Building the Data Warehouse
by Inmon, William H.Format: Paperback
Pub. Date: 1992-01-01
Publisher(s): John Wiley & Sons Inc
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Summary
"Data warehouses provide a much-needed strategy for organizations to collect, store, and analyze vast amounts of business data. As businesses expand both brick-and-mortar and online activities, the field of data warehousing has become increasingly important. Since it was first published in 1990, W. H. Inmon's Building the Data Warehouse has been the bible of data warehousing - it is the book that launched the data warehousing industry and it remains the preeminent introduction to the subject. This new edition covers the latest developments with this technology, many of which have been pioneered by Inmon himself."--BOOK JACKET.
Author Biography
W. H. Inmon is the acknowledged "Father of Data Warehousing" and a partner in www.billinmon.com
Table of Contents
| Preface for the Second Edition | p. xiii |
| Preface for the Third Edition | p. xiv |
| Acknowledgments | p. xix |
| About the Author | p. xx |
| Evolution of Decision Support Systems | p. 1 |
| The Evolution | p. 2 |
| The Advent of DASD | p. 4 |
| PC/4GL Technology | p. 4 |
| Enter the Extract Program | p. 5 |
| The Spider Web | p. 6 |
| Problems with the Naturally Evolving Architecture | p. 6 |
| Lack of Data Credibility | p. 6 |
| Problems with Productivity | p. 9 |
| From Data to Information | p. 12 |
| A Change in Approach | p. 15 |
| The Architected Environment | p. 16 |
| Data Integration in the Architected Environment | p. 19 |
| Who Is the User? | p. 19 |
| The Development Life Cycle | p. 21 |
| Patterns of Hardware Utilization | p. 22 |
| Setting the Stage for Reengineering | p. 23 |
| Monitoring the Data Warehouse Environment | p. 25 |
| Summary | p. 28 |
| The Data Warehouse Environment | p. 31 |
| The Structure of the Data Warehouse | p. 35 |
| Subject Orientation | p. 36 |
| Day 1-Day n Phenomenon | p. 41 |
| Granularity | p. 43 |
| The Benefits of Granularity | p. 45 |
| An Example of Granularity | p. 46 |
| Dual Levels of Granularity | p. 49 |
| Exploration and Data Mining | p. 53 |
| Living Sample Database | p. 53 |
| Partitioning as a Design Approach | p. 55 |
| Partitioning of Data | p. 56 |
| Structuring Data in the Data Warehouse | p. 59 |
| Data Warehouse: The Standards Manual | p. 64 |
| Auditing and the Data Warehouse | p. 64 |
| Cost Justification | p. 65 |
| Justifying Your Data Warehouse | p. 66 |
| Data Homogeneity/Heterogeneity | p. 69 |
| Purging Warehouse Data | p. 72 |
| Reporting and the Architected Environment | p. 73 |
| The Operational Window of Opportunity | p. 74 |
| Incorrect Data in the Data Warehouse | p. 76 |
| Summary | p. 77 |
| The Data Warehouse and Design | p. 81 |
| Beginning with Operational Data | p. 82 |
| Data/Process Models and the Architected Environment | p. 87 |
| The Data Warehouse and Data Models | p. 89 |
| The Data Warehouse Data Model | p. 92 |
| The Midlevel Data Model | p. 94 |
| The Physical Data Model | p. 98 |
| The Data Model and Iterative Development | p. 102 |
| Normalization/Denormalization | p. 102 |
| Snapshots in the Data Warehouse | p. 110 |
| Meta Data | p. 113 |
| Managing Reference Tables in a Data Warehouse | p. 113 |
| Cyclicity of Data-The Wrinkle of Time | p. 115 |
| Complexity of Transformation and Integration | p. 118 |
| Triggering the Data Warehouse Record | p. 122 |
| Events | p. 122 |
| Components of the Snapshot | p. 123 |
| Some Examples | p. 123 |
| Profile Records | p. 124 |
| Managing Volume | p. 126 |
| Creating Multiple Profile Records | p. 127 |
| Going from the Data Warehouse to the Operational Environment | p. 128 |
| Direct Access of Data Warehouse Data | p. 129 |
| Indirect Access of Data Warehouse Data | p. 130 |
| An Airline Commission Calculation System | p. 130 |
| A Retail Personalization System | p. 132 |
| Credit Scoring | p. 133 |
| Indirect Use of Data Warehouse Data | p. 136 |
| Star Joins | p. 137 |
| Supporting the ODS | p. 143 |
| Summary | p. 145 |
| Granularity in the Data Warehouse | p. 147 |
| Raw Estimates | p. 148 |
| Input to the Planning Process | p. 149 |
| Data in Overflow? | p. 149 |
| Overflow Storage | p. 151 |
| What the Levels of Granularity Will Be | p. 155 |
| Some Feedback Loop Techniques | p. 156 |
| Levels of Granularity-Banking Environment | p. 158 |
| Summary | p. 165 |
| The Data Warehouse and Technology | p. 167 |
| Managing Large Amounts of Data | p. 167 |
| Managing Multiple Media | p. 169 |
| Index/Monitor Data | p. 169 |
| Interfaces to Many Technologies | p. 170 |
| Programmer/Designer Control of Data Placement | p. 171 |
| Parallel Storage/Management of Data | p. 171 |
| Meta Data Management | p. 171 |
| Language Interface | p. 173 |
| Efficient Loading of Data | p. 173 |
| Efficient Index Utilization | p. 175 |
| Compaction of Data | p. 175 |
| Compound Keys | p. 176 |
| Variable-Length Data | p. 176 |
| Lock Management | p. 176 |
| Index-Only Processing | p. 178 |
| Fast Restore | p. 178 |
| Other Technological Features | p. 178 |
| DBMS Types and the Data Warehouse | p. 179 |
| Changing DBMS Technology | p. 181 |
| Multidimensional DBMS and the Data Warehouse | p. 182 |
| Data Warehousing across Multiple Storage Media | p. 188 |
| Meta Data in the Data Warehouse Environment | p. 189 |
| Context and Content | p. 192 |
| Three Types of Contextual Information | p. 193 |
| Capturing and Managing Contextual Information | p. 194 |
| Looking at the Past | p. 195 |
| Refreshing the Data Warehouse | p. 195 |
| Testing | p. 198 |
| Summary | p. 198 |
| The Distributed Data Warehouse | p. 201 |
| Types of Distributed Data Warehouses | p. 202 |
| Local and Global Data Warehouses | p. 202 |
| The Technologically Distributed Data Warehouse | p. 220 |
| The Independently Evolving Distributed Data Warehouse | p. 221 |
| The Nature of the Development Efforts | p. 222 |
| Completely Unrelated Warehouses | p. 224 |
| Distributed Data Warehouse Development | p. 226 |
| Coordinating Development across Distributed Locations | p. 227 |
| The Corporate Data Model-Distributed | p. 228 |
| Meta Data in the Distributed Warehouse | p. 232 |
| Building the Warehouse on Multiple Levels | p. 232 |
| Multiple Groups Building the Current Level of Detail | p. 235 |
| Different Requirements at Different Levels | p. 238 |
| Other Types of Detailed Data | p. 239 |
| Meta Data | p. 244 |
| Multiple Platforms for Common Detail Data | p. 244 |
| Summary | p. 245 |
| Executive Information Systems and the Data Warehouse | p. 247 |
| EIS-The Promise | p. 248 |
| A Simple Example | p. 248 |
| Drill-Down Analysis | p. 251 |
| Supporting the Drill-Down Process | p. 253 |
| The Data Warehouse as a Basis for EIS | p. 254 |
| Where to Turn | p. 256 |
| Event Mapping | p. 258 |
| Detailed Data and EIS | p. 261 |
| Keeping Only Summary Data in the EIS | p. 262 |
| Summary | p. 263 |
| External/Unstructured Data and the Data Warehouse | p. 265 |
| External/Unstructured Data in the Data Warehouse | p. 268 |
| Meta Data and External Data | p. 269 |
| Storing External/Unstructured Data | p. 271 |
| Different Components of External/Unstructured Data | p. 272 |
| Modeling and External/Unstructured Data | p. 273 |
| Secondary Reports | p. 274 |
| Archiving External Data | p. 275 |
| Comparing Internal Data to External Data | p. 275 |
| Summary | p. 276 |
| Migration to the Architected Environment | p. 277 |
| A Migration Plan | p. 278 |
| The Feedback Loop | p. 286 |
| Strategic Considerations | p. 287 |
| Methodology and Migration | p. 289 |
| A Data-Driven Development Methodology | p. 291 |
| Data-Driven Methodology | p. 293 |
| System Development Life Cycles | p. 294 |
| A Philosophical Observation | p. 294 |
| Operational Development/DSS Development | p. 294 |
| Summary | p. 295 |
| The Data Warehouse and the Web | p. 297 |
| Supporting the Ebusiness Environment | p. 307 |
| Moving Data from the Web to the Data Warehouse | p. 307 |
| Moving Data from the Data Warehouse to the Web | p. 308 |
| Web Support | p. 309 |
| Summary | p. 310 |
| ERP and the Data Warehouse | p. 311 |
| ERP Applications Outside the Data Warehouse | p. 312 |
| Building the Data Warehouse inside the ERP Environment | p. 314 |
| Feeding the Data Warehouse through ERP and Non-ERP Systems | p. 314 |
| The ERP-Oriented Corporate Data Warehouse | p. 318 |
| Summary | p. 320 |
| Data Warehouse Design Review Checklist | p. 321 |
| When to Do Design Review | p. 322 |
| Who Should Be in the Design Review? | p. 323 |
| What Should the Agenda Be? | p. 323 |
| The Results | p. 323 |
| Administering the Review | p. 324 |
| A Typical Data Warehouse Design Review | p. 324 |
| Summary | p. 342 |
| Appendix | p. 343 |
| Glossary | p. 385 |
| Reference | p. 397 |
| Index | p. 407 |
| Table of Contents provided by Syndetics. All Rights Reserved. |
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