Breaking Down Data Silos: Data Mesh to Achieve Effective Aggregation in Data Localization

Data localization laws are becoming more common, which makes it hard for companies to manage and combine data that is spread out in different parts of the world. This is especially hard because data is scattered and there are limits on how data can be sent across borders. Data Mesh, a new way of thinking about data architecture, offers a solution to this problem by offering a decentralized way of managing data that can make it easier to put together data in a local context. In this paper, we discuss the problems that organizations face when trying to manage data localization with respect to the data regulations in different regions, the problems with traditional approaches to data management, and the benefits of using a data mesh architecture to gather data. We also discuss a region-based unified data mesh architecture that was made with data localization in mind, pointing out its most important parts and benefits. Our proposed unified data mesh abstraction model can help organizations to deal with the problems caused by data localization and use their data assets to make better decisions and get better insights.