Do your source systems contain duplicate data? Are the business begging you to merge together multiple, disparate sources to provide a single view of entities such as products and customers? Are you struggling to meet these requirements using PaaS services in Azure? If so, then this session is for you.

In this session we will explore master data management and the benefits it can bring to your organisation. We'll explore what master data management is, understand the different types / levels of maturity that can be adopted and then dive into a real-world example to understand how we can utilise PaaS services in Azure to build a matching engine that can match and master large amounts of data in a scalable and future-proof manner. Finally, we'll explore how you can serve mastered data to other applications within the organisation and provide business users with a method to amend and enrich mastered data.

This session is based on learnings from real-world master data management projects and will explore how we can adopt an iterative approach to master data management, using Azure Databricks with ready-built open source implementations of matching algorithms to enrich our matching engine and ensure we get the highest possible match rate.

No specific prior knowledge is required to attend this session however, some understanding of Azure services such as Databricks is useful.