Data Architecture

Data Architecture, 1st Edition

From Zen to Reality

Data Architecture, 1st Edition,Charles Tupper,ISBN9780123851260


Morgan Kaufmann




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Find proven methods and technologies to solve the complex issues dealing with data

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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


    Data Architecture: From Zen to Reality provides an introduction to the basic principles of data architecture, focusing on the development and implementation of enterprise-level information architecture. The book is organized into five sections. Section 1 discusses the data architecture and data design principles needed to reintroduce architecture into the business and software development process. Section 2 deals with the business and organizational issues of modern businesses and how structured and architected approaches may help them remain flexible and responsive. Section 3 focuses on the software-application development process, defining tools, techniques, and methods that ensure repeatable results. Section 4 discusses the artifact results of the process and the ways to make output products more efficient in real-world environments. Section 5 covers specialty databases and the various issues that arise in the business data processing environment, including data warehousing, objects and objects relational databases, and distributed databases. This book was written for people in business management involved with corporate data issues and information technology decisions. It is also a reference tool for those in a higher-level education process involved in data or information technology management.


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

    Charles Tupper

    Data Architecture, 1st Edition



    Section One: The Principles

    1: Understanding Architectural Principles

    1.1 Architecture Definition

    1.2Design Problem Definition

    1.3 Patterns and Pattern Usage

    1.4 Concepts for Pattern Usage

    1.5 Information Architecture

    1.6 Structure works!

    1.7 Architecture Problems

    1.8 Architectural Solutions

    1.9 The idea of ‘Form Follows Function’

    1.10 Guideline: Composition and Environment

    1.11 Guideline: Evolution

    1.12 Guideline: Current and Future

    1.13 Data Policies (Governance), the Foundation Building Codes

    1.14 Data Policy Principles

    1.15 References

    2: Enterprise Architecture Frameworks and Methodologies

    2.1 Architecture Frameworks

    2.2 A brief history of Enterprise Architecture

    2.3 The Zachman framework for Enterprise Architecture

    2.4 The Open Group Architecture Framework (TOGAF)

    2.5 The Federal Enterprise Architecture (FEA)

    2.6 The Gartner Process

    2.7 Enterprise Data Architectures

    2.8 Enterprise Models

    2.9 The Enterprise Data Model

    2.10 Importance of the Enterprise Data Model

    2.11 Object Concepts: Types and Structures within Databases

    2.12 Inheritance

    2.13 Object Life Cycles

    2.14 Relationships and Collections

    2.15 Object Frameworks:

    2.16 Object Framework Programming

    2.17 Pattern Based Frameworks

    2.18 Architecture Patterns in Use

    2.19 US Treasury Architecture Development Guidance (TADG)

    2.20 TADG Pattern Content

    2.21 TADG Architecture Patterns

    2.22 IBM Patterns for e-Business

    2.23 Enterprise Data Model Implementation Methods 

    3. Enterprise Level Data Architecture Practices

    3.1 Enterprise Level Architectures

    3.2 System Architectures

    3.3 Enterprise Data Architectures

    3.4 Enterprise Technology Architectures

    3.5 Enterprise Architecture Terminology - Business terms

    3.6 The Enterprise Model

    3.7 The Enterprise Data Architecture from a Development Perspective

    3.8 Subject Area Drivers

    3.9 Naming and Object Standards

    3.10 Data Sharing

    3.11 Data Dictionary-Metadata Repository

    3.12 Domain Constraints in Corporate and Non-Corporate Data

    3.13 Organizational Control Components

    3.14 Data Administration.

    3.15 Database Administration.

    3.16 Setting Up a Database Administration Group

    3.17 Repository Management Area and Model Management.

    3.18 References

    4: Understanding Development Methodologies

    4.1 Design Methods

    4.2 Why do we need Development Methodologies?

    4.3 The Beginnings

    4.4 Structured methods

    4.5 Structured Programming

    4.6 Structured Design

    4.7 Structured Analysis

    4.8 Still Having Problems

    4.9 Requirements Definitions

    4.10 Problems with Structured Approaches

    4.11 Personal Computers and the Age of Tools

    4.12 Engineering Concepts Applied

    4.13 Other Principles Utilized

    4.14 The Birth of Information Engineering

    4.15 The Four Tenets of Information Engineering

    4.16 Information Engineering as a Design Methodology

    4.17 The Synergy of Tools and Information Engineering.

    4.18 Problems with Information Engineering

    4.19 Implementing the best of IE while minimizing Expense

    4.20 References:

    Section Two: The Problem

    5: Business Evolution

    5.1 The Problem of Business Evolution

    5.2 Expansion and Function Separation

    5.3 Separate Function Communication.

    5.4 Manual Data Redundancy

    5.5 Management Organization and Data.

    5.6 Data Planning and Process Planning

    5.7 Corporate Architecture

    5.8 Using Nolan’s Stages of Growth

    5.9 Problems with Older Organizations

    5.10 Business Today

    5.11 When will it end

    5.12 What can we do about it?

    5.13 Generic Subject Areas for Corporate Architectures

    5.14 Corporate Information Groupings or Functional Areas

    5.15 Corporate Knowledge

    5.16 References

    6 Business Organizations

    6.1 Purpose and Mission of the Organization.

    6.2 Ideology, Mission and Purpose

    6.3 Design with the Future of the Organization in Mind

    6.4 Generalize for Future Potential Directions

    6.5 Organizational Structure

    6.6 What are the Basic Functions in an Organization?

    6.7 The Information Needs of Management

    6.8 Organizations Don’t Know What They Don’t Know

    6.9 Information Strategy for Modern Business

    6.10 Maximization of the Value of Information

    6.11 Loci of forces in the Organization

    6.12 References

    7. Productivity inside the Data Organization

    7.1 Information Technology

    7.2 What Is Information Technology?

    7.3 Trends in Information Technology

    7.4 Vendor Software Development

    7.5 The Other Option

    7.6 Trends in Organizational Change

    7.7 Productivity

    7.8 Explanations for the Anomaly in Productivity

    7.9 ‘Business has evolved and is using the benefits’ Theory

    7.10 ‘Businesses are still evolving’ Theory

    7.11 ‘It is just evolutionary change’ Theory

    7.12 Information Technology and its impact on Organizations

    7.13 Why Invest in Information Technology?

    7.14 Ineffective Use of Information Technology

    7.15 Other Impediments to Organizational Efficiency

    7.16 Organizational Impediments to Information Technology

    7.17 Technological Solutions for Information Technology

    7.18 Human Resource issues in Information Technology

    7.19 Quality of the Workforce

    7.20 Summary of the Discussion of the Anomaly in Information Technology

    7.21 Maximizing the Use of Information Technology

    7.22 References:

    8. Solutions That Cause Problems

    8.1 Downsizing and Organizational Culture

    8.2 Downsizing Defined

    8.3 Culture Change

    8.4 Organizational Level Analysis

    8.5 Organizational/ Individual Level Analysis

    8.6 Downswing’s Impact on Culture

    8.7 A Different Approach to Culture Change and Downsizing

    8.8 Conclusion for Downsizing

    8.9 Outsourcing

    8.10 Rapid Application Development

    8.11 References

    Section Three: The Process

    9. Data Organization Practices

    9.1 Fundamentals of all Data Organization Practices

    9.2 Corporate Data Architecture

    9.3 Corporate Data Policy

    9.4 Architecture Team

    9.5 Design Team

    9.6 Develop the Project Structure

    9.7 Scope Definition

    9.8 Project Plan

    9.9 Data Architecture and Strategic Requirements Planning

    9.10 Data Gathering and Classification

    9.11 Business Area Data Modeling

    9.12 Current Data Inventory Analysis

    9.13 Data and Function Integration

    9.14 Procedure Definition via Functional Decomposition

    9.15 Process Use Identification

    9.16 New Function Creation

    9.17 Utilization Analysis via Process Use Mapping

    9.18 Access Path Mapping

    9.19 Entity Cluster Development and Logical Residence Planning

    9.20 Application Development Templates

    9.21 Quality Assurance Metrics

    9.22 Maintenance Control Process

    9.23 The Software Development Methods

    9.24 Architectural Development Methods

    9.25 Atomic Process Models

    9.26 Entity Process Models

    9.27 The Unified Method

    9.28 References:

    10. Models and Model Repositories

    10.1What are Models and How Did they come about?

    10.2 Data Models Introduction

    10.3 What does Modeling do for us?

    10.4 Process Models Introduction.

    10.5 Process Models, Why?

    10.6 How are Automated Models developed?

    10.7 How Are Models Retained?

    10.8 Model Repository Policy and Approach

    10.9 Shared Repository Objects

    10.10 Model Driven Releases

    10.11 Supporting an Application Release

    10.12 Version Type

    10.13 Participation

    10.14 Seamless Development Control Process

    10.15 Test Environments, Releases, and Databases

    10.16 Release Stacking

    10.17 Emergency Corrections

    10.18 Emergency Correction Procedures

    10.19 PTF Implementation for Shared Batch and On-line Objects

    10.20 References:

    11. Model Constructs and Model Types

    11.1 Data Model Constructs

    11.2 Application Audience and Services

    11.3 Entities

    11.4 Attributes

    11.5 Relationships

    11.6 Primary Identifiers

    11.7 Entity Types

    11.8 Entity Relationship Diagrams

    11.9 Types of Relationships

    11.10 Model Types

    11.11 Physical-level design

    11.12 Primary Keys

    11.13 Normalization

    11.14 Denormalization

    11.15 Over-normalization

    11.16 Domains

    11.17 Domain Constraints

    11.18 Reference Data

    11.19 Generic Domain Constraint Constructs

    11.20 References

    12. Time as a Dimension of the Database

    12.1 What is to be done with historical data?

    12.2 Application History

    12.3 Classes and Characteristics

    12.4 Current Occurrence

    12.5 Simple History

    12.6 Bounded Simple History

    12.7 Complex History

    12.8 Logically Modeling History

    12.9 Physical Design of History

    12.10 Physical Implementation of History

    12.11 Performance Tuning

    12.12 Finding Patterns

    12.13 Tips and Techniques for Implementing History

    12.14 Types of Systems

    12.15 Physical Structure

    12.16 Dimensional History

    12.17 References

    12.18 Section Four: The Product

    13. Concepts of Clustering, Indexing and Structures

    13.1 Cluster Analysis

    13.2 What is a Cluster?

    13.3 Cluster Theory Applied

    13.4 Inserts

    13.5 Updates

    13.6 Deletes

    13.7 Physical Structure

    13.8 Key History and Development

    13.9 Primary Key

    13.10 Foreign Keys

    13.11 Foreign Key Propagation

    13.12 Candidate Keys

    13.13 Natural Keys

    13.14 Engineered Keys

    13.15 Surrogate Keys

    13.16 High Water Key

    13.17 One of a Kind Key

    13.18 Other Specialized Keys

    13.19 References

    Section Four: The Product

    14. Basic Requirements for Physical Design

    14.1 Requirements for Physical Design

    14.2 How Much Data?

    14.3 History

    14.4 Population Quantification of Application Data

    14.5 Concurrency

    14.6 Security / Audit

    14.7 Audit

    14.8 Archive/Purge

    14.9 Recovery/Restart

    14.10 Sort / Search Requirements

    14.11 Reorganization and Restructuring

    14.12 Data Integrity

    14.13 Referential Integrity

    14.14 Data Access

    14.15 Privacy Requirements

    14.16 Suggested Reading

    15. Physical Database Considerations

    15.1 Three Level Architecture

    15.2 Data Independence

    15.3 Data Base Languages

    15.4 Classification of Data Base Management Systems

    15.5 Factors Impacting Physical Database Design

    15.6 Analysis of Queries, Reporting and Transactions

    15.7 Queries, Reports and Transactions

    15.8 Interpretation of the Functional Decomposition

    15.9 Event Identification

    15.10 Process Use Identification Reviewed

    15.11 Utilization Analysis via Process Use Mapping

    15.12 Analysis of expected frequency of Insert, Delete, Update

    15.13 Other Physical Database Design Considerations

    15.14 Population on the Database

    15.15 References

    15.16 Section Four: The Product

    16. Interpretation of Models

    16.1 Physical Design Philosophy

    16.2 Objectives

    16.3 The Entity Relationship Model

    16.4 Interaction Analysis

    16.5 The CRUD Matrix

    16.6 Entity Life Cycle Analysis/ Entity State transition Diagrams

    16.7 Process Dependency Scope and Process Dependency Diagram

    16.8 Event Analysis

    16.9 Process Logic Diagrams

    16.10 Interaction Analysis Summary

    16.11 Changes to ER Models

    16.12 ERD Denormalization

    16.13 Collapse of 1:1 relationships

    16.14 Actions on Multiple Relationships

    16.15 Resolution of Circular References

    16.16 Resolution of Duplicate Propagated Keys

    16.17 Access Level Denormalization

    16.18 Consolidation of Entities

    16.19 Implement Repeating Groups

    16.20 Introduce Redundancy

    16.21 Access Path Mapping

    16.22 Conclusion

    16.23 References

    Section Five: Specialized Databases

    17. Data Warehouses I

    17.1 Early analysis in this area

    17.2 Keen & Scott Morton

    17.3 Decision discussion

    17.4 Components of decisions

    17.5 Responsibility

    17.6 Report Writers and Query engines

    17.7 Warehouses vs Reporting Databases

    17.8 Higher level of abstraction

    17.9 Based on perceived business use

    17.10 Structure Evolution

    17.11 Warehouse Components

    17.12 Why can’t OLTP Data Stores be used?

    17.13 DSS Requirements

    17.14 Warehouse Characteristics

    17.15 Warehouse Modeling

    17.16 Warehouse Modeling is dependent on Architectures

    17.17 Fundamental Benefits:

    17.18 Enterprise Level Data Architecture

    17.19 References:

    18. Data Warehouses II

    18.1 Reprise

    18.2 Background

    18.3 Many types and levels of Data

    18.4 Data Modeling Definitions

    18.5 Logical to Physical Transformation

    18.6 Confusion over Terms such as Entity Relational model

    18.7 Placement of Models

    18.8 Denormalization and the Dimensional Model

    18.9 Dimensional Model Evaluation

    18.10 Data Evolution

    18.11 What are the choices?

    18.12 Applicability of the Dimensional and Relational and Hybrid Models

    18.13 Dimensional Architecture

    18.14 Where is the Relational Data Warehouse best suited?

    18.15 Where is Dimensional Best Suited?

    18.16 Hybrid ER-Dimensional

    18.17 Problems Associated with the Hybrid Approach.

    18.18 Target Enterprise Architecture

    18.19 Building an Enterprise Data Model

    18.20 Current Data Inventory

    18.21 Standard or corporate business language

    18.22 Conclusion of Hybrid Approach

    18.23 References

    18.24 Section Five: Specialty Databases

    19. Dimensional Warehouses from Enterprise Models

    19.1 Dimensional Databases from Enterprise Data Models

    19.2 Warehouse Architecture

    19.3 Dimensional Modeling

    19.4 Dimensional Model Concepts

    19.5 Review of Basic Components of Dimensional Models

    19.6 Differences between Dimension and Fact Tables

    19.7 Star Schema

    19.8 Star Schema Design Approach

    19.9 Enterprise Data Warehouse Design

    19.10 Structure Design

    19.11 Categorize the Entities

    19.12 Identify Dependency Chains

    19.13 Produce Dimensional Models

    19.14 Options for Dimensional Design

    19.15 The Flat Table Schema

    19.16 The Stepped Table Schema

    19.17 Star Schema

    19.18 Snowflake Schema

    19.19 Star Schema Clusters

    19.20 Iterate to Refine the Design

    19.21 Review of Design options

    20. The Enterprise Data Warehouse

    20.1 Enterprise Data Warehouses

    20.2 Why would you want an Enterprise Data Warehouse?

    20.3 Enterprise Data Warehouse Defined

    20.4 What are the important EDW Drivers?

    20.5 The Best Practices for EDW implementation

    20.6 Enterprise Data Architecture Implementation Methods

    20.7 Top Down approach

    20.8 Bottom Up

    20.9 These are your Choices

    20.10 Preliminary Conclusion

    20.11 Hybrid Approach

    20.12 Implementation summary

    20.13 References:

    21. Object and Object/Relational Databases

    21.1 Object Oriented Data Architecture

    21.2 Illustration of OOD (Object Oriented Design) Concepts - Wiring Money

    21.3 Examples of Different Actions

    21.4 Elements of OOD - Overriding

    21.5 Analogy and Problem Solving

    21.6 Coping with Complexity

    21.7 Interconnections - the Perpetrator of Complexity

    21.8 Assembler Languages

    21.9 Procedures and Functions

    21.10 Modules

    21.11 Parameter Passing

    21.12Abstract Data Types

    21.13 Objects -like Abstract Data Type’s with Parameter Passing

    21.14 Object Oriented Architectures Summary

    21.15 EER Concepts that support Object and Relational Models

    21.16 Subclasses and Superclasses

    21.17 Attribute Inheritance

    21.18 Specialization

    21.19 Generalization Hierarchies

    21.20 Multiple Inheritance


    21.22 Object Identity

    21.23 Type ‘Generators’ and Type Constructors

    21.24 Summary

    21.25 References:

    22. Distributed Databases

    22.1 Some Distributed concepts

    22.2 The Distributed Model(s)

    22.3 How Does It Work?

    22.4 Distributed Data Design Concepts

    22.5 Fragmentation

    22.6 Replication

    22.7 Homogeneous Distributed Model

    22.8 Federated or Heterogeneous Distributed Model

    22.9 Reliability and Availability

    22.10 Controlled Data Sharing

    22.11 Performance

    22.12 Qualities required in a DDBMS

    22.13 Other Factors

    22.14 An Overview of Client Server

    22.15 Functionality within Client Server

    22.16 A Typical DDBMS

    22.17 Distribution Transparency

    22.18 Types of DDBMSs

    22.19 Problems in DDBMSs

    22.20 Individual Site Failure’s Effect on Data Integrity

    22.21 Individual Site Failure‘s Effect on Traffic Flow

    22.22 Communication Failure

    22.23 Distributed Commitment

    22.24 Distributed Deadlocks

    22.25 Summary

    22.26 References

    Quotes and 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


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