While at first glance potential readers might see this white paper sized text as overlapping with another recent O'Reilly Radar Team publication, "Big Data Now: Current Perspectives from O'Reilly Radar", this work is really intended to focus on what Big Data is all about, why it matters, and where to get started, whereas the earlier text covered a much broader spectrum of Big Data related material. In addition, while management is part of the target audience for both, the earlier text is also more technical in the sense that it gets down to programmatic levels in a few places, and also discusses technology stacks that this book does not cover.
After a discussion of how a company collects, analyzes, and acts on data, and a walk through different aspects of Big Data, the editors shift the discussion to a very high level overview of the Apache Hadoop ecosystem, followed by a Big Data market survey somewhat akin to what one might find from Gartner that focuses on enterprise software vendor distributions of Hadoop, Big Data cloud platforms, and data markets, and brief entries on the NoSQL movement, data visualization, and O'Reilly Radar Team expections from the Big Data landscape over the coming year.
Readers are gently led through the current Big Data landscape. For example, as the author of the second chapter states, "Big data is data that exceeds the processing capacity of conventional database systems. The data is too big, moves too fast, or doesn't fit the structures of your database architectures. To gain value from this data, you must choose an alternative way to process it. The hot IT buzzword of 2012, big data has become viable as cost-effective approaches have emerged to tame the volume, velocity, and variability of massive data. Within this data lie valuable patterns and information, previously hidden because of the amount of work required to extract them."
Although this book contains different material than "Big Data Now: Current Perspectives from O'Reilly Radar", as a consultant I think technical audiences new to this space will prefer this earlier work. In addition, it is rather apparent that "Planning for Big Data: A CIO's Handbook to the Changing Data Landscape" emphasizes commericalized open source products, and does not cover tooling outside of the Hadoop ecosystem to any great extent. While this book is 25% shorter, and is understandably targeted at senior management, many potential readers will likely appreciate the more extensive coverage of this space in the earlier text.