The Medallion Architecture in Practice: A Framework for Building Scalable and Governed Data Lakehouses on Microsoft Fabric

The present day we see an extensive amount of data produced by what is basically the universal use of digital systems and mobile computing which in turn put out large volumes of very varied data. What we are seeing is that companies today are putting into play and at the same time are trying to manage structured, semi structured and unstructured data flows in near real time also at the same time they are looking at issues of scalability, reliability and strong governance. Also what we are seeing is that the legacy Enterprise Data Warehouse (DWH) structures which are very much the norm at present are put to the test by these requirements. These legacy systems are very costly to maintain, have a very set in stone design and are very much tied into proprietary storage and processing formats. Which in turn means that they do not do a great job at supporting advanced analytics use cases like large scale machine learning (ML) and artificial intelligence (AI) as well as the integration of many different types of unstructured data sources. This paper reports on a practical full scale implementation of the Medallion Architecture which includes the Bronze, Silver and Gold layers. Here we did in the Microsoft Fabric Lakehouse unified environment and used Delta Lake as the base storage format. This approach makes improvement over the past DWH based designs which did not do a great job structurally and also in terms of cost.By decoupling storage and compute resources and utilizing open, efficient data formats, we can create a framework that dramatically enhances the quality of data, the ability to process data flexibly, and the performance of systems operating on that data and enables the execution of AI and ML workloads within the same ecosystem. The Unity Catalog Governance Framework (UCGF) represents the major component of this strategy, providing a comprehensive, extensible governance model designed for the Lakehouse architecture. The UCGF utilizes an attribute-based access control model (i.e., ABAC), which has been implemented within the Unity Catalog, and includes automated tracking of column-level lineage, as well as centralized auditing capabilities, providing a means for organizations to implement access and data traceability throughout the data lifecycle with fine-grained capabilities based on policies they establish. The UCGF is especially critical for organizations managing sensitive or regulatory protected personal data because it helps meet or exceed their organization's security and audit compliance requirements while providing them with the greatest level of flexibility in how they analyze and manipulate their data.Quantitatively evaluated, the proposed architectural framework indicates that the Gold layer provides very low latency for accessing data through Delta Lake optimizations and direct lake integration. High-Performance analytics are possible with no additional data movement or complex synchronization necessary. In addition, the architecture also significantly reduces total cost of ownership (TCO), as the cost of incremental data synchronization has been measured to be 95% less than the legacy architecture. Therefore, this proposed architecture has many strengths including performance, scalability, compliance and low TCO, and can serve as a sound foundation for enterprise-scale analytics and AI-based decision-making.