. Similarly, on the AWS side, you have your Iceberg tables, your analytics engines, you have the governance layer, and you also have your AI and the agent layer in AWS and Bedrock agent core. Now let's talk about how Workday and AWS connects. So with this integration from AWS, you can query about the data, from AWS analytics engines, and you have the option of, either using a live data query connection or using a Workday data connect, connection to access your iceberg data in Workday. Similarly, from Workday, you can query, your s three I Iceberg data lake sitting in your own AWS accounts. To get started, you first set up the connection in SageMaker Unified Studio like how Archana showed it in the demo, and you get to fully manage built in connectors in SageMaker Unified Studio that you can easily configure, from, the console and get connected back to Workday, your Workday data Cloud environment. And from there on, then you can query the data from your different AWS analytics engines. And Archana touched on this earlier, but how you think about the two connectors is if you need, real time live data access to your birthday data and are looking for simple, low volume queries, that's when you use the live data query connector. And this is ideal for, let's say, dashboards and agents, things like that. Now if your requirement is to run large analytical queries, that's when you would use the Workday Data Connect connector and to access your, iceberg data in Workday. Similarly, in the other direction, you can query your data in S3 data lake from Workday. Together, this gives you one continuous governed data fabric that spans across both these systems. This is the foundation that enables you to then unlock your data and AI innovation at scale. Now, Archana showed you how to connect AWS and Workday and realize some of the analytics use cases that this integration enables you to do. Now let me walk you through a few out of the possible scenarios that this integration would enable for you. Let me switch my screen share. Okay. So this is AWS kit. This is an AI assistant that I run right on my desktop. Think of it like a teammate that I have who can actually do the work. It's more than a chatbot. It can read my files, search my Slack and my e mail, pull up data, and also take actions against the different tools I use on a day to day basis. The good thing is that it does all this from a single place, so I'm not jumping between a dozen tabs to get, to do what I need to do. Also another powerful capability is that over time it learns my context, so it gets better at understanding what I'm actually asking it for just like my colleague. Today, I'm going to show you what happens when I connect to Workday and then have it work across Workday, AWS, and Salesforce together. How do I bring Workday into this? Technically, there are different options. Today I'm going to use an MCP connected to Workday Data Cloud. MCP stands for Model Context Protocol. This is an open standard that allows AI agents to connect to external tools and data so they can be better informed as well as, they can take actions with external systems. As you can see, I already have a few connections set up. I have connection to my builder tools, Slack, and Salesforce. Now to add Workday, I click on Create and add an MCP server. I will fill in Workday MCP details and click Add MCP to add that connector. As you can see, the connector is created. Now, let me go back to my chat window and I'll start with a very simple use case. In this case, I just need some answers straight from my HR data. I'm an HR leader who just wants to know where things stand. I can ask that to click instead of having someone create a report for me. First I typed in ports are attrition rate. This script finds us, and queries Workday to get back with an answer from Workday. I can always ask a follow-up question. How many open requests do we have? And same thing, it will go and get the data from Workday. This is live people data flowing from Workday Data Cloud into an AWS agent. Now let's move on to a slightly harder question. This is something that would normally take two teams and a spreadsheet. I'm looking to start a new project and I want to know how best I can do that. So in this case, the skills data leaves in Workday and the project pipeline data, is in my AWS data lake. And usually I have to join them manually. Let's see how QUIC does it in one step. For that, I ask this question to QUIC, how do I staff my new project? In this scenario, it will go connect to, Workday and then also pull the data from AWS. Then this is an agent that resents over the data in Workday and AWS together in one single flow to give you an answer. Now, let's move on to the third scenario. In this, we will connect people data with, revenue data in Salesforce. So this is a use case where, where that is related to onboarding a new sales hire. So I'm as a head of sales, I want to know if, my new hire is ready to sell and what is happening to their pipeline. So again, I can ask click that question. Give me the onboarding readiness check for my new account executive, Jordan. In this case, click pull start data, Jordan's onboarding status from Workday and shows his onboarding progress. From Salesforce, it will bring the pipeline data and then it gives me a good picture of where things stand as of today. Now, as their manager, I can also take actions to adjust the pipeline if I need to. Everything that you just saw, shows you how open platforms allow you to get the best out of your data and technology investments and enable you to accelerate your innovation. This really makes your AI agent smarter and more reliable by grounding them on a trusted and open data foundation, which in this case what they provide. So with that, I will hand it over to Bryan to to talk us through some some of the next steps. Thank you so much, Poornima. And let me just share back on this. So right now and, I hope I hope this this has drummed up some questions here, so we're gonna get to them in a second. But currently, our available timeline, you know, the road map questions here, We are in early access right now, and we'll provide some links, to that. We expect to be generally available here very quickly, at Workday Rising. And if if you're a customer so you heard a little bit about Alex Mednick talk about the the public and private cloud relationship here with Workday Data Cloud and AWS. So for customers who are already on the public cloud, you can upgrade and you can get started with, Workday Data Cloud. Right now, you can reach out to your account teams. You are primed for that, because public being on the public cloud is is a requirement for Workday Data Cloud. However, let's say you're a customer right now and your, Workday tenants are on the private cloud. No no no worries. Right now, the the Workday Data Cloud provides a a a fast pass to, the public cloud migration. Really, what this process looks like is reach out to your account teams. Your account teams are are very aware that we are we are introducing this to customers across their tech stack, across AWS, and other tech stacks, in their environment. And so the account teams are are ready to to help you walk through that process. So if you're a private cloud if you're on a private cloud customer and and you are saying, hey. Look. This is something we need. Please make sure you let your account team know because they can walk you through that that process, quicker for Workday Data Cloud. And so let's say, like, kinda some quick next steps. We've got some resources right now on our on our Workday Community page that I want you to take a look at. We can provide the links right here for you, and we'll have we'll have those links available in in replays. There's an EA interest form. So please, you know, even though we're GA, you know, expect to be GA shortly, you know, please reach out through that interest form. We'd love to to know that you're interested in getting in EA with us. We'd also, like to be able to to to help you walk through that process. And so that interest form kinda gives a signal to your account teams and to our product teams to to help move forward. And then, like I said, you know, stay tuned because we are gonna be GA. We expect to be GA very soon at Workday Rising. With that, I'm gonna jump into q and a. And so I'm gonna invite, Poornima, Archana, you know, our our speakers onto this you know, we've we've got some questions here. So, let's just let's just hit some some first question out of the out of the gates. You know, one of the questions we we hear a lot is how does identity federation security and governance, how is this happening with zero copy between AWS and Workday data cloud? So, I'll kinda tee that tee that one up for Archana and Poornima, either one of you, if you wanna kind of speak to that quickly. So, I'm gonna answer it generically because, there are two paths that we showed. Of course, the reverse path is you come into Workday, so there's Workday security and identity access, etcetera, that comes into play. Then when you're trying to access the data from external sources, AWS in this case, for live data query, it's gonna be contextual security. We do have, trying to get technical here, the one one myself, but, we do have the ISU, support as well. So if you're using an integration system user, we'll be able to use that for live data query as well, but you'll be able to use your individual accounts. So your your workday account will be able to access live data query product and gain the transactional system data, directly based on what you can see. The the second part, which is a lake path, is a materialized path. So today, we, support it via Apache Polaris, as our being our catalog place. So you're you're gonna be able to put some, you know, access mechanisms there where you can say, oh, these user this user can access these tables and this user can access these tables. So that level of setup can be done and then role based access control then falls down inside AWS where AWS will let you identify which users should access what. Hope that covers, Poornima, but please, chime in. Yeah. So, it is was enabled through an odd integration between, AWS and Workday. And Workday has the the security, configured on Workday side, and you can also have additional, configuration as your AWS administrator can, have additional configuration on AWS side through, like, formation to further get to further securing our access. No. That that that's that's really helpful. I think that's really important for especially, you know, for our customers with but this is Workday data is very sensitive. It's it's critical. So that's that's that's really helpful for diving diving deep into. I think, you know, we have questions around, you know, the MCP hosting model with Workday data cloud and MCPs in general. Again, Poornima and Archana, if you can dive into a a bit of the the MCP process here with Workday Data Cloud and and AWS because that that's something that's very, you know, keen for customers building across across TextX. Yeah. I'll start, and Poornima can complete my answer. Workday Data Cloud will have an MCB server of its own, which will have the different tools. Sample tools could be running a query on LDQ, trying to get the schema details, what are the different tables, like the typical stuff that you would like to do on a tool like LiveDataQuery. The same thing will be will be done for the lake piece as well. So our our grand plan is that, our federated engine can access both the lake tables as well as the transactional tables. That's not something that we're delivering right away, but the lake table access will then also use the same m MCP tools that we plan to give for live data query product. So those tools and server would then be available for external agents or internal agents that you build an extent, product that I showed earlier to build however whatever agents you want, to use the LiveData query or the Workday transactional look up mainly. Now this angles of every agent that is created and is accessing Workday data needs to be registered within Workday through ASR. So all of that will still apply. So if you're building an agent that uses these tools and you wanted to function well, it needs to be registered in ASR, whether it's an external agent or internal agent, which is custom built by you. Hope that helps. Yeah. We have we have we have sort of a deep dive question here. So, thanks for posting this. How does live date how live day how live data query differs from AWS and APIs, WQL currently available in Workday apart from auto applying contextual security. So a a little bit about how is this different than what's already available in Workday. Yeah. It's a great question. It's a question we think about a lot as well, coming up with this product and the overlap that we see very visually. So first off, I'm gonna start with all of these products stay. They will have continued support. So if you have investments in that, that's not going away. You can continue. The big difference are are the the pinpoints that we hear both from AWS or WQL, is they have some guardrails and limitations that that that that force you to build multiple AWS reports to be able to extract data. Now and also the contextual security part that you already asked in the question, which is the difference. The one thing I would say is for everything that you're trying to do with workday data, you just have to think through this whole gamut of products that we have now and think where does it exactly map really well and what will generally keep it low maintenance for you. So if you were using RAS to extract data and do downstream analysis using external data and, you know, transforming it with that data, there is a data lake product that rightly fits there because that data is already materialized. You can establish an iceberg zero copy federation using the integration that we just showed, and that just takes away the ETL aspect of it and maintenance of that ETL. Were you trying to achieve a near real time analytics support externally by extracting the data, where you are as or using WQL? Live data query fits really well in that scenario, and if you were having troubles with that path. So there's overlap. We understand it. There's gonna be continued support of these products. That's also there. But when you're thinking about new use cases or use cases that you wanna maintain and change, you have to think through all of the different offerings that Workday is giving you and and pick the one that fits the best for you. That's really good. I I I think there's you know, I'm gonna tee up this question because I know we've had it from from customers in the past. So I'm gonna share the slide. Alex and Poornima, I. I you know, how are how are your customers thinking about the business value between Workday, Data Cloud, and AWS? And then, you know, some practical what are they doing with this with this data in AWS? You know? What what part of your services can they think about using? And, if you can sort of hit some of those those those high level points, I think it might be really valuable for our our customers and and and and, and folks here on the webinar. Yeah. I I can go first here. You know, so we've been, at Workday Rising and DevCons and Rising to use and Elevates for years. And and one of the most common requests across all of them, hundreds, if not thousands of our joint customers have asked for something similar. Give me the easy button to connect my my AWS world to my Workday world. Like, where is the easy button? We're using RAS reports and it's labor intensive and where where our data strategy is changing with with now bringing in AI. That piece of the business as well. Where's the easy button to bring it all together? Help us move faster and make this all easier for us. And, you know, big kudos to to Workday for recognizing that with their customers and and bringing out the data cloud. And that that's the goal here. Right? That's the business value. We have in more than ever before, need to do more with less faster, and having tools like the data cloud, being able to integrate with what you're doing in AWS as a customer. Your data is there. You're building AI there. And especially to organizations that take security is paramount. It's p zero for both of us. You have that trust as a customer. So we're our customers are have been looking for this forever, and now this is something that will enable them to execute business processes faster, bring that real time data together faster with between Workday and AWS. And then you think about the next step forward in Poornima Chand demonstration as well, the ability to build AI solutions and agents on top of that join data together and then register back into ASR for that agentic interoperability. It's that full circle effect of why Workday and AWS are better together, and we're delivering real value in real time for our customers. Poornima, anything else you'd wanna add? Yeah. Just a a couple of things. Right? So, ultimately, like, Workday is a system of record for HR and finance data And, whether you are doing analytics or agents, all of that you want to, be like you want to use the system of record to for that data that you're using. And a lot of enterprise workflows span our system. So you would want to bring out, like in the demo that I showed you, would we want to bring, Workday data with AWS data, Salesforce, ServiceNow, or whatever systems that you have in your organization. So this really opens up that cross platform workflows for you, whether it it is analytics or AI. This this has been excellent. I think I'm just gonna kinda touch upon these things really quick because, we we we still have some questions questions coming in. So I just wanna say that that that, yes, we will be posting a follow-up link to this webinar where you can access it on demand. That will be available. And, really, it's teeing up teeing up the conversation right now with your account teams. And and on both both ends, you know, if if if you reach out to your AWS account team and say, hey. Look. You know, we have a use case we've been trying to to use Workday data with. We just got off a webinar where we heard about this zero copy, offering. We're we're working very closely. Workday and AWS are working very closely to help help our our customers along this journey. And and but there's, you know, two paths to tee it up with. And I wanna just bring, you know, kinda Archana Bansal, before we kinda close out, are are there some things we need to just kinda make sure we hit with our customers before we close out this webinar today? Yeah. I think two two things, which we didn't touch upon, and are important for the audience to know is we are starting with the HCM data, which is the workforce management talent learning. That's gonna be available, what, this week, early next week. That's that's our plan. And then we are including financials objects soon after. So we're we're probably gonna do weekly drops, but the real timeline that we're targeting is twenty seven r one. We will have financials data, prism data, student data. There was a question on student data and other data. So there's there's gonna be a full catalog available by mostly by twenty seven r one, and then we'll continue to build it up for other products as well that are inside Workday. So that's a big one to know. There's a flex credit question. I would encourage you to talk to your account executive. RAS does impact API flex credits. Workday data cloud is gonna have different skews that you can buy in, and it gives you entitlements to stay within. Those entitlements, you don't pay. But if you go beyond that, then there is flex credit impact. But more details from your account executive, I would highly encourage you to connect with them to understand the pricing better. No. Thank you. Thank you so much. So now that we're kind of hitting the top of the hour, I do just wanna follow back up and say, please grab this QR code. We will be together at Workday Rising, which is, you know, just a few weeks away. We are so excited to bring, you know, Workday data cloud with AWS, for our customers. And thank you so much for for joining us today for all the engaging engaging, questions. Thank you so much. Thank you. Thanks, everybody, and look forward to Workday Rising.