I've been delivering data integration solutions for decades but I only recently started working with Hadoop. McKnight's and Dolezal's book is very helpful for people using any data integration technology. The language is for executives, directors, managers, and practitioners interested in learning (or learning more) about the oft-overlooked topic of data integration. As I often tell people, "You can't do Big Data without... data." The data required for modern analytics projects is rarely stored nearby. Data must be collected, transformed (shaped, cleansed, "munged"), and loaded "near" modern processing engines; whether they reside on premises or (increasingly) in the cloud.
Integrating Hadoop is peek behind the curtain of data integration - not just data integration for big data and Hadoop projects.
The first three chapters ("Hadoop in Support of an Information Strategy," "Preparing for Integration," and "ETL versus ELT") should be required reading for anyone learning data integration. McKnight, who has written previously about information technology, data, and strategy (https://www.amazon.com/William-McKnight/e/B002QLXASK/), is a thought leader in data strategy.
Chapters 4-9 provide a deeper dive into facets of data integration, using Hadoop and related technologies as examples. While the focus and examples are Hadoop-related, the principles apply almost universally to integrating data with other technology platforms.
Like the first three chapters, the last two chapters ("Top 10 Mistakes Integrating Hadoop Data" and "Case Studies and Trends") should be required reading for everyone seeking to deliver robust, high-quality, strategic data integration solutions.
I recommend Integrating Hadoop to executives, directors, managers, and developers of Analytics, Business Intelligence, Big Data, and Data Warehouse projects.