As regular readers of this blog know, I periodically review database and data related books in a feature dubbed Inside the Data Reading Room. Today’s blog post is one of those data book review posts!
And we’ll start off today’s edition of Inside the Data Reading Room with a Big Data book: Commercial Data Mining: Processing, Analysis and Modeling for Predictive Analytics Projects by David Nettleton (Morgan Kaufmann, ISBN 978-0-12-416602-8). And yes, data mining and analytics are important aspects of the Big Data trend.
The book is laid out nicely to use as a reference and will be helpful to both pros and newbies alike. You can use the book to guide you through the process from beginning to end in your data mining and analytics endeavors. The book starts by focusing on business objectives and moves forward from there covering important aspects like Data Quality, Data Representation, Sources of Data, Data Sampling and Analysis, Modeling, and more.
If you are look for a book that not only can serve as a valuable reference guide for your data mining project, but also offers up practical examples,case studies, and actionable business insights based on the author’s experience, then look no further than Nettleton’s Commercial Data Mining.
Next up on my reading list is The Art of Information Architecture: A Systems-Based Approach for Unlocking Business Insight by Mario Godinez, et al (IBM Press, ISBN 978-0-13-703571-7). This book tries to examine and explain the new reality being faced by organizations as they build their enterprise information architecture (EIA) — to bring some clarity to a rapidly evolving and confusing field.
The book attempts to explain the key concepts of information processing and management, the methodology for creating next generation EIA, how to architect an information management solution, and how to apply archictetural patterns for business solutions. That is a lot of ground to cover, but the authors do a reasonable job of accomplishing that goal.
The material is not in-depth, as each of the areas covered could consume an entire book (or more) themselves. Chapters are including that focus on component and operational models, cloud computing, enterprise information integration (EII), metadata management, master data management (MDM), and more. If you are looking for comprehensive treatment of any of these topics, this is not your book. However, if you are looking for a nice overview of the concepts and how they fit into a modern enterprise information architecture, then this book will be ideal for you.
Perhaps the only complaint I have is that with so many authors (6) the writing style can change somewhat abruptly at times. But the material is solid; The Art of Information Architecture offers a nice view of enterprise data management in the early 2010s.
Finally, I’d like to recommend a non-IT book that can nevertheless help you with your IT career – any career, actually. That book is An Illustrated Book of Bad Arguments by Ali Almossawi (JasperCollins Publishers, ISBN 978-0-9899312-0-5). The title notwithstanding, the book can help you to form reasonable and “good” arguments by avoiding the examples of fallacious reasoning that it provides.
You do not need to be an expert in the field of logic to benefit from this book. It is short, concise, and to the point. Over the course of 56 pages the author introduces a “bad argument” method, gives an example, and explains why the method is faulty. If you have ever participated in an Internet chat room “discussion” you will recognize all of the bad argument techniques in the book… and now you will know why they are bad and how to avoid them.
That’s all for this edition of Inside the Data Reading Room… see you next time!