Azure Synapse Analytics is a powerful cloud-based data warehouse service that allows businesses to quickly and easily analyze large datasets.
It offers a variety of features, including serverless SQL pools, dedicated SQL pools, and Spark pools, making it a versatile tool for data engineers and analysts.
If you’re looking for a good course to learn Azure Synapse Analytics, you’ve likely found yourself frustrated by the sheer number of options available.
Many courses are either too basic, too advanced, or simply lack the hands-on experience that’s so crucial for mastering this complex platform.
That’s where the Azure Synapse Analytics For Data Engineers - Hands-On Project course on Udemy comes in.
It stands out as the best overall course because it strikes the perfect balance between theory and practice, taking you from the fundamentals of Azure Synapse Analytics to building real-world data pipelines and projects.
It provides a comprehensive deep dive into Azure Synapse Analytics, covering everything from data ingestion and transformation to advanced analytics and visualization.
This course isn’t the only great option out there, however.
We’ve compiled a list of the best Azure Synapse Analytics courses on Udemy, catering to different learning styles and experience levels.
Keep reading to find the perfect course for your journey into the world of Azure Synapse Analytics.
Azure Synapse Analytics For Data Engineers -Hands On Project
This course provides a comprehensive deep dive into Azure Synapse Analytics, a powerful cloud-based data warehouse service that’s essential for modern data engineers.
You’ll gain the practical skills to tackle real-world data challenges, from ingestion and transformation to advanced analytics and visualization.
Starting with the fundamentals, you’ll create an Azure account and become familiar with the Azure portal.
You’ll then explore the core components of Azure Synapse Analytics, including the workspace, studio, and the various hubs for data management, development, integration, monitoring, and administration.
To solidify your understanding, you’ll work through a hands-on project centered around analyzing NYC taxi data.
The course dives deep into Serverless SQL Pool, a key feature of Azure Synapse Analytics.
You’ll learn to query various file formats like CSV, JSON, and Parquet, leveraging functions like OPENROWSET and JSON_VALUE for efficient data extraction.
You’ll also master data discovery techniques, such as identifying duplicates and performing data quality checks, as well as building external tables for data virtualization.
Next, you’ll delve into data ingestion and transformation using Serverless SQL Pool.
You’ll discover CREATE EXTERNAL TABLE AS (CETAS) for data conversion and learn how to build robust stored procedures for complex data manipulation.
You’ll then be introduced to Synapse Pipelines, a powerful tool for automating data workflows, where you’ll learn to build pipelines that can be triggered both manually and automatically.
You’ll also explore Spark Pool, another vital component of Azure Synapse Analytics.
You’ll create a Spark Pool and learn how to seamlessly integrate it with Serverless SQL Pool for advanced data analysis.
The course demonstrates how to use Power BI to effectively visualize data from Azure Synapse Analytics.
You’ll learn about Synapse Link, which allows you to query data stored in Azure Cosmos DB using Serverless SQL Pool or Spark Pool.
Finally, you’ll explore Dedicated SQL Pool, another powerful data warehouse offering within Azure Synapse Analytics.
You’ll learn to create a Dedicated SQL Pool, copy data into it using Polybase or the Copy command, and connect it to Azure Data Studio and Power BI.
Azure SQL Data Warehouse Synapse Analytics Service
You’ll delve deep into the core components of Synapse, starting with the creation of dedicated SQL Pools – specialized databases built for handling large-scale data.
Get hands-on experience with Synapse Studio, a powerful and intuitive interface designed to streamline your data management and analytics workflows.
You’ll also discover the capabilities of Apache Spark, a tool that excels at processing large datasets with unmatched efficiency.
The course then delves into the fundamentals of data warehousing, highlighting the differences between traditional and modern approaches and how Synapse seamlessly integrates into the modern landscape.
You’ll gain a firm grasp of dimensional modeling, a key technique for structuring data for effective analysis.
The course clearly defines the roles of facts and dimensions and explores their application in both star and snowflake schema models.
Data migration is covered in depth, equipping you with the knowledge and skills to transfer data into Azure Synapse efficiently.
You’ll learn about the various loading methods available, including SSIS and PolyBase, and gain proficiency in using Data Factory for automated data loading.
Security is a critical aspect of any data warehousing solution, and this course provides a thorough understanding of how to protect your data within Synapse.
You’ll learn about features like Transparent data encryption and Dynamic Data Masking, which play crucial roles in safeguarding sensitive information.
You’ll also learn how to optimize your Synapse environment for maximum performance and cost-efficiency.
The course covers key configuration options, backup and restore procedures, and troubleshooting techniques, empowering you to manage your Synapse resources effectively.
The course concludes with a comprehensive review of key concepts, practice tests to reinforce your learning, and bonus materials for further exploration.
Azure Data Factory +Synapse Analytics End to End ETL project
This course provides a comprehensive deep dive into building end-to-end ETL (Extract, Transform, Load) projects using Azure Data Factory and Synapse Analytics.
You’ll be guided through real-world scenarios, mastering key skills in data ingestion, transformation, loading, orchestration, and reporting.
The course starts with a thorough environment setup, covering the creation of Azure Data Factory, Azure Datalake Storage Gen2, and Azure Synapse Analytics Workspace.
You’ll gain valuable insights into creating a budget for your project and optimizing costs for Azure SQL Database.
Data ingestion is tackled in detail, introducing you to various integration runtimes, including the critical self-hosted integration runtime.
You’ll practice copying data from on-premise file storage to Azure Datalake and learn effective methods for incremental data loading based on file modification dates and names.
The course then delves into the critical area of data transformation.
You’ll explore Azure Synapse Analytics, create a Spark pool, and leverage PySpark within notebooks to transform data.
Practical exercises include removing duplicates, handling null values, and creating new columns based on specific conditions.
You’ll also learn to change data types and write transformed data back to Datalake.
Data loading is covered next, with instructions on connecting to Azure SQL Database using SSMS and loading the transformed data.
You’ll practice copying data from Datalake to the SQL database and learn how to troubleshoot common errors.
The course goes beyond the basics by focusing on project enhancements.
You’ll learn how to optimize data copying from on-premise to Datalake and implement strategies for transforming only the latest data files in Synapse notebooks.
Orchestration, a vital skill for automated processes, is covered extensively.
You’ll learn to create automated pipelines using Azure Data Factory and implement email notifications for pipeline failures.
You’ll also master the orchestration of pipelines for efficient data loading into SQL Database.
Finally, the course introduces you to data reporting using Power BI, offering hands-on experience in creating reports and visualizations.
You’ll also be introduced to the concept of Continuous Integration Continuous Deployment (CICD) for Azure Data Factory, learning how to automate the build and deployment process for your project.
This course is particularly well-suited for data professionals seeking to enhance their skills in building and managing data pipelines within the Azure ecosystem.
The hands-on approach and focus on practical applications make it a valuable resource for individuals seeking to gain real-world experience in data engineering with Azure Data Factory and Synapse Analytics.
Basics to Advanced: Azure Synapse Analytics Hands-On Project
You’ll embark on a journey that covers the entire data warehousing ecosystem, starting with foundational concepts and progressing to advanced techniques.
First, you’ll gain a solid understanding of data warehousing principles and how Azure Synapse Analytics fits into the modern data landscape.
You’ll explore the key components of Azure Synapse Analytics, including the Serverless SQL Pool and the Dedicated SQL Pool, learning their strengths and how to leverage them effectively.
The course then transitions seamlessly into the world of Spark, a crucial tool for big data processing.
You’ll learn core Spark concepts, such as RDDs (Resilient Distributed Datasets), and get hands-on experience with PySpark through practical examples.
You’ll explore various Spark APIs, including DataFrames and SQL, and delve into essential PySpark transformations like filtering, aggregation, and joining data.
The course also provides guidance on optimizing your Spark code for peak performance.
You’ll then discover Delta Lake, a cutting-edge technology that empowers you to build a lakehouse architecture for your data.
Delta Lake offers enhanced reliability and performance for your data pipelines, making it a valuable asset for your big data endeavors.
Finally, you’ll learn how to seamlessly integrate your data with Power BI, enabling you to create interactive reports and dashboards that visualize your insights.
You’ll have the tools and knowledge to design, build, and optimize data pipelines, manage data lakes, and extract valuable insights from your data.
Data Warehousing with Azure Synapse Analytics : Hands on Lab
You’ll begin by getting comfortable with the cloud and understanding why Azure stands out as a leading platform.
From there, you’ll delve into the fundamentals of Azure Synapse Analytics, learning what it is and how to set up your own workspace.
You’ll gain practical experience through hands-on labs, working within Synapse Studio, the platform where you’ll build your skills.
The course then focuses on Synapse SQL Pool, formerly known as SQL Data Warehouse, a powerful tool for storing and analyzing massive datasets.
You’ll explore its architecture and learn how to create your own SQL pool.
The course covers essential data loading methods like Polybase, CTAS, and Copy Into statements, giving you the tools to effectively manage your data.
You’ll even learn how to leverage Azure Data Factory, another Azure tool that simplifies data movement and transformation.
But this course goes beyond just using Synapse.
You’ll also learn how to manage it effectively, covering critical topics like creating restore points and backups, performing geo-backups for disaster recovery, and implementing encryption and auditing.
Finally, you’ll gain the knowledge to monitor your Synapse SQL Pool, ensuring its smooth operation and optimal performance.
This course provides a comprehensive foundation in Azure Synapse Analytics, equipping you with the skills and knowledge to effectively use and manage this powerful cloud platform.
Azure Synapse Analytics For Data Engineers
You’ll dive into the core components of Azure Synapse Analytics, including Dedicated SQL Pools, Serverless SQL Pools, and Data Explorer Pools.
Learn how to create external tables and views in Serverless SQL Pools, read files from ADLS Gen2 (Azure Data Lake Storage Gen2) using T-SQL, and write and execute KQL queries in Data Explorer Pools.
These are the skills that enable you to explore and analyze data effectively.
But there’s more.
This course goes beyond traditional SQL.
You’ll experience the power of Apache Spark, a distributed processing framework, within Azure Synapse Analytics.
Discover how Spark pools can accelerate data processing, handle massive datasets in memory, and scale your analytics workflows efficiently.
You’ll learn to perform data transformation, build machine learning models using MLlib, and even analyze real-time data streams.
This comprehensive course will help you design, build, and manage data pipelines in Azure Synapse Analytics, enabling you to tackle complex data engineering challenges with confidence.