Data Mesh in AWS
While data lake is a popular concept, it has its issues. While putting data in one place creates a single source of truth, it means you are also creating a single source of failure, which violet standard architecture principles to build high availability. The other problem is the data lake maintained by a centralized team of data engineers who may need more domain knowledge to clean data, resulting in back-and-forth communication with business users. Over time your data lake can become a data swamp.
The ultimate target of collecting data is to get business insight and retain business domain context while processing that data. What is the solution? That's where data mesh comes into the picture. With data mesh, you can treat data as a product where the business team owns the data, and they expose it as a product that can be consumed by various other teams who need it in their account. It solves the problem of maintaining domain knowledge while providing the required...
