Overview

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Unlock the potential of cloud data warehousing with Azure Synapse Analytics. This course begins by introducing the core concepts of cloud-based warehousing, highlighting the advantages over traditional systems. You will gain insights into Synapse Analytics' unified approach to data, enabling you to manage SQL and Spark workloads with ease, all while streamlining analytics and reporting tasks. As you move through the course, you'll dive into practical applications, including demos on creating and managing dedicated SQL pools, integrating Spark for big data analysis, and leveraging serverless capabilities for efficient data processing. The course also covers the crucial aspects of cloud security, teaching you how to safeguard your data with tools like dynamic data masking and auditing. By exploring best practices in architecture, partitioning, and performance tuning, you'll understand how to optimize your data warehouse for enterprise-scale tasks. Finally, the course walks you through key data migration strategies, emphasizing the use of SSIS, PolyBase, and Data Factory. You’ll wrap up by exploring Azure’s monitoring and troubleshooting features, ensuring your Synapse deployment runs smoothly. This course not only equips you with essential technical skills but also prepares you to tackle real-world challenges in cloud-based data warehousing. This course is designed for data professionals, cloud engineers, and database administrators who are interested in building scalable, secure data warehouses using Azure Synapse Analytics. Prior knowledge of SQL and basic cloud computing concepts is recommended but not required.

Syllabus

Course Introduction

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.

Azure Synapse Analytics (Updated Dec 2020)

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.

Data Warehouse Internals and Architecture

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.

Data 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.

Security Layers

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.

Configuring and Optimizing

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.

Data Warehouse Crash Course

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.