
Data Engineering with AWS
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In Section 3 of the book, we examine the bigger picture of data analytics in modern organizations. We learn about the tools that data consumers commonly use to work with data transformed by data engineers, and briefly look into how machine learning (ML) and artificial intelligence (AI) can draw rich insights out of data. We also get hands-on with tools for running ad hoc SQL queries on data in the data lake (Amazon Athena), for creating data visualizations (Amazon QuickSight), and for using AI to derive insights from data (Amazon Comprehend). We then conclude by looking at data engineering examples from the real world and explore some emerging trends in data engineering.
This section comprises the following chapters: