In a previous article, we discussed the new enterprise data architecture spreading like wildfire among the data community — Data Mesh architecture. We mentioned that it presents a paradigm shift in data architecture that sees the data industry follow suit by moving away from massive data teams prioritising centralised, monolithic data lakes and databases, to one that prioritises data domains and data products as first-class citizens.
In a nutshell, it presents a convergence of distributed domain-driven architecture, self-serve platform design, and product thinking with data. To better understand the concept, we talked to Daniel Tidström, Partner & Management Consultant at Data Edge, who has been working with Data Mesh in parts at least for quite some time.
Daniel explained that Data Mesh becomes crucial when a company scales quickly. “With the proliferation of data sources and data consumers, having one central team to manage and own data ingestion, data transformation and serving data to all potential stakeholders will inevitably lead to scaling issues. “Given the increasing importance of data in our organisations, designing for scalable teams and scalable platforms is really crucial,” explained Daniel.
An important thing that he mentioned about Data Mesh is starting to discuss the distribution of data because data creation is inherently distributed in all companies.” With the number of data sources growing every day, many organisations should probably at least consider what their options for scaling are.
For companies wondering whether Data Mesh is a good fit for them, Daniel suggested that if you have domain-driven development, started working with Microservices, or if you do a cloud migration, that’s a good time to consider it.
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