In the age of Big Data, businesses are collecting mountains of information about their customers that, when organized effectively, offers the potential to deliver important and actionable buyer insights. To do this, many organizations store information in data warehouses, or more recently, data lakes in big data environment. However, with customer databases collecting hefty streams of data on a daily basis, wading through and determining what information is useful or relevant for a specific business division or decision can become a very daunting task.
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.
Great article on the value of the graph.
