Business requirements such as the relatively new General Data Protection Regulation (GDPR) in Europe are driving a need to better understand customer data assets and where they reside within the organization. Businesses are collecting mountains of personal data about their customers that, when organized effectively, offers the potential to reduce regulatory and compliance risk.
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 relevant for compliance initiatives such as GDPR can become a very daunting task.
A key approach is to develop an agile single view solution, understanding relevant data assets and their quality and suitability for purpose. Building a bridge between the business and IT sides of the organizations requires a focus on enterprise metadata. Ideally, you have 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. A complete solution based around Graph provides a natural way to model these requirements, and to understand the Enterprise Metadata Graph and its typically complex set of relationships.
In this session you will learn how to:
- Adopt a new approach that develops an agile single view and enterprise metadata management strategy around graph databases.
- Deliver a model that is far quicker to implement and more agile than anything that has gone before, with an eye towards key business drivers like GDPR.