Tupper C.D. Data Architecture: From Zen to Reality

Morgan Kaufmann, 2011. — 422 p. — ISBN10: 0123851262, ISBN13: 978-0123851260.First, note that I have used Zen in the title of this book. I have been asked many times why I used such an esoteric term. After all, what is the meaning of Zen? To clarify the meaning of Zen, we must examine the philosophical environment that gave rise to Zen: Indian and Chinese philosophies. In India, Buddhism arose out of a Hindu environment, and later one form called Mahayana evolved. Taoism, a philosophy that also contributed much to Zen, was developed in China.
It was in China where imported Mahayana Buddhist ideas fused with existing Taoist ideas to form what was later called Zen. Concepts that are typically attributed to Mahayana Buddhism and Taoism are integral parts of Zen thought. These concepts helped me in my choice for the title.
Zen is a philosophy, a religion, a psychology, and a way of life, but these are interpretations of Zen. It is said that Zen is complex and contradictory but remarkably simple; that Zen is empty and void but remarkably full and delightful. Simply put, Zen is a way of being. It also is a state of mind. Zen involves dropping illusion and seeing things without distortion created by your own perceptions.
Words and concepts can be useful, but mistaking them for reality can cause many problems. Concepts about reality are not reality. The menu is not the food. In order to experience Zen, one needs to dissolve all preconceptions, beliefs, concepts, and judgments about the self and the universe and see the now.
So what is Zen? Zen simply is. Often it seems that the search for Zen’s meaning reveals nothing but contradictions. Any realization of truth seems impossible. Yet, Zen has a unique way of pointing at the thatness of everything. Zen brings us face to face with the true original nature of things, undefiled by cultural conditioning and neurotic tendencies.
When this is applied to data, it simply means that data is. It exists in its own state, without our perspectives and views of it. It has a now and a whatness of existence. So it is this presence or oneness of data that we begin with and move toward discrete interpretations of how it can be shaped, molded, viewed, illustrated, structured, and understood. It is with this in mind that the book is titled Data Architecture: From Zen to Perceived Reality. I wrote this book because something has been fundamentally lost in the last decade in the information technology world. We are no longer developing information stores that address the present and future needs; we are merely generating information stores that meet the current needs.
Like everything else over the last 15 to 20 years, new products are being designed from a tactical point of view with builtin obsolescence. There is no long-term view, no strategy, without which it is impossible to develop data stores that are built to last. It is time to revisit the basic principles from which we deviated to get to this point.
Instead of the evolution that was prophesied in the 1970s and early 1980s, what happened instead was a revolution where many good things were lost and destroyed at the expense of developing things rapidly and at low cost. This is not a polemic against what has occurred in the last 10 to 15 years but merely a commentary and observational review of some of the basic principles that were the basis of the initial evolution.
It is time to revisit those principles and try to rescue and reinstate some of those values to validate our course in building proper data architectures that will stand the test of time. It is also time to review many of the principles posited by Peter Drucker concerning the knowledge workers that interact with those data architectures.
You see, the evolution started with a basic principle that knowledge is created from data by people for people to use for the greater good of all people. Modern business has somehow drifted away from people and quality and is now focused on money and speed. On a more specific note, this book’s goal is to raise the awareness of the single most ignored component of the original evolution in the IT world: architecture.
Architecture — the method of design and planning things before they are constructed — is being overlooked or bypassed in the haste to develop and deliver the product. The focus has shifted from the process to the product. The quality, and even the quantity, doesn’t appear to matter anymore as long as the product gets out and the delivery time is short. This short delivery time, dovetailed with built-in obsolescence, is leading the inroads to the explosion of consumerism. With the advent of the rampant consumerism comes the downfall of the principles of building things to last.The Principles
Understanding Architectural Principles.
Enterprise Architecture Frameworks and Methodologies.
Enterprise-Level Data Architecture Practices.
Understanding Development Methodologies.
The Problem
Business Evolution.
Business Organizations.
Productivity Inside the Data Organization.
Solutions That Cause Problems.
The Process
Data Organization Practices.
Models and Model Repositories.
Model Constructs and Model Types.
Time as a Dimension of the Database.
The Product
Concepts of Clustering, Indexing, and Structures.
Basic Requirements for Physical Design.
Physical Database Considerations.
Interpreting Models.
Specialized Databases
Data Warehouses I.
Data Warehouses II.
Dimensional Warehouses from Enterprise Models.
The Enterprise Data Warehouse.
Object and Object/Relational Databases.
Distributed Databases.