Build a Data Mesh using Azure-Hands on, real-world scenario

In this course, I will practically show you how to build a Data Mesh using Microsoft’s cloud computing platform Azure. By the end of the course, you would have gained a solid understanding of Azure Synapse analytics, and how it can be used for data ingestion, transformation, and analysis. I will give you an overview of all the Hubs in Azure Synapse and show you how to use Serverless SQL Pools and Spark Pools. You will understand the OPENROWSET function, explicit data types, collation, database, external data source, linked service, built-in copy data tool, CETAS, pipelines, activities, dataflows, external table, and view. I will show how to perform data analysis using Spark and SQL.  You will understand what data mesh is and its principles, and how it can be applied in a real-world scenario. You will learn about the importance of data domains.  You will learn about azure data lake storage gen v2. You will learn about how to assign built-in roles in Azure.

Furthermore, you would have explored the role of domain-driven design in creating a modular scalable data infrastructure. Data Mesh emphasizes the decentralization of data management, allowing teams to own their data and avoid dependencies on a central data team, you will learn about using Azure to create decentralized teams, in the Microsoft Entra Id previously Azure active directory we will create users and groups for the decentralized teams. Then we will build the data domains using the domain-specific teams. The principles of data mesh can help you build more robust and scalable data systems that meet your organization's needs. Whether you are a data engineer or a data scientist or a data analyst or a business analyst or whichever role in IT, at the end of this course you will understand how with the new Data Mesh architecture in place, the company can build data-driven products without any data silos.