Data is an expensive and expansive asset. Information capture has forced storage capacity from megabytes to terabytes, exabytes and, pretty soon, zetabytes of data. So the need for accessible storage space for this data is great. To make this huge amount of data usable and relevant, it needs to be organized effectively. Database Base Management Systems, such as Oracle, IBM's DB2, and Microsoft SqlServer are used often, but these are being enhanced continuously and auxiliary tools are being developed every week; there needs to be a fundamental starting point for it all. That stating point is Data Architecture, the blueprint for organizing and structuring of information for services, service providers, and the consumers of that data.
Data Architecture: From Zen to Reality explains the principles underlying data architecture, how data evolves with organizations, and the challenges organizations face in structuring and managing their data. It also discusses proven methods and technologies to solve the complex issues dealing with data. The book uses a holistic approach to the field of data architecture by covering the various applied areas of data, including data modelling and data model management, data quality , data governance, enterprise information management, database design, data warehousing, and warehouse design. This book is a core resource for anyone emplacing, customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality.
Review By: John Snuggs 02/05/2012I enjoyed this book but really struggled to understand whom it’s trying to reach. The early chapters are deep in theory and attempt to tie into physical building architectural theory as well as the Zen in the title. In my opinion, they just flat out miss the mark. However, I will keep this book on my bookshelf and happily use the later chapters.
The subject of data architecture is a huge target. The author provides a fairly thorough treatment and documents plenty of options for further study via references and suggested readings.
Major sections include Principles (extremely dry; bring your own caffeine), the Problem (esoteric), the Process and the Product (tied for my favorite), and Specialized Databases (pretty good). Within the Process and Product sections, I found the content on data modeling and physical design to be the most interesting. Each is covered well enough to make this a reference book that I will pull out to refresh my memory. The section on Specialized Databases piqued my interest and made me seek out additional information about distributed databases.
My experience with data warehouses is fairly limited. I found the four chapters that cover them to be interesting and helpful. I am still not an expert, but I do feel like I can carry on a conversation as an informed participant rather than being blissfully ignorant.
If you are looking for a good, solid foundation on data architecture that will allow you to easily find information and a good collection of references for more study, I recommend this book.