A Data Mesh is an emerging technology and practice used to manage large amounts of data distributed across multiple accounts and platforms. It is a decentralized approach to data management, in which data remains within the business domain (producers), while also making data available to qualified users in different locations (consumers), without moving data from producer accounts. It is a step forward in the adoption of modern data architecture and aims to improve business outcomes. A Data Mesh is a modern architecture made to ingest, transform, access, and manage analytical data at scale.
In this use case learn how a leading financial services company obtained a data platform that is capable of scaling to accommodate the various steps of the data lifecycle along with tracking of all the steps involved including cost allocation, parameter capturing, and the providing of metadata required for integration of the client’s third party services.
How one of the world's largest investment companies is migrating data to AWS using a Lake House. By engaging with AWS and Vertical Relevance, the Customer was able to decide which incremental “Waved” approach is best aligned with their needs. The Customer now has a plan for completion of successful migration to the next best Lake House AWS architecture state as well as managing risks while delivering business value at each increment.