Managing Data in Motion: Data Integration Best Practice Techniques and Technologies (The Morgan Kaufmann Series on Business Intelligence)

One of my favorite things about this book is the length. It covers so much good material in less than half the length of similar books that it's a worthwhile investment of time for anyone who does serious work with data integration on a medium or large scale. Along with covering best practices for data management issues such as realistic lifecycles for data integration implementations, the book provides good historical context for how people dealt with the relevant issues in the past, and in general puts many common buzzwords and acronyms in perspective. I like how it often enumerates the connections between technical data integration issues and business data integration issues, between theory and practice, and the implications of the use of recent technologies (and data, such as "Internet of Things" data along with legacy data) popular in big data environments.I did a lot of underlining in this book and I'm sure I'll be reviewing those parts multiple times.

Complete high level information, with zero substance. Don't waste your money or time

Very good overview book on the considerations and challenges of enterprise level integrations.

An excellent book for my needs. I would have enjoyed seeing methods for testing data in motion, but can figure that out. Sending my appreciation to April Reeve for this fine work.

Gear treatment of the topic.

Managing Data in Motion, Data Integration Best Practice Techniques and Technologies is a really well written work that surveyed a broad range of practices and technologies used in Data Integration. The book avoided overburdening jargon so it should be quite accessible to anyone who is interested in learning about Data Integration's past, present and future. The author has done a valiant job pulling together a wealth of knowledge into an easily consumable form. In addition to her own words, I also greatly appreciated the sidebars from experts in their own domains. While the Table of Contents is somewhat intimidating in its list of topics, it was really a very easy read.So I've been in the IT industry from over 14 years now. While I have deep experience in many areas, I felt I needed to shore up my expertise on Data Integration (DI) and Information Management. MDM, DI, Business Intelligence and Big Data are white hot now in the market! This book was just the ticket. It refreshed and honed the areas that I knew; and succinctly introduced and summarized many that I've recently started exploring. For example, the author revalidated (for me) the tried-and-true practices of Profiling and Proving, and then moved on to hit all the new sexy topics as well. Chapters 16+ were especially timely in their survey of emerging practices and technologies, such as Data Virtualization and Big Data.In short, this is a very well written book that any person at any point in their IT career ought to appreciate. Well worth a read.

Uber basic, was hoping for more design patterns, pros and cons of next generation streaming approaches (Kafka, messages queues etc etc). Very superficial, almost a primer on the uber basics.

O livro detalha o processo de movimento de dados principalmente no aspecto não tecnológico. Acho que deveria se mais objetivo para alguns conceitos, pois parte de um príncipio que o leitor já conhece.

I can not recommend the book at. It is listing trivial topics, is repeating content quite often and lacks deep insights. It is scratching several topics on the surface only. It is bloated due to its overarching structure - sections with two or three pages are just not worth a section at all. It seems to me that structure was defined first and then the author was trying hard to fill the structure with content rather than structuring content and deep knowledge. I am very sorry to say, but I wasted time and money by ordering the book.