Azure SQL Data Warehouse Synapse Analytics Service

In this module, we will introduce the course, outlining its main objectives and the key takeaways that learners can expect. You'll gain insight into how the course will benefit you and set the stage for what's to come in later sections.

In this module, we will explore the capabilities of Azure Synapse Analytics, focusing on cloud-based data warehousing and its modern architecture. You will engage in hands-on demos to create and manage SQL and Spark pools, analyze data using different methods, and understand the unified experience Synapse offers for data professionals.

In this module, we will dive into the internals of data warehouse architecture, covering essential topics like Azure Synapse's MPP architecture, sharding, data distribution, and partitioning. You will also explore best practices for designing fact and dimension tables, along with a practical demo on analyzing data distribution before migration.

In this module, we will focus on the critical aspects of data migration, including best practices, different loading methods, and hands-on demonstrations using tools like SSIS, PolyBase, and Data Factory. You'll also engage in assignments to apply what you've learned, ensuring a smooth transition of data from the lake to the warehouse.

In this module, we will explore the critical security layers necessary for protecting data in cloud environments. Topics include advanced data security, auditing, network protection, and encryption techniques. You'll also learn how to implement dynamic data masking and effectively manage user access to maintain data integrity and confidentiality.

In this module, we will focus on configuring and optimizing your cloud environment, covering essential tasks like backup and restore, workload management, and price optimization. You'll also explore monitoring techniques, support, troubleshooting, and how to efficiently delete and manage resources to maintain a well-optimized system.

In this module, we will dive into the fundamentals of data warehousing, exploring key concepts like dimensional modeling, fact and dimension tables, and common warehouse schemas. You'll learn the differences between OLTP and OLAP systems, the importance of data warehouses, and how to design them effectively using the best modeling practices.