Microsoft Azure Data Engineering: A Microsoft Azure Cloud Data Engineering, Data Integration and Data Warehousing reference guide
Microsoft Azure Data Engineering: A Microsoft Azure Cloud Data Engineering, Data Integration and Data Warehousing reference guide

Microsoft Azure Data Engineering: A Microsoft Azure Cloud Data Engineering, Data Integration and Data Warehousing reference guide

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Success & InspirationData Science
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This comprehensive guide toMicrosoft Azure Data Engineeringis designed to elevate your skills in data analytics, pipeline development, and Azure cloud solutions. Dive deep into essential concepts like data integration, ETL, SQL, Data Lakes, storage management, Data Governance, Data Strategy and big data architecture.This eBook is a Number #1 Best Seller in the following categories:#1 Data Warehousing#1 Computer Engineering#1 SQL ProgrammingIn today's job market, skilled Azure Data Engineers are rare, and their compensation reflects that rarity. They enjoy substantial salaries and the freedom to choose their ideal employers.As someone who has successfully become an Azure Data Engineer, I'm sharing the blueprint for my journey in this eBook.Inside, you'll find over 1,100 meticulously crafted questions and answers covering the core Azure components that Data Engineers rely on daily.This eBook is indispensable for:Rapidly enhancing your grasp of Azure Data Engineering technologyPreparing for an Azure Data Engineering interviewStudying for the DP-203 Microsoft Certification examServing as a reference guide for comprehending the operations of relevant Azure componentsSome of the key Data Engineering concepts covered include:Azure Platform: Azure Tenant, Azure Active Directory, Management Groups, Subscriptions, Resource GroupsDatabases: Azure Synapse Analytics, Azure SQL Database, SQL Server on Virtual Machines, Azure Cosmos DB, SQL Server On-Premises, DBA concepts, and SQL Performance TuningETL: Azure Data FactoryStorage: Azure Data Lake Gen2Real-Time Analytics: IoT Hub, Event Hub, Event Grid, Azure Stream Analytics, Data ExplorerData Science: Machine Learning, Databricks, Cognitive ServicesSecurity: Key Vault, RBAC, Private EndpointsDeployments: DevOps, ARM, and BICEP TemplatesProgramming: SQL, Python, PowerShell, and Azure CLIData Modeling: Kimball Methodology, Data WarehousingFront End: Function Apps, Logic AppsReporting: Power BI and Azure Analysis ServicesAzure Architecture: Lambda, Kappa, Data MeshMonitoring and