Today’s organizations understand the importance of modern data architectures, such as data mesh and data fabric; integration processes, such as extract, transform, load (ETL) and extract, load, transform (ELT); and advanced cloud capabilities, such as artificial intelligence (AI) and automation. Without these capabilities, it is virtually impossible for an enterprise to maximize the business value of its greatest asset: its data.

This reality creates a pressing challenge for business and technology leaders: How do you develop a strategy for adopting new cloud-native technologies to deliver trusted and clean data for AI and analytics while simultaneously minimizing migration costs, timelines and risks?