The 5-Minute Interview: Solving Challenges of Master Data Management
Neo4j interviews product manager Aaron Wallace of Pitney Bowes to find out how his group made use of Neo4j to solve an MDM-based challenge. Read on for more information!
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“We knew we couldn’t come to market with the same old solution and be competitive — so we decided to explore a differentiated solution,” said Aaron Wallace, Product Manager at Pitney Bowes.
As a software company prepared to enter the master data management (MDM) market, they found that the space was already crowded with enterprise software vendors. To be competitive, the company knew it had to offer a truly new product — which they were able to do with Neo4j.
In this week’s five-minute interview (conducted at GraphConnect San Francisco) we discuss how Pitney Bowes uses Neo4j to offer an enterprise master data management solution to companies from industries ranging from financial services to retail.
Q: Talk to us about how you use Neo4j at Pitney Bowes.
Aaron Wallace: I work with software solutions in customer information management, where we use Neo4j as a repository within our information management product, Spectrum.
It’s the primary repository for our master data management solution. We surround that with a number of components that make data quality, data integration, and data analytics essentially modular components on the Spectrum platform.
Q: What made you choose to work with Neo4j?
Wallace: As a data quality vendor, we first explored graph databases around six years ago when we made the decision to move into the MDM market. But we quickly found that almost every major enterprise software vendor had an MDM product. We knew we couldn’t come to market with the same old solution and be competitive, so we decided to explore a differentiated solution.
We first explored graphs around some network analysis use cases and checked in with Cisco regarding their implementation. These were in the early days of doing MDM as an internal project, which they were doing using Neo4j. We ultimately chose Neo4j because it’s written in Java (the core to our product architecture), it supports multi-platform asset compliance and it is the market leader.
Q: Can you tell us a little bit more about how your customers benefit from Neo4j?
Wallace: We have a number of customers in different verticals doing some interesting things. At a high level, from an MDM perspective, most of the use cases are driven around improving the effectiveness of marketing, sales or customer support. In all of these cases, companies have a large amount of available data that resides in silos around the organization. And these companies have to figure out a way to bring all the data together in one place.
We currently have financial services companies leveraging our technology to drive results around a fully digitized process on the web and to deal with AML and KYC regulations in the field of anti-money laundering.
We also have retail organizations using Spectrum to more effectively market and cross-sell to their existing customer base. The classic problem is when a person comes into a brick and mortar location, we don’t know much about them — what they prefer, how they prefer to shop, products we might be able to cross-sell or up-sell — things like that. And we’re able to solve these kinds of use cases across a few different verticals.
Q: What are some of the most interesting or surprising results you’ve had while using Neo4j?
Wallace: One of the most exciting things we’re doing is we’ve taken Neo4j and made it the core database for our entire platform. Previously, it was just a component of the MDM piece of the product, but now it’s the actual repository for the entire platform.
This allows us to move in the direction of metadata management as a solution on our platform, as well as to understand the landscape of information and data across an enterprise — which is the key focus for our next version.
Many of the companies we work with are dealing with hundreds of systems that need to be rolled up into single customer views. Understanding things like impact analysis, data lineage, the location of data assets, whether or not data is trustworthy...these will all be pieces of our graph and MDM solution in the next iteration of our product, version 12.
Published at DZone with permission of Bryce Merkl Sasaki, DZone MVB. See the original article here.
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