Data Architecture - 1st Edition - ISBN: 9780123851260, 9780123851277

Data Architecture

1st Edition

From Zen to Reality

Authors: Charles Tupper
eBook ISBN: 9780123851277
Paperback ISBN: 9780123851260
Imprint: Morgan Kaufmann
Published Date: 23rd March 2011
Page Count: 448
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Description

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. Using a holistic approach to the field of data architecture, the book describes proven methods and technologies to solve the complex issues dealing with data. It covers 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 text is a core resource for anyone customizing or aligning data management systems, taking the Zen-like idea of data architecture to an attainable reality.

The book presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios. It teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions. It includes the detail needed to illustrate how the fundamental principles are used in current business practice. The book is divided into five sections, one of which addresses the software-application development process, defining tools, techniques, and methods that ensure repeatable results.

Data Architecture is intended for people in business management involved with corporate data issues and information technology decisions, ranging from data architects to IT consultants, IT auditors, and data administrators. It is also an ideal reference tool for those in a higher-level education process involved in data or information technology management.

Key Features

  • Presents fundamental concepts of enterprise architecture with definitions and real-world applications and scenarios
  • Teaches data managers and planners about the challenges of building a data architecture roadmap, structuring the right team, and building a long term set of solutions
  • Includes the detail needed to illustrate how the fundamental principles are used in current business practice

Readership

Data architects; systems analysts, data modelers, IT Directors, managers and CxOs, IT governance employees, business process management strategists; IT consultants, IT auditors, data administrators

Table of Contents


Preface

Section 1 The Principles

Chapter 1 Understanding Architectural Principles

Defining Architecture

Design Problems

Patterns and Pattern Usage

Concepts for Pattern Usage

Information Architecture

Structure Works!

Problems in Architecture

Architectural Solutions

The “Form Follows Function” Concept

Guideline: Composition and Environment

Guideline: Evolution

Guideline: Current and Future

Data Policies (Governance), the Foundation Building Codes

Data Policy Principles

Chapter 2 Enterprise Architecture Frameworks and Methodologies

Architecture Frameworks

Brief History of Enterprise Architecture

The Zachman Framework for Enterprise Architecture

The Open Group Architecture Framework

The Federal Enterprise Architecture

Conclusions

Enterprise Data Architectures

Enterprise Models

The Enterprise Data Model

The Importance of the Enterprise Data Model

Object Concepts: Types and Structures Within Databases

Inheritance

Object Life Cycles

Relationships and Collections

Object Frameworks

Object Framework Programming

Pattern-Based Frameworks

Architecture Patterns in Use

U.S. Treasury Architecture Development Guidance

TADG Pattern Content

TADG Architecture Patterns

IBM Patterns for e-Business

Enterprise Data Model Implementation Methods

Chapter 3 Enterprise-Level Data Architecture Practices

Enterprise-Level Architectures

System Architectures

Enterprise Data Architectures

Enterprise Technology Architectures

Enterprise Architecture Terminology—Business Terms

The Enterprise Model

The Enterprise Data Architecture from a Development Perspective

Subject Area Drivers

Naming and Object Standards

Data Sharing

Data Dictionary–Metadata Repository

Domain Constraints in Corporate and Non-Corporate Data

Organizational Control Components

Data Administration

Database Administration

Setting Up a Database Administration Group

Repository Management Areas and Model Management

Chapter 4 Understanding Development Methodologies

Design Methods

Why Do We Need Development Methodologies?

The Beginnings

Structured Methods

Structured Programming

Structured Design

Structured Analysis

Still Having Problems

Requirements Definitions

Problems with Structured Approaches

Personal Computers and the Age of Tools

Engineering Concepts Applied

Other Principles Utilized

The Birth of Information Engineering

Information Engineering as a Design Methodology

The Synergy of Tools and Information Engineering

Problems with Information Engineering

Implementing the Best of IE while Minimizing Expense

Section 2 The Problem

Chapter 5 Business Evolution

The Problem of Business Evolution

Expansion and Function Separation

Separate Function Communication

Manual Data Redundancy

Data Planning and Process Planning

Corporate Architecture

Using Nolan’s Stages of Growth

Problems with Older Organizations

Business Today

When Will It End?

What Can We Do about It?

Generic Subject Areas for Corporate Architectures

Corporate Information Groupings or Functional Areas

Corporate Knowledge

Chapter 6 Business Organizations

Purpose and Mission of the Organization

Ideology, Mission, and Purpose

Design with the Future of the Organization in Mind

Generalize for Future Potential Directions

Organizational Structure

What Are the Basic Functions in an Organization?

The Information Needs of Management

Organizations Don’t Know What They Don’t Know

Information Strategy for Modern Business

Maximizing the Value of Information

Forces in the Organization

Chapter 7 Productivity Inside the Data Organization

Information Technology

What Is Information Technology?

Trends in Information Technology

Vendor Software Development

The Other Option

Trends in Organizational Change

Productivity

Explanations for the Anomaly in Productivity

Information Technology and Its Impact on Organizations

Why Invest in Information Technology?

Ineffective Use of Information Technology

Other Impediments to Organizational Efficiency

Organizational Impediments to Information Technology

Technological Solutions for Information Technology

Human Resource Issues in Information Technology

Quality of the Workforce

Summary

Maximizing the Use of Information Technology

Chapter 8 Solutions That Cause Problems

Downsizing and Organizational Culture

Downsizing Defined

Culture Change

Organizational-Level Analysis

Organizational/Individual-Level Analysis

Downswing’s Impact on Culture

A Different Approach to Culture Change and Downsizing

Summary

Outsourcing

Rapid Application Development

Section 3 The Process

Chapter 9 Data Organization Practices

Fundamentals of All Data Organization Practices

Corporate Data Architecture

Corporate Data Policy

Architecture Team

Design Team

Develop the Project Structure

Scope Definition

Project Plan

Data Architecture and Strategic Requirements Planning

Data Gathering and Classification

Business Area Data Modeling

Current Data Inventory Analysis

Data and Function Integration

Event Identification

Procedure Definition via Functional Decomposition

Process Use Identification

New Function Creation

Utilization Analysis via Process Use Mapping

Access Path Mapping

Entity Cluster Development and Logical Residence Planning

Application Development Templates

Quality Assurance Metrics

Maintenance Control Process

The Software Development Methods

Architectural Development Methods

Atomic Process Models

Entity Process Models

The Unified Method

Chapter 10 Models and Model Repositories

What Are Models and How Did They Come About?

Data Models Introduction

What Does Modeling Do for Us?

Process Models Introduction

Process Models—Why?

How Are Automated Models Developed?

How Are Models Retained?

Model Repository Policy and Approach

Shared Repository Objects

Model-Driven Releases

Supporting an Application Release

Version Type: Participation

Seamless Development Control Process

Test Environments, Releases, and Databases

Release Stacking

Emergency Corrections

Emergency Correction Procedures

PTF Implementation for Shared Batch and Online Objects

Chapter 11 Model Constructs and Model Types

Data Model Constructs

Application Audience and Services

Entities

Attributes

Relationships

Primary Identifiers

Entity Types

Entity Relationship Diagrams

Types of Relationships

Model Types

Physical-Level Design

Primary Keys

Normalization

Denormalization

Overnormalization

Domains

Domain Constraints

Reference Data

Generic Domain Constraint Constructs

Chapter 12 Time as a Dimension of the Database

What Is to Be Done with Historical Data?

Application History

Classes and Characteristics

Current Occurrence

Simple History

Bounded Simple History

Complex History

Logically Modeling History

Physical Design of History

Physical Implementation of History

Performance Tuning

Finding Patterns

Tips and Techniques for Implementing History

Types of Systems

Physical Structure

Dimensional History

Section 4 The Product

Chapter 13 Concepts of Clustering, Indexing, and Structures

Cluster Analysis

What Is a Cluster?

Cluster Properties

Cluster Theory Applied

Inserts

Updates

Deletes

Physical Structure

Key History and Development

Primary Keys

Foreign Keys

Foreign Key Propagation

Candidate Keys

Natural Keys

Engineered Keys

Surrogate Keys

High Water Keys

One of a Kind Keys

Other Specialized Keys

Chapter 14 Basic Requirements for Physical Design

Requirements for Physical Design

How Much Data?

History

Population Quantification of Application Data

Concurrency

Security/Audit

Audit

Archive/Purge

Recovery/Restart

Sort/Search Requirements

Reorganization and Restructuring

Data Integrity

Referential Integrity

Data Access

Privacy Requirements

Chapter 15 Physical Database Considerations

Three-Level Architecture

Data Independence

Database Languages

Classification of Database Management Systems

Factors Impacting Physical Database Design

Analysis of Queries, Reporting, and Transactions

Queries, Reports, and Transactions

Interpreting the Functional Decomposition

Event Identification

Process Use Identification Reviewed

Utilization Analysis via Process Use Mapping

Time Constraints of Queries and Transactions

Analysis of Expected Frequency of Insert, Delete, Update

Other Physical Database Design Considerations

Population on the Database

Chapter 16 Interpreting Models

Physical Design Philosophy

Objectives

The Entity Relationship Model

Interaction Analysis

The CRUD Matrix

Entity Life Cycle Analysis/Entity State Transition Diagrams

Process Dependency Scope and Process Dependency Diagram

Event Analysis

Process Logic Diagrams

Interaction Analysis Summary

Changes to ER Models

ERD Denormalization

Actions on Super Type–Subtype Constructs

Actions on Multiple Relationships

Resolution of Circular References

Resolution of Duplicate Propagated Keys

Access-Level Denormalization

Movement of Attributes

Consolidation of Entities

Derived Attributes and Summary Data

Implement Repeating Groups

Introduce Redundancy

Introduce Surrogate or Synthetic Keys

Vertical or Horizontal Segmentation

Access Path Mapping

Conclusion

Section 5 Specialized Databases

Chapter 17 Data Warehouses I

Early Analysis in this Area

Keen and Scott-Morton

Decision Discussion

Components of Decisions

Responsibility

Report Writers and Query Engines

Warehouses versus Reporting Databases

Higher Level of Abstraction

Based on Perceived Business Use

Structure Evolution

Warehouse Components

Why Can’t OLTP Data Stores Be Used?

DSS Requirements

Warehouse Characteristics

Warehouse Modeling

Warehouse Modeling Depends on Architectures

Enterprise-Level Data Architecture

Chapter 18 Data Warehouses II

Reprise

Background

The Many Types and Levels of Data

Data Modeling: Definitions

Logical to Physical Transformation

Entity Relational Models

Placement of Models

Dimensional Modeling: Definitions

Denormalization and the Dimensional Model

Dimensional Model Evaluation

Data Evolution

What Are the Choices?

Applicability of the Dimensional and Relational and Hybrid Models

Dimensional Architecture

Where Is the Relational Data Warehouse Best Suited?

Where Is the Dimensional Best Suited?

Hybrid ER-Dimensional

Problems Associated with the Hybrid Approach

Target Enterprise Architecture

Building an Enterprise Data Model

Current Data Inventory

Standard or Corporate Business Language

Conclusion of Hybrid Approach

Chapter 19 Dimensional Warehouses from Enterprise Models

Dimensional Databases from Enterprise Data Models

Warehouse Architecture

Dimensional Model Concepts

Review of Basic Components of Dimensional Models

Differences between Dimension and Fact Tables

Star Schemas

Star Schema Design Approach

Enterprise Data Warehouse Design

Structure Design

Categorize the Entities

Identify Dependency Chains

Produce Dimensional Models

Options for Dimensional Design

The Flat Table Schema

The Stepped Table Schema

Simple Star Schemas

Snowflake Schemas

Star Schema Clusters

Review of Design Options

Chapter 20 The Enterprise Data Warehouse

Enterprise Data Warehouses

Why Would You Want an Enterprise Data Warehouse?

Enterprise Data Warehouse Defined

What Are the Important EDW Driving Forces?

The Best Practices for EDW Implementation

Enterprise Data Architecture Implementation Methods

The Top-Down Approach

The Bottom-Up Approach

Your Choices

Preliminary Conclusion

The Hybrid Approach

Implementation Summary

Chapter 21 Object and Object/Relational Databases

Object Oriented Data Architecture

Sample Object Oriented Design Concept: Wiring Money

Examples of Different Actions

Elements of Object Oriented Design: Overriding

Analogy and Problem Solving

Coping with Complexity

Interconnections: The Perpetrator of Complexity

Assembler Languages

Procedures and Functions

Modules

Parameter Passing

Abstract Data Types

Objects with Parameter Passing

Object Oriented Architectures Summary

Enhanced Entity Relationship Concepts

Subclasses and Superclasses

Attribute Inheritance

Specialization

Generalization

Generalization Hierarchies

Physical Data Design Considerations

Messaging

Object Identity

Type “Generators” and Type Constructors

Summary

Chapter 22 Distributed Databases

Some Distributed Concepts

The Distributed Model

How Does It Work?

Distributed Data Design Concepts

Fragmentation

Replication

Homogeneous Distributed Model

Federated or Heterogeneous Distributed Model

Distributed DBMSs

Reliability and Availability

Controlled Data Sharing

Performance

Qualities Required in a DDBMS

Other Factors

An Overview of Client Server

Functionality within Client Server

A Typical DDBMS

Distribution Transparency

Types of DDBMSs

Individual Site Failure’s Effect on Data Integrity

Individual Site Failure‘s Effect on Traffic Flow

Communication Failure

Distributed Commitment

Distributed Deadlocks

Summary

Index






Details

No. of pages:
448
Language:
English
Copyright:
© Morgan Kaufmann 2011
Published:
Imprint:
Morgan Kaufmann
eBook ISBN:
9780123851277
Paperback ISBN:
9780123851260

About the Author

Charles Tupper

Reviews

I am extremely thrilled that Mr. Tupper has decided to write this book. This book would fill a void in knowledge and know-how in the area of data administration and architecture. Mr. Tupper built over the years an impressive expertise and authority on the subject of enterprise data architecture.

Daniel Fitzpatrick, Principal Consultant, Nakama Consulting Group

I see a wealth of information ranging from technical reference information to higher level concepts and principles. Overall a very comprehensive guide where some sections can be read in a flowing manner to enhance understanding of the topic and other sections can be flipped to/from to provide greater detail and context.

Lynn Rivera, Consultant, LMR Consulting

Ratings and Reviews