Informatica in a Modern Data Platform

Watch the KPMG session from Informatica World 2022

Joseph Updegrove

Joseph Updegrove

Principal, Lighthouse, KPMG LLP

+1 212-954-3013

Danielle Beringer

Danielle Beringer

Advisory Managing Director, Lighthouse, KPMG US

+1 615-244-1602

Transcript

Danielle Beringer: Welcome, everybody. We're really excited to be here at Informatica World, presenting Informatica in a Modern Data Platform. My name is Danielle Beringer. I'm a managing director in The Lighthouse organization, on the engineering team.

Joseph Updegrove: And hi everyone, I'm Joe Updegrove. I lead our data platforms practice here at KPMG. I've been working with Informatica for many, many years. I'm super excited to be here today in Vegas, and am looking forward to the discussion.

Danielle Beringer. : One of the topics we want to talk about today is data maturity and accessibility. Our data management spectrum shows the span of control and maturity for emergent baseline in more modern data management capabilities.

The base of all of our clients' needs start with a north star for their data strategy. In this spectrum you'll see some key activities and capabilities, that today we'll talk about how we empower our clients through the Informatica platform offering and our partnership with them.

The tiles on the bottom are key activities that we recommend for customers who are seeking to mature their data literacy, data management, and data accessibility for the enterprise. These tiles are the cornerstone for how we move forward with our clients and empower them to use cloud native technologies, APIs, and have better data accessibility in a trusted data ecosystem.

Joseph Updegrove : So how do we bring all of these capabilities that Danielle was just talking about together to really enable the organization? Right? And in our view, it's really via these personas and these use cases. And for the personas, it's both at the exec level and at the operational level.

And so if we start with maybe on the right hand side of this slide, you'll see a bunch of really big data topics, right? So application modernization, data monetization, data governance. These are things that don't just take a couple hours, a couple days, a couple weeks to solve for. These are big data topics that oftentimes live in perpetuity kind of throughout the organization.

And so obviously these topics are on the mind of your tech and data leaders, but it's also more and more so on the mind of the business leaders. So how do we actually achieve some of things?

When you look at then on the left hand side, you look at some of the more operational sort of personas. Some of the key activities then that are required to achieve these really big agenda topics. So data lineage, data governance, master data management, data quality. These are really then those key activities that drive and enable some of these really big topics on the right hand side.

We're actually just performing a data monetization assessment for an organization that we work with, and the number one thing that they identified in order to enable the modernization of their data, was having a foundational enterprise data management program in place. So, really those key topics that I was referring to before.

And what enables all that from a tech- technology perspective? Informatica. Right? The, the IDMC platform that we're all here talking about this week. Those key foundational components across data quality, across master data management, across lineage and metadata management. It's really those foundational components that enable the personas, that then enable the use cases, that ultimately really then can solve some of these big problems like data monetization.

So then, how do we bridge the gap between some of those tech and data personas to the key business personas, and the main objectives of the organization? Well in our view, that's where the Modern Data Platform comes in to play. This is the point where ideation meets innovation. Where business meets technology. Where the business architecture of business processes, people, design... This is where it meets the underlying technology and data architecture to then really enable trusted data accessibility, which Danielle was just referring to.

Discovery of new insights accelerates speed to value. Really starting with, what are those key business use cases? What is really going to bring ROI to the organization? And then working... The business teams working shoulder to shoulder with the tech and data folks to then enable those use cases.

Oftentimes, we recommend to do that in an iterative way, right? So you identify what are the key business intelligent reports? What are the key analytics? What are the key models... AI, machine learning, that need to be built? Work through each of those in more of an iterative way, so that you can then build on top of the platform. And, and you can then enable the other parts of the organization.

So really, all of that enabled via the Modern Data Platform, which we're going to dive into a little bit deeper.

Danielle Beringer : So a few things, before I move into the contents of a Modern Data Platform. We very strongly advocate that any solution, whether it's an extension of a customer's existing environment, whether it's brand new, or whether it's part of a modernization effort, that they really focus on speed to market, higher data quality, greater data utility particularly around AI/ML, and stronger data operations.

So the KPMG Modern Data Platform model is something that we are showing to you today. We're very excited to be launching this in three ways. The first is as a reference architecture for our clients. For anyone who has challenges in their data environment, who is trying to move from the starting point, the starting block of data management, all the way into more modern technology.

The second way is in a client deployed model, using cloud native technologies. And the third is an a KPMG hosted model. But let's talk about the key parts of a Modern Data Platform, regardless of the deployment plane.

The first is context. We work cross-domain with thousands of clients. There is deep business knowledge for data context and the way in which businesses operate. That's an important part of the modern data platform. Common features that serve multiple personas. Very much like you heard in this morning's Informatica key note. All of the personas have to unify around the data. And those are people that are in the lines of business with high data context and knowledge, as well as people in a technology role.

Our accelerators are key items that KPMG has curated over time, through many engagements with our clients. These can be AI/ML accelerators, and a variety of other ones that we'll talk about in just a few moments.

But the core platform is a scalable, cloud native offering, that is highly curated based on the latest and greatest technologies. We are stacking that together for our clients as an offering, after many years of experience and seeing what some of the big trends are in the market, for moving quickly and speed to value for data consumers.

The integrations. Today we're here to be excited at Informatica World to show how Informatica is baked into our platform, as well as some other key partnerships with Snowflake and Databricks.

The accelerator topology that we are showing today, is based on several types of accelerators. Framework, data, functional, and technology. It is a prescriptive approach to supporting data initiatives for our clients. They have varying degrees of maturity, as we discussed in the very first slide. Maybe they're just starting with a data strategy. Perhaps they have a new chief data officer. Or in the best case, they're finally bringing together business and IT, on that bridge of a Modern Data Platform.

These accelerators can hone in on key initiatives, like data governance, data monetization... Particularly around advancing AI and ML, if there is a starting data scientist group or perhaps a new partnership between data engineering and data science, for data value.

Joseph Updegrove : And so also, just to add to some of those accelerators that Danielle was just referring to. So we think about this like cartridge based approach, right, as part of the Modern Data Platform. So we're building assets and accelerators. Things like Citizen 360 for state and local government. Similar to Customer 360, but really in a state and local government organization. We're thinking about Patient 360, and the healthcare industry and sector.

 We're thinking about then Customer 360, building out what are those customer... Or what are those common data models? What are some of the key rules that apply? What are those business validation rules? What are the match merge rules? Helping to develop kind of the foundation, the starting point, the libraries that can support all of those things.

 On kind of the more functional side, also is thinking through, from a functional and an industry perspective, what are the business glossaries? What are the data dictionaries that are required? How do you actually link those terms and those definitions to the technical metadata that will be gathered?

 We've started to develop inventories or libraries of what some of those business glossary terms will look like. And, and actually starting to develop libraries of data quality rules, as well. These are all of that things that we can kind of plug in, plug out, of the Modern Data Platform to support our various different business needs, and the organizations with whom we work.

 In all of this, we at KPMG, we have a client promise, that we will continue to deliver as well. Right, so when you think about all of the services that we offer... Everything that we just spoke about across the Modern Data Platform, how it's enabled by Informatica. Well, we'd bring all of that together via our client promise. We'll deliver results that matter. We'll work with our clients to get things done. We are always on our clients' side. We heard some of the messaging from the Informatica team this morning, around always being on the client and the customers' side. We believe in that exact same model as well.

We know how the organizations that we work with, we know how their businesses work. And we know how to leverage technology. Technologies like Informatica, that enable the Modern Data Platform. And hopefully we'll be a part of that for many years to come. And we'll help then enable those business use cases and the ROI that the, the data dream has been for all of these years. We're finally able to start to achieve it.

Thank you so much for having us here today. We're super excited to be here in Vegas, after a couple years of a break. And we thank Informatica for the time, but also being such an integral part of our Modern Data Platform. Thank you.

Danielle Beringer. : Thank you.

 

Today’s modern data architecture must be built on a scalable, cloud-native data platform. This enables trusted data accessibility, actionable insights and accelerated time to value. The result is an architecture that delivers a common data ecosystem, a seamless development and deployment platform, and an integrative API marketplace for higher data quality and stronger data operations. Watch this video recording of our KPMG session to learn more.