Key Components of a Modern MDM Platform
- DATAMASTERS on Demand
- Key Components of a Modern MDM Platform
Master data management is evolving. Machine learning is replacing rules, reducing manual efforts to clean and curate data. And the cloud is allowing businesses the flexibility to scale their workloads. Blackstone will share how these technologies help the firm redefine its approach to MDM and provide it with complete records that deliver business value.
Speaker 1: Data Masters Summit 2021 presented to you by Tamr.
Jenn McAuliffe: Hi, everyone. Thanks very much for joining us for this session today. I’m Jenn McAuliffe, Head of New Business for Tamr. I’m coming to you from New York City today with Tom Pologruto from Blackstone. Tom is the firm’s Chief Data Architect, and Blackstone is the world’s largest alternative asset manager. Blackstone’s assets under management include private equity, real estate, credit, and much more. As the firm’s Chief Data Architect, Tom is responsible for helping Blackstone adopt a modern approach to master data management. Today, he’s going to share with us why the firm has changed how it’s handled master data management and how its new approach generates clean, unified data that drives analytics. Thanks for being here today, Tom.
Ton Pologruto: It’s my pleasure to be here.
Jenn McAuliffe: So tell us a little bit about your role and what challenges you face with your data?
Ton Pologruto: Absolutely. So I’m part of Blackstone’s Technology and Innovation Group, or BXTI, we look after technology, data across the entire enterprise of Blackstone. So in the role that was created last year, I wanted to take a deep look at our largest asset, which is our datasets and the data that we use to drive the entire firm, and that led me into really taking a new approach to master data management.
Jenn McAuliffe: Great. And what challenges do you face with any operational or analytical issues?
Ton Pologruto: As the name MDM implies, master data management is at the core of everything that we do. So whether it’s an operational task or a reporting task or any analytics that we’re running, having good, high quality master data managed datasets is absolutely integral to accurate analytics, accurate reporting, and accurate operations of our firm. So, in that sense, it is the most valuable dataset that we have and we have to treat it as such, and a large part of what I’ve done as Chief Data Architect working with everybody across BXTI and Blackstone is making that a true statement, really putting the time and the effort and the partnerships in place to allow us to take our MDM and our datasets that derive from MDM as the firm’s premier dataset.
Jenn McAuliffe: Great. And how did you previously handle MDM and why the need for the change given the strategy?
Ton Pologruto: MDM has always been at Blackstone by definition. As a core dataset, everything derives from that particular piece of data. As part of a broader initiative to get all of our data from all these desperate systems in the firm into a centralized data warehouse, hence making all of our data more available for every use case, the quality of the data was the biggest obstacle. Most of the time, data was derived from an internal system, for example, our MDM system, and then it was cleaned manually for every single use case in the firm, typically in a spreadsheet. So that approach has been effective for many years, but as the size and the scale and the breadth of the analytics that we want to run, having that be centralized and all of that logic out of spreadsheets and one-off into our data warehouse was absolutely a critical requirement to doing anything beyond that. So, in that sense, the strategy for digital, the strategy for data transformation, the strategy for automation, that all hinges upon us getting our MDM datasets correct.
Jenn McAuliffe: Got it. And with machine learning and cloud underpinning the digital strategy, how did that all play into your master data management strategy?
Ton Pologruto: We’ve been on a cloud migration journey for the last two years and in that sense the data world has really always been cloud first. So the machine learning aspect really came into play because we needed to replicate a lot of logic that actually existed in human beings’ brains and that logic was much deeper than any previous technique that we could do. We couldn’t simply do some simple manipulations with strings or some other one-off mappings and map every entity within the firm. It was just too large of a dataset. So the right tool for the job was to use a machine learning based tool that a human being could supervise and the machine learning tool could then work in concert with that human being to create a very efficient way to get our data properly managed and organized.
Jenn McAuliffe: Okay. Your first Tamr use case was entity data. How did you decide what entities to start with? How did you prioritize those things? How do you think about the prioritization of your entities when you’re looking at master data management?
Ton Pologruto: The approach we took was to start with the combination of the most important datasets and the datasets that we felt most comfortable we could know were better once we had done and used Tamr for the cleaning of the data. So legal entities became a primary focus for us. Legal entities are verifiable externally. We had a great target and we could collaborate with law firms with our finance teams and with our deal teams to make sure that we were actually targeting a better state of the world than the one we started from. And just because of my background in science, that scientific method driven approach of asking questions and determining outputs and measuring all along the way was something that Tamr made very easy for us. So it went from legal entities, that was definitely the number one use case and the biggest value to the firm, but then we really started to branch out from there into the full suite of all of our master data management datasets. And as the relationship has grown, we got better at using the tools, it’s really been a fantastic partnership for us.
Jenn McAuliffe: Great, great. And with all of these projects that impact the bottom line, who benefits from the data the most, do you think?
Ton Pologruto: Our investors, ultimately, and that’s a key part, is everything that we do at Blackstone is for the benefit of our investors, the people that trust us to be chaperones of that capital and make great investments. Across the teams, we see a lot of the operational teams and our deal teams, our technology teams, everybody having a go-to place for accurate data. It can’t be overemphasized how important that is in implementing any sort of digital transformation strategy, and it all starts with your master data management datasets.
Jenn McAuliffe: Great. And you got started the Tamr pretty quickly. You implemented pretty quickly. You guys have seen value fairly quickly. What would be your recommendation to other customers or other prospects that are thinking about Tamr with how to get started?
Ton Pologruto: You have to pick the right question and the right question that you want to answer is exactly almost what I just said before. Pick something that’s well-defined, adds value to your business, and don’t try to eat the whole elephant at once. You have to break the problem down into smaller pieces, solve each of those pieces, learn how to use the tool. That’s really the key part with Tamr. We took the effort on our side. I had some wonderful people on my team who spent a lot of time working with the Tamr engineers and data scientists as well as our Data Science Team. Everybody collaborated together to understand how this tool could be most effective inside of Blackstone.
The result of that was not only accomplishing our initial goals, but giving us ideas for new goals, more ambitious goals and better uses of the tool. So, for anyone out there who’s looking to do this, it can’t be a side project. You really have to put the time and the effort and the focus into it. And these are partnerships. The partnership with Tamr has been absolutely fantastic and we’re looking to grow that partnership over time because the use cases just never stop.
Jenn McAuliffe: Great. Thank you so much for your time and your insight today, Tom. We really appreciate it.
Ton Pologruto: Fantastic to be here.