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Suddenly more timely than ever in light of the US Government's own Big Data projects, Too Big To Ignore provides a quick-read introduction to Big Data for both managers and technical types. The book's subtitle sets forth its scope: this is neither a technical work on Big Data, nor a "how-to" primer, nor a comprehensive survey of the field. Instead, Phil Simon seeks to explain why a given organization of any size — small, medium, or large — might want to give serious thought to initiating a Big Data strategy relevant to its mission. He gives an overview of Big Data concepts, current solutions, case studies, and a path to get started.
Too Big to Fail: The Business Case for Big Data
Author: Phil Simon
Publisher: John Wiley & Sons Inc., 2013
Reviewer: Bruce F. Webster
ISBN: 9781118638170 (Hardcover)
Summary: Why businesses should consider a Big Data strategy
Disclosure: I reviewed Simon's first book (Why New Systems Fail) here on Slashdot four years ago and became friends with him as a result.
Following the success of his first book, Why New Systems Fail, Phil Simon has carved a publishing niche for himself in focusing on key issues in the intersection of technology and business, then explaining those issues to business types (as well as technical workers seeking a general introduction). Successive titles include The Next Wave of Technologies (various emerging technologies relevant to business), The New Small (using key technologies to allow small businesses to compete with large ones), and The Age of the Platform (the emergence of platform-based business models).
His newest book, Too Big to Fail, seeks to do the same for Big Data. As with his prior books, Simon's audience is primarily managers and business decision makers, though his books also provide a quick overview for technologists as well.
Big Data, as Simon uses the term, refers primarily to the massive amounts of unstructured data that organizations now have access to, either by tapping into various external data sources or capturing data directly via platforms and other hosted environments. In that sense, Big Data contrasts with traditional internal data stores, such as relational database systems and data warehouses. Big Data is, of course, very much in the news right now, given the on-going revelations of the US Government's PRISM project and other data gathering efforts, which may well be the largest Big Data project to date. This book — which came out in March — clearly does not address those revelations, nor does it touch upon government analysis of Big Data (beyond one or two passing comments). What it does do — as per the subtitle — is make the business case for exploring a Big Data strategy within your organization.
The book has an introduction and eight chapters, but really comprises three major sections.The first section — the introduction and Chapters 1 & 2 — covers, in effect, "What is Big Data, and why should I care?" Simon talks about the massive growth in unstructured data over the past 10-15 years and the impact it has had on various businesses. He also
The second section — Chapters 3 and 4 — provide an overview of Big Data techniques and current solutions. While the techniques — including data visualization, semantics, and predictive analytics — are timeless, the discussion of specific current technology solutions runs the risk of being dated within a few years, though there is probably no way to avoid that beyond future edition updates.
The final section — chapters 5 through 8 — seeks to explain what Big Data looks like in a business environment (including three case studies), how to get started on a Big Data project for your organization, and what the future is likely to hold.
As someone with a strong technical background who has not had any dealings to date with Big Data, I found the book a very useful introduction and overview to the business concepts and realities of Big Data. A few times I wanted a deeper technical dive and had to remind myself that this is not written as a technical overview of the subject, but is intended primarily for a business audience.
Simon's writing style is readable and informal (occasionally perhaps a bit too informal). But it is a fast and easy read — I read it in one sitting — which is essential for Simon's target audience. In light of PRISM, the subject is perhaps more relevant than ever for all of us, and some organizations may now see Big Data initiatives as a defensive move. However, the real long-term relevance of Big Data — and the corresponding issue, opportunity, and challenge — is underscored by a sidebar in the book written by Brad Feld (Managing Director at Foundry Group, a VC firm):
Twenty years from now, the thing we call Big Data will be tiny data. It'll be microscopic data. The volume that we're talking about today, in 20 years, is a speck....We are at the very beginning of a Cambrian explosion of data. (pp. 132-133)
And that is why Big Data will impact us all."