Data Architectures and Microsoft Fabric

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they’re also surrounded by a lot of hyperbole and confusion. In this presentation, I will give you a guided tour of each architecture to help you understand its pros and cons. I will also examine common data architecture concepts, including data warehouses and data lakes. You’ll learn what data lakehouses can help you achieve, and how to distinguish data mesh hype from reality. Best of all, you’ll be able to determine the most appropriate data architecture for your needs.

In addition, I will delve into how Microsoft Fabric can be leveraged within each of these architectures. From integrating data fabrics for enhanced data management and governance, to implementing data lakehouses for streamlined analytics, and establishing data meshes for decentralized data ownership, Microsoft Fabric offers robust solutions and tools. By the end of this presentation, you’ll have a clear understanding of how to use Microsoft Fabric to build and optimize these diverse data architectures, tailored to meet your specific requirements.

Explain and compare data fabric, data lakehouse, and data mesh architectures, including their strengths and limitations. Clarify how these approaches relate to traditional data warehouses and data lakes. Show how Microsoft Fabric can be applied to build and optimize each architecture.