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!
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.
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.
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.
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.
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.
