Data quality processes need to move from reactive practices to more proactive frameworks and approaches. This is a key requirement to provide secure and scalable models and analytics driving business growth, in addition to automating processes and generating efficiencies.

 In this session we will:

• Discuss some of the challenges in investing in data quality exercises, and implementing DQ-Ops pipelines
• Discuss some approaches/ideas to assign value to high-quality data, and how to these can enable buy-in and prioritisation 

Join us in this session to discover how your peers in the BFSI sector are monitoring and improving data quality and hygiene at an enterprise level – and especially in readiness for AI use cases and implementation.