Business Metadata: Capturing Enterprise Knowledge (Paperback)
W.H. Inmon, Bonnie O'Neil, Lowell Fryman
- 出版商: Morgan Kaufmann
- 出版日期: 2007-09-01
- 售價: $2,520
- 貴賓價: 9.5 折 $2,394
- 語言: 英文
- 頁數: 312
- 裝訂: Paperback
- ISBN: 0123737265
- ISBN-13: 9780123737267
-
相關分類:
大數據 Big-data、管理與領導 Management-leadership、資料庫
海外代購書籍(需單獨結帳)
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相關主題
商品描述
Description
People have a hard time communicating, and also have a hard time finding business knowledge in the environment. With the sophistication of search technologies like Google, business people expect to be able to get their questions answered about the business just like you can do an internet search. The truth is, knowledge management is primitive today, and it is due to the fact that we have poor business metadata management.
This book is about all the groundwork necessary for IT to really support the business properly. By providing not just data, but the context behind the data. For the IT professional, it will be tactically practical--very "how to" and a detailed approach to implementing best practices supporting knowledge management. And for the the IT or other manager who needs a guide for creating and justifying projects, it will help provide a strategic map.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.
Table of Contents
Business Metadata
The Quest for Business Understanding
Section I: Rationale and Planning
1. What is Business Metadata
a. What is Metadata?
i. A brief history of metadata
ii. Types of Metadata
1. Technical
2. Business
3. 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
2. 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
3. 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
1. The business case for business metadata
ii. The search process – from a visceral standpoint
1. Follow up from Subsequent Chapter
2. The end user buying departmental tools
3. The technician buying a repository
iii. Blending everything together – a combined approach
iv. Life without an organized approach to business metadata
v. Funding Models
1. Should MD be funded by ROI?
2. What are the funding options (LOB or centralized IT, usage or overhead)?
vi. Funding a Corporate Knowledge Base
4. 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
5.
Section II: How-To
6. 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
7. 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
8. 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
8.5.1.1 ERP
8.5.1.2 Reports
8.5.1.3 Spreadsheets
8.5.1.4 Documents
8.5.1.5 DBMS system catalogs
8.5.1.6 OLAP
8.5.1.7 ETL
8.5.1.8 Legacy System
8.5.1.9 Data Warehouse
8.5.2 Editing the metadata as it passes into the metadata repository
8.5.2.1 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
9. 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
10. 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
11. 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
12. 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
13. 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
14. 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
15. 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)
商品描述(中文翻譯)
描述
人們在溝通上遇到困難,也很難在環境中找到商業知識。隨著像Google這樣的搜索技術的精密化,商業人士期望能夠像在網絡搜索一樣獲得有關業務的問題的答案。事實是,知識管理在今天仍然很原始,這是因為我們對商業元數據管理不善。這本書是關於IT真正支持業務所需的所有基礎工作。不僅提供數據,還提供數據背後的上下文。對於IT專業人士來說,這將是具有戰術實用性的書籍,非常實用且詳細地介紹了支持知識管理的最佳實踐的實施方法。對於需要創建和證明項目的IT或其他管理人員,它將幫助提供戰略地圖。
- 第一本幫助企業捕獲公司(人類)知識和非結構化數據的書籍,並提供將其編碼供IT和管理使用的解決方案。
- 由資料倉庫之父之一、著名作家Bill Inmon撰寫,並充滿了來自當前項目的戰爭故事、例子和案例。
- 非常實用,包括完整的元數據獲取方法論和項目計劃,引導讀者每一步。
- 包括用於自我測試和技能開發的樣本非結構化元數據。
目錄
- 商業元數據
- 追求商業理解
- 第一部分:原理和計劃
1. 什麼是商業元數據
- 什麼是元數據?
- 元數據的簡史
- 元數據的類型
- 技術元數據
- 商業元數據
- 結構化與非結構化元數據
- 什麼是商業元數據?
- 商業元數據的一些例子和用途
- 數據何時變成元數據?
- 誰是商業元數據的使用者?
- 元數據網格
- 商業元數據和參考文件
2. 商業元數據的價值和好處
- 元數據提供上下文
- 例子:數字“42”
- 路牌類比
- 圖書館卡片目錄類比
- 商業元數據提供歷史視角
- 分析處理中的上下文優勢
- 簡單報告
- 鑽取
- 異常報告
- 問題分析
- 關鍵績效指標分析
- 多變量分析
- 模式分析
- 電子表格
- 屏幕
- 隱藏的元數據
- 信息供應鏈
- 商業反饋循環
3. 誰負責商業元數據?
- 誰最有可能從商業元數據中獲益?
- 管理權責與所有權
- 商業與技術所有權
- 商業元數據管理是否有所不同?
- 數據管理
- 元數據管理
- 商業元數據管理
- 管理權責的挑戰
- 為什麼應該資助元數據管理?
- 商業元數據的商業案例
- 從直觀角度看搜索過程
- 後續章節的跟進
- 最終用戶購買部門工具
- 技術人員購買存儲庫
- 將所有事物結合在一起-綜合方法
- 沒有組織化商業元數據方法的生活
- 資助