Azure Data Engineering teaches you to build high-capacity data analytics systems using Azure cloud services for storing, collecting, and analyzing data. In it, seasoned IT professional and author Richard Nuckolls starts you off with an overview of core data engineering tasks and the Azure tools that support them. Then, you’ll dive right into building your analytics system, starting with Data Lake Store for data retention, Azure Event Hubs for high-throughput ingestion, and Stream Analytics for real-time query processing.
The Microsoft Azure cloud is an ideal platform for data-intensive applications. Designed for productivity, Azure provides pre-built services that make collection, storage, and analysis much easier to implement and manage. Azure Data Engineering teaches you how to design a reliable, performant, and cost-effective data infrastructure in Azure by progressively building a complete working analytics system.
The Microsoft Azure cloud platform can host virtually any sort of computing task, from simple web applications to full-scale enterprise systems. With many pre-built services for everything from data storage to advanced machine learning, Azure offers all the building blocks for scalable big data analysis systems including ingestion, processing, querying, and migration.
For batch scheduling and aggregate data movement, you’ll add Data Factory and Data Lake Analytics, along with SQL Data Warehouse for interactive queries. With Azure Active Directory, you’ll manage security by applying permissions and access roles. And because your design is based on the Lambda architecture, you can be sure it will handle large volumes of data beautifully and with lightning speed!
What's inside:
Azure cloud services architecture Building a data warehouse in Azure How to choose the right Azure technology for your task Calculating fixed and variable costs Hot and cold path analytics Stream processing with Azure Stream Analytics and Event Hub integration Giving structure to distributed storage Practical examples leading up to a fully functioning analytics system
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