Azure Data Engineer Technologies for Beginners [Bundle]

Based on the information provided, here is a structured outline for a comprehensive Azure Data Solutions course that covers the various services and technologies mentioned: Course Title: Comprehensive Azure Data Solutions: From SQL to Big Data & Analytics

Introduction:

• Welcome and Course Overview
• Prerequisites (Basic T-SQL and Database concepts)
• Introduction to Microsoft Azure Free trial Subscription
• Language (English proficiency required)

Module 1: Microsoft Azure SQL Server

• Advantages of Azure Database over on-premises Database
• Provisioning Azure Database PaaS Deployments (Single, Elastic Pool, Managed Instance)
• Understanding purchasing models and Service tiers
• Provisioning Azure Database within a Virtual Machine (IaaS)
• Working with Elastic Pool Databases
• Migration to Azure SQL Data Warehouse using various methods (SSIS, Data Factory, PolyBase)

Module 2: Microsoft Azure Synapse Analytics

• Introduction to Azure Synapse analytics service
• Comparing Traditional, Modern, and Synapse Architectures
• Understanding Azure's MPP architecture
• Concepts like Data Distribution, Sharding, and partitioning
• Performing data migration to Azure SQL Data Warehouse
• Setting up and using PolyBase for efficient data loading
• Demonstrating data migration with SSIS, Data Factory, and PolyBase

Module 3: Microsoft Azure Data Lake Gen1

• Addressing limitations of traditional database systems
• Understanding the role of Azure Data Lake Gen1 in Big Data analytics
• Creating and managing a Data Lake Gen1 storage account
• Utilizing the U-SQL language for data analysis

Module 4: Microsoft Azure Data Factory

• Understanding Azure Data Factory's components and advantages
• Designing and executing pipelines with Azure Data Factory
• Scheduling, monitoring, and troubleshooting data pipelines

Module 5: Introduction to Hadoop Ecosystem

• Fundamental understanding of the Hadoop Ecosystem
• Learning the three main building blocks of Hadoop
• Overview of Apache Hive, Apache HBase, and Apache Spark within HDInsight

Module 6: Microsoft Azure HDInsight

• Understanding challenges with Hadoop and how HDInsight addresses them
• Exploring different types of HDInsight clusters (Hadoop, HBase, Spark, Kafka)
• Real-world demo: Fetching data from Data Lake, processing it through Hive, storing data in SQL Server

Labs and Practical Demonstrations:

• Step-by-step guided labs for each module to reinforce learning
• Real-world scenarios and case studies to apply concepts learned
• Tips and best practices for working with Azure Data Solutions

Course Wrap-Up:

• Recap of key concepts from each module
• Additional resources for further learning (documentation, tutorials, etc.)
• Final assessment to test comprehensive understanding
• Feedback and Q&A session

Student Testimonials:

• Include feedback from students who have completed the course, highlighting its value and the professionalism of the instructor.

Supplementary Materials:

• Downloadable cheat sheets for reference
• Code snippets and script samples
• Links to Microsoft Azure documentation and further reading materials

This course is designed to take students from the basics of Azure SQL through to understanding and working with Big Data using Azure Data Lake Gen1 and HDInsight. It aims to provide a solid foundation in Azure's data solutions ecosystem, catering to both beginners and those looking to deepen their knowledge and skills.