Become Microsoft Certified: Azure Data Engineer Associate "Become a Microsoft Certified: Azure Data Engineer Associate: The Comprehensive Guide" provides readers with a thorough understanding of Azure data engineering concepts and technologies. Through twelve chapters covering various aspects of Azure data services, data storage, data integration, data processing, data governance, data monitoring, data pipelines, data warehousing, data integration in hybrid scenarios, data streaming, data governance and compliance, and exam preparation strategies, readers will gain the knowledge and skills required to pass the Azure Data Engineer Associate certification exam. By following the guide and mastering the topics, readers will be well-equipped to excel in the field of Azure data engineering. The book covers the following: Chapter 1: Introduction to Azure Data Engineering Overview of Azure Data Engineering and its significance. Understanding the Azure Data Engineer Associate certification. Examining the role and responsibilities of an Azure Data Engineer. Navigating the Microsoft Certified Azure Data Engineer exam structure, format, and scoring. Developing a study plan and preparing for the Microsoft Certified Azure Data Engineer exam. Chapter 2: Azure Data Services Understanding the various data services offered by Azure. Exploring Azure SQL Database and its features. Utilizing Azure Synapse Analytics for big data and analytics. Implementing Azure Data Lake Storage for scalable data storage. Leveraging Azure Databricks for data engineering and analytics. Chapter 3: Data Storage and Data Integration in Azure Designing and implementing data storage solutions in Azure. Utilizing Azure Blob Storage and Azure Files for unstructured data. Implementing Azure Data Factory for data integration and orchestration. Utilizing Azure Data Share for secure data sharing. Examining Azure Data Catalog for data discovery and governance. Chapter 4: Data Processing with Azure Implementing batch processing using Azure Batch. Utilizing Azure HDInsight for big data processing. Understanding Azure Stream Analytics for real-time data processing. Leveraging Azure Functions for serverless data processing. Implementing data pipelines and data transformations with Azure. Chapter 5: Data Governance and Security in Azure Implementing data governance practices in Azure. Understanding Azure Data Catalog for metadata management. Implementing Azure Purview for data discovery and classification. Ensuring data security and privacy in Azure. Managing access control and implementing data encryption in Azure. Chapter 6: Data Monitoring and Optimization in Azure Implementing data monitoring and diagnostics in Azure. Utilizing Azure Monitor for monitoring data solutions. Analyzing and optimizing data storage and processing costs in Azure. Examining performance tuning techniques for Azure data services. Utilizing Azure Advisor for recommendations and best practices. Chapter 7: Data Pipelines and Orchestration in Azure Designing and implementing data pipelines in Azure. Utilizing Azure Data Factory for data movement and transformation. Implementing data orchestration with Azure Logic Apps. Automating data workflows using Azure Scheduler. Monitoring and troubleshooting data pipelines in Azure. Chapter 8: Data Warehousing and Business Intelligence in Azure Designing and implementing data warehousing solutions in Azure. Utilizing Azure Synapse Analytics for data warehousing. Implementing dimensional modeling and star schema in Azure. Utilizing Azure Analysis Services for business intelligence. Implementing data visualization and reporting using Power BI. Chapter 9: Data Integration and Hybrid Scenarios in Azure Chapter 10: Data Streaming and Event Processing in Azure Chapter 11: Data Governance and Compliance in Azure Chapter 12: Microsoft Certified Azure Data Engineer
