Microsoft Azure Data Engineering
A Microsoft Azure Cloud Data Engineering, Data Integration and Data Warehousing reference guide
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Microsoft Azure Data Engineering
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Jack Reynolds
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This comprehensive guide to Microsoft Azure Data Engineering is 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 Programming
In 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 technology
- Preparing for an Azure Data Engineering interview
- Studying for the DP-203 Microsoft Certification exam
- Serving as a reference guide for comprehending the operations of relevant Azure components
Some of the key Data Engineering concepts covered include:
- Azure Platform: Azure Tenant, Azure Active Directory, Management Groups, Subscriptions, Resource Groups
- Databases: Azure Synapse Analytics, Azure SQL Database, SQL Server on Virtual Machines, Azure Cosmos DB, SQL Server On-Premises, DBA concepts, and SQL Performance Tuning
- ETL: Azure Data Factory
- Storage: Azure Data Lake Gen2
- Real-Time Analytics: IoT Hub, Event Hub, Event Grid, Azure Stream Analytics, Data Explorer
- Data Science: Machine Learning, Databricks, Cognitive Services
- Security: Key Vault, RBAC, Private Endpoints
- Deployments: DevOps, ARM, and BICEP Templates
- Programming: SQL, Python, PowerShell, and Azure CLI
- Data Modeling: Kimball Methodology, Data Warehousing
- Front End: Function Apps, Logic Apps
- Reporting: Power BI and Azure Analysis Services
- Azure Architecture: Lambda, Kappa, Data Mesh
- Monitoring and Governance: Azure Purview, Azure Monitor, Log Analytics
Secure your copy of "Microsoft Azure Data Engineering" today and embark on your journey to a rewarding six-figure career!