In the age of Big Data, businesses are collecting mountains of information about their customers that, when organized effectively, offers the potential to reduce regulatory and compliance risk. To do this many organizations store information in data warehouses, or more recently, data lakes. However, with customer databases collecting hefty streams of data on a daily basis, wading through and determining what information is useful or relevant for initiatives such as GDPR can become a very daunting task.
A key aspect of delivering Single View solutions involve understanding relevant data assets and their quality and suitability for purpose. Bridging the gap between the business and IT sides of the organization requires a focus on enterprise metadata, with the ability to collaborate on whiteboard style models, maps of existing data assets to these models, and an ability to profile directly against these models to evaluate their relevance. Graph provides a natural way to model these requirements, and to understand the Enterprise Metadata Graph and its’ typically complex set of relationships.
To tackle this challenge, businesses will often deploy Master Data Management (MDM) technologies that aggregate the wealth of incoming transactional data per customer. The goal is to offer a complete perspective of each customer’s relationship with the business, from the first transaction to the most recent. In the past, these MDM solutions were built on traditional relational databases that were able to provide easy views of a defined subset of the information through a trusted data hub.
However, MDM platforms based on relational databases limit what businesses can do – and how quickly they can do it – with the customer data they collect. With more customer information available today than ever before, there are now greater opportunities to leverage this information across the organization. These opportunities require agile MDM platforms that can react to needs across the business, rather than the narrow demands of a single part of the company.
The answer is to adopt a new approach and develop a MDM strategy around Graph databases, instead of relational databases. Compared to a relational database, a graph database offers a more flexible starting point from which to build an MDM program. Graph databases inherently offer individual departments within a business the ability to pull answers from the full range of information available on each customer, as opposed to solely the data sets that are deemed relevant to that specific business unit.
At this years’ GraphConnect event Aaron Wallace, Principal Product Manager, Customer Information Management at Pitney Bowes will be leading the session “The Next Generation for Single View: Moving from the Static Grid to the Virtualized Graph”. This session will focus on how to adopt a new approach and develop a Single View and Enterprise Metadata Management strategy around Graph databases, with an eye towards key business drivers like GDPR, to deliver a model that is far quicker to implement and more agile than anything that has gone before.
Join Aaron’s session - Tuesday October 24, 2017 11:00am - 11:40am - Room 3. Learn more