Business Metadata: Capturing Enterprise Knowledge is the first book that helps businesses capture corporate (human) knowledge and unstructured data, and offer solutions for codifying it for use in IT and management. Written by Bill Inmon, one of the fathers of the data warehouse and well-known author, the book is filled with war stories, examples, and cases from current projects. It includes a complete metadata acquisition methodology and project plan to guide readers every step of the way, and sample unstructured metadata for use in self-testing and developing skills.
This book is recommended for IT professionals, including those in consulting, working on systems that will deliver better knowledge management capability. This includes people in these positions: data architects, data analysts, SOA architects, metadata analysts, repository (metadata data warehouse) managers as well as vendors that have a metadata component as part of their systems or tools.
First book that helps businesses capture corporate (human) knowledge and unstructured data, and offer solutions for codifying it for use in IT and management.
Written by Bill Inmon, one of the fathers of the data warehouse and well-known author, and filled with war stories, examples, and cases from current projects.
Very practical, includes a complete metadata acquisition methodology and project plan to guide readers every step of the way.
Includes sample unstructured metadata for use in self-testing and developing skills.
The market includes IT professionals, including those in consulting, working on systems that will deliver better knowledge management capability. This includes people in these positions: data architects; data analysts, SOA architects; metadata analysts, repository (metadata data warehouse) managers. Also, vendors that have a metadata component as part of their systems or tools.
Business Metadata The Quest for Business Understanding Section I: Rationale and Planning
- What is Business Metadata
a. What is Metadata? i. A brief history of metadata ii. Types of Metadata
- Structured versus Unstructured MD b. What is Business MD? i. Some examples and usage c. When does data become MD? d. Who are the users of business metadata? e. A grid of metadata f. Business metadata and reference files
- The Value and Benefits of Business Metadata
a. Metadata Provides Context: i. Example: the number "42" ii. The road sign analogy iii. The library card catalog analogy b. Business Metadata Provides Historical Perspective c. Contextual Benefits in Analytical Processing i. Simple Reports ii. Drill Downs iii. Exception Reporting iv. Heuristic Analysis v. KPI Analysis vi. Multivariate Analysis vii. Pattern Analysis viii. Spreadsheets ix. Screens d. Hidden MD e. The Information Supply Chain i. The Business Feedback Loop
- Who is responsible for Business Metadata? a. Who Has the Most to Gain from Business Metadata? b. Stewardship versus Ownership c. Business versus Technical Ownership d. Is Stewardship of Business Metadata any different? i. Data Stewardship ii. Metadata Stewardship iii. Business Metadata Stewardship e. Stewardship Challenges f. Why should MD be funded? (Bill) i. How and why should business metadata be funded
- The business case for business metadata ii. The search process – from a visceral standpoint
- Follow up from Subsequent Chapter
- The end user buying departmental tools
- The technician buying a repository iii. Blending everything together – a combined approach iv. Life without an organized approach to business metadata v. Funding Models
- Should MD be funded by ROI?
- What are the funding options (LOB or centralized IT, usage or overhead)? vi. Funding a Corporate Knowledge Base
- Business Metadata, Communication and Search (BKO) a. The need for better communication b. Faulty communication causes bad business practices c. Much time is lost in the organization due to not being able to find things i. Losing Your Car Keys Analogy d. The need for structured definitions e. The Role of Taxonomies
- OUT; this chapter rolled into Stewardship Section II: How-To
- How do you initiate a MD project? a. What are the options? b. Planning Guidelines i. Examples in MSProject c. Defining the Business Metadata Strategy and Goals i. Strategy & Goals: Business Focus ii. Strategy & Goals: Technical Focus d. Complete enterprise strategy & goals e. Constructing a Strategic Plan f. Examples in MSWord
- Technology Infrastructure for Metadata a. MD Modeling and Design (CWM and OMG) i. Special Challenges of Business Metadata b. What does business metadata integration entail? i. Similarity to a data warehouse c. Should be treated like a data warehouse project d. Buy versus Build Alternatives e. Centralized MD Implementation i. Federated ii. Repository f. Distributed MD Implementation g. Hybrid MD Implementation h. ETL for business metadata i. Semantic integration
- Business Metadata Capture a. Business MD scope i. Vulcan mind meld ii. Intro to Unstructured MD iii. Business Rules iv. Definitions v. Domains b. Business Metadata Capture from Technical MD i. Enterprise Model layer ii. Conceptual Model layer iii. Logical Model layer iv. Physical Model layer c. Special Challenges of Business Metadata i. Capturing knowledge from Business People d. Capturing knowledge from Individuals e. Capturing knowledge from Groups i. The Socialization Factor ii. Wikis and Collabs f. PR: Encouraging and Incentivizing g. Special Stewardship Approaches i. Proactive vs. Reactive ii. "Governance Lite" 8.5 Business Metadata Capture from Existing Data 8.5.1 Technical Sources of MD 126.96.36.199 ERP 188.8.131.52 Reports 184.108.40.206 Spreadsheets 220.127.116.11 Documents 18.104.22.168 DBMS system catalogs 22.214.171.124 OLAP 126.96.36.199 ETL 188.8.131.52 Legacy System 184.108.40.206 Data Warehouse 8.5.2 Editing the metadata as it passes into the metadata repository 220.127.116.11 Automation of the editing 8.5.3 Granularizing metadata 8.5.4 Expanding definitions & descriptions 8.5.5 Synonym resolution 8.5.6 Homonym Resolution 8.5.7 Manual Metadata editing 8.5.8 Turning Technical MD into Business MD
- MD Data Delivery a. Avoid Roach Motel b. Who are users? How do you deliver it? c. Active vs. Passive Delivery d. MD & DW e. MD & Marts f. MD & Operational Systems g. Example: Corporate Glossary Section III: Special Categories of Business MD 9.5 Data Quality a. Why is data quality business metadata? b. Purpose of Data Quality c. Using a Data Quality Methodology d. Expressing data quality into the language of the business
- Semantics & Ontologies a. Semantics: The study of meaning b. Semantic frameworks i. Controlled Vocabulary ii. Taxonomy iii. Ontology iv. Chart showing Semantic Richness c. Semantics and Business Metadata d. Semantics and Technology i. The Semantic Web ii. SOA iii. Other tools iv. Standards: OWL etc e. Making semantics practical f. Two different uses i. Glossaries/CV ii. Search g. Simple implementations
- Unstructured MD a. Characteristics of Unstructured business metadata b. Where unstructured business metadata resides i. Reports ii. Spreadsheets iii. Text files iv. email c. Examples of unstructured business metadata d. Plucking business metadata out i. An example of finding business metadata in unstructured data e. Relationships among unstructured business metadata objects i. Familial ii. Hierarchy f. Using Unstructured business metadata i. Business metadata and understanding unstructured documents ii. Theming documents using business metadata g. Industrial recognized lists as a basis for understanding documents h. Linguistics i. Marrying structured & unstructured data
- Business Rules a. Why business rules are a type of business metadata b. Business rules and their role in managing the business c. Where do you find business rules? d. Purpose for managing them as metadata e. Business Rules and Rule Engine technology f. Business Rules and the Repository
- Metadata & Compliance
a. Compliance – the issues b. Financial compliance c. Communications compliance d. Types of compliance i. Sarbanes Oxley ii. Basel II iii. HIPAA iv. Patriot Act e. How do you use MD to find compliance data? f. Using business metadata i. As a screen—Finding blather ii. To classify transactions iii. As a means to determine criticality g. Creating the historical record i. Preparing for the audit using business metadata h. An example of business metadata during the compliance process i. Document Retention and Compliance i. Document Retention issues ii. Maintenance of email, iii. Email as a knowledge base & the problems it creates
- Knowledge Management and Business Metadata a. Intersection of Business Metadata and Knowledge Management b. Knowledge Management in Practice i. Knowledge Capture ii. Knowledge Dissemination c. Explicit and Tacit Knowledge d. Building Intellectual capital and the Corporate Knowledgebase e. Social Issues i. Impact of collaboration on Knowledge ii. Graying of the Workforce
Section IV: Putting it All Together
- Summary a. Business Metadata is important b. Business Metadata has been ignored in general discussions of metadata c. Lessons learned in the field d. /What does the future hold? e. Trends f. Resources
Appendix: A: MD Repository Buy Methodology (Sample project plan) B: MD Repository Build Methodology (Sample project plan) C: glossary of terms (the metadata)
- No. of pages:
- © Morgan Kaufmann 2008
- 27th September 2007
- Morgan Kaufmann
- eBook ISBN:
- Paperback ISBN:
Inmon Data Systems, Castle Rock, CO, USA
Project Performance Corporation, Denver, CO, USA
Lowell is responsible for directing thought leadership and advisory services in the Customer Success practice of Collibra. He has been a practitioner in the data management industry for three decades and is recognized as a leader in data governance, analytics and data quality having hands-on experience with implementations across most industries. Lowell is a co-author of the book “Business Metadata; Capturing Enterprise Knowledge”. Lowell is a past adjunct professor at Daniels College of Business, Denver University, a past President and current VP of Education for DAMA-I Rocky Mountain Chapter (RMC), a DAMA-I Charter member and member of the Data Governance Professionals Organization. He is also an author and reviewer on the DAMA-I Data Management Book of Knowledge (DMBOK). He focuses on practical data governance practices and has trained thousands of professionals in data governance, data warehousing, data management and data quality techniques. You can read his Data Governance Blogs at https://www.collibra.com/blog/