Summary
In this chapter, we explored how to model data formally and intentionally within a data-product-centered architecture. We focused on analyzing how key techniques for physical and conceptual data modeling can be applied within a modular and potentially distributed data management solution.
Initially, we examined how, for data products, data modeling transcends mere development to become an intrinsic part of the product itself. The physical model is the gateway through which consumers interact with the product, accessing and utilizing the exposed data. Conversely, the conceptual model provides the framework for understanding the meaning of that data, enabling proper usage and integration.
We then reviewed the main techniques for physical data modeling, particularly for analytical purposes. For each technique, we assessed the advantages and disadvantages, exploring their applicability within distributed data management architectures. We proposed a two-tier architecture,...
