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DW2.0 The Architecture for the Next Generation of Data Warehousing
W. H. Inmon Forest Rim Technology
Derek Strauss Gavroshe
Genia Neushloss Gavroshe
AMSTERDAM • BOSTON • HEIDELBERG • LONDON NEW YORK • OXFORD • PARIS • SAN DIEGO SAN FRANCISCO • SINGAPORE • SYDNEY • TOKYO Morgan Kaufmann Publishers is an imprint of Elsevier.
К MORGAN K A U F M A N N
PUBLISHERS
Contents Preface
xvii
Acknowledgments
xx
About the Authors
xxi
CHAPTER 1
CHAPTER 2
A brief history of data warehousing and first-generation data warehouses
1
Database management systems Online applications Personal computers and 4GL technology The spider web environment Evolution from the business perspective The data warehouse environment What is a data warehouse? Integrating data—a painful experience Volumes of data A different development approach Evolution to the DW2.0 environment The business impact of the data warehouse Various components of the data warehouse environment ETL—extract/transform/load ODS—operational data store Data mart Exploration warehouse The evolution of data warehousing from the business perspective Other notions about a data warehouse The active data warehouse The federated data warehouse approach The star schema approach The data mart data warehouse Building a "real" data warehouse Summary
DW 2.0—a new paradigm DW 2.0—from the business perspective The life cycle of data Reasons for the different sectors Metadata Access of data Structured data/unstructured data
24 24 27 30 31 33 34
viii
Contents
CHAPTER 3
CHAPTER 4
Textual analytics Blather The issue of terminology Specific text/general text Metadata—a major component Local metadata A foundation of technology Changing business requirements The flow of data within DW 2.0 Volumes of data Useful applications DW 2.0 and referential integrity Reporting in DW 2.0 Summary
35 38 38 40 40 43 45 47 48 50 51 52 53 53
DW 2.0 components—about the different sectors
55
The Interactive Sector The Integrated Sector The Near Line Sector The Archival Sector Unstructured processing From the business perspective Summary
55 62 71 76 86 90 92
Metadata in DW 2.0
95
Reusability of data and analysis Metadata in DW 2.0 Active repository/passive repository The active repository Enterprise metadata Metadata and the system of record Taxonomy Internal taxonomies/external taxonomies Metadata in the Archival Sector Maintaining metadata Using metadata—an example From the end-user perspective Summary CHAPTER 5
Fluidity of the DW 2.0 technology infrastructure The technology infrastructure Rapid business changes
The treadmill of change Getting off the treadmill Reducing the length of time for IT to respond Semantically temporal, semantically static data Semantically temporal data Semantically stable data Mixing semantically stable and unstable data Separating semantically stable and unstable data Mitigating business change Creating snapshots of data A historical record Dividing data From the end-user perspective Summary
Spiral methodology—a summary of key features The seven streams approach—an overview Enterprise reference model stream Enterprise knowledge coordination stream Information factory development stream Data profiling and mapping stream Data correction stream Infrastructure stream Total information quality management stream Summary
124 129 129 129 133 133 133 133 134 137
Statistical processing and DW 2.0
141
Two types of transactions Using statistical analysis The integrity of the comparison Heuristic analysis Freezing data Exploration processing The frequency of analysis The exploration facility The sources for exploration processing Refreshing exploration data Project-based data Data marts and the exploration facility Abackflowof data Using exploration data internally
An intellectual road map The data model and business The scope of integration Making the distinction between granular and summarized data Levels of the data model Data models and the Interactive Sector The corporate data model A transformation of models Data models and unstructured data From the perspective of the business user Summary
157 157 158 159 159 161 162 163 164 166 167
Monitoring the DW 2.0 environment
169
Monitoring the DW 2.0 environment The transaction monitor Monitoring data quality A data warehouse monitor The transaction monitor—response time Peak-period processing The ETL data quality monitor The data warehouse monitor Dormant data From the perspective of the business user Summary
169 169 170 171 171 172 174 176 177 178 179
CHAPTER 10 DW 2.0 and security Protecting access to data Encryption Drawbacks The firewall Moving data offline Limiting encryption A direct dump The data warehouse monitor Sensing an attack Security for near line data From the perspective of the business user Summary
CHAPTER 11 Time-variant data All data in DW 2.0—relative to time Time relativity in the Interactive Sector Data relativity elsewhere in DW 2.0 Transactions in the Integrated Sector Discrete data Continuous time span data A sequence of records Nonoverlapping records Beginning and ending a sequence of records Continuity of data Time-collapsed data Time variance in the Archival Sector From the perspective of the end user Summary CHAPTER 12 Theflowof data in DW 2.0 The flow of data throughout the architecture Entering the Interactive Sector The role of ETL Data flow into the Integrated Sector Data flow into the Near Line Sector Data flow into the Archival Sector The falling probability of data access Exception-based flow of data From the perspective of the business user Summary CHAPTER 13 ETL processing and DW 2.0 Changing states of data Where ETL fits From application data to corporate data ETL in online mode ETL in batch mode Source and target An ETL mapping Changing states—an example More complex transformations ETL and throughput ETL and metadata ETL and an audit trail
ETL and data quality Creating ETL Code creation or parametrically driven ETL ETL and rejects Changed data capture ELT From the perspective of the business user Summary CHAPTER 14 DW 2.0 and the granularity manager The granularity manager Raising the level of granularity Filtering data The functions of the granularity manager Home-grown versus third-party granularity managers Parallelizing the granularity manager Metadata as a by-product From the perspective of the business user Summary CHAPTER 15 DW 2.0 and performance Good performance—a cornerstone for DW 2.0 Online response time Analytical response time The flow of data Queues Heuristic processing Analytical productivity and response time Many facets to performance Indexing Removing dormant data End-user education Monitoring the environment Capacity planning Metadata Batch parallelization Parallelization for transaction processing Workload management Data marts Exploration facilities Separation of transactions into classes Service level agreements
Protecting the Interactive Sector Partitioning data Choosing the proper hardware Separating farmers and explorers Physically group data together Check automatically generated code From the perspective of the business user Summary CHAPTER 16 Migration Houses and cities Migration in a perfect world The perfect world almost never happens Adding components incrementally Adding the Archival Sector Creating enterprise metadata Building the metadata infrastructure "Swallowing" source systems ETL as a shock absorber Migration to the unstructured environment From the perspective of the business user Summary CHAPTER 17 Cost justification and DW 2.0 Is DW 2.0 worth it? Macro-level justification A micro-level cost justification Company В has DW 2.0 Creating new analysis Executing the steps So how much does all of this cost? Consider company В Factoring the cost of DW 2.0 Reality of information The real economics of DW 2.0 The time value of information The value of integration Historical information First-generation DW and DW 2.0—the economics From the perspective of the business user Summary
CHAPTER 18 Data quality in DW 2.0 The DW 2.0 data quality tool set Data profiling tools and the reverse-engineered data model Data model types Data profiling inconsistencies challenge top-down modeling Summary CHAPTER 19 DW 2.0 and unstructured data DW 2.0 and unstructured data Reading text Where to do textual analytical processing Integrating text Simple editing Stop words Synonym replacement Synonym concatenation Homographic resolution Creating themes External glossaries/taxonomies Stemming Alternate spellings Text across languages Direct searches Indirect searches Terminology Semistructured data/VALUE = NAME data The technology needed to prepare the data The relational data base Structured/unstructured linkage From the perspective of the business user Summary CHAPTER 20 DW 2.0 and the system of record Other systems of record From the perspective of the business user Summary CHAPTER21 Miscellaneous topics Data marts The convenience of a data mart Transforming data mart data
Monitoring DW 2.0 Moving data from one data mart to another Bad data A balancing entry Resetting a value Making corrections The speed of movement of data Data warehouse utilities Summary CHAPTER 22 Processing in the DW 2.0 environment Summary
326 327 329 330 330 330 331 332 337 339 345
CHAPTER 23 Administering the DW 2.0 environment The data model Architectural administration Defining the moment when an Archival Sector will be needed Determining whether the Near Line Sector is needed Metadata administration Database administration Stewardship Systems and technology administration Management administration of the DW 2.0 environment Prioritization and prioritization conflicts Budget Scheduling and determination of milestones Allocation of resources Managing consultants Summary
