1. Turning Data into Knowledge: Creating and Implementing a Metadata Strategy
Anne Marie Smith

2. Metadata Management Best Practices
12/27/2018
Agenda
Introduction
Metadata Overview
Principles of Metadata Management
Metadata Strategy
Key Roles in Metadata Management
Metadata Quality
Important Aspects of Metadata
Conclusion
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(C) Alabama Yankee Systems, LLC

3. Anne Marie Smith Background
Metadata Management Best Practices
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Anne Marie Smith Background
BA and MBA Management Information Systems (La Salle University)
PhD, Management Information Systems (NorthCentral University)
Consultant in data management, metadata, data warehousing, requirements analysis, systems re-engineering
Certified Project Management Professional (PMP)
Certified Data Management Professional (
Author of over 40 publications and papers
Instructor on varied information systems management topics
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(C) Alabama Yankee Systems, LLC

4. Metadata Management Best Practices
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Definition of "Metadata"
Metadata: "data about data"
Collection of information about the data stored in an application or database
Examples:
Data element definition
Data element business name
Data element systems abbreviation
Data type and data size
Data element source location
Dictionary
All of these pieces of Metadata are of interest to various members of the GA community some only to certain IS staff members, others to business users of the data attempting to navigate through the GA DW
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5. Metadata Management Best Practices
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Data Orientation Movement
Traditional systems development focused on processes, not data as foundation
Data orientation is a major cultural shift
change in methods used to design and deliver systems
change in perception, access and asset management of data and information
Traditional systems - process
Data orientation - cultural change
Change in systems design and delivery
Change in usage of data asset (perceiving, accessing and respecting value)
Sometimes adopting a data orientation requires a reengineering of IS and business communities
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6. Metadata Management Best Practices
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Enterprise View of Data
Data is a sharable resource
Effective use and reuse of data requires an enterprise view of essential concepts, entities and attributes for cross-application and cross-departmental functionality
Enterprise view MUST be generated at the top of an organization, with active commitment and support for efforts
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7. Metadata Management Best Practices
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Goals of Metadata Strategy
Provide business orientation as foundation for sharing data assets across entire organization
Offer recognition of value of data and its components
Develop map for managing expanding information requirements
Highlight importance of central data administration
Address data quality, data integrity, data reuse
Measurement of value of information
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8. Metadata Management Best Practices
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Strategic Plan for Information
Evaluate and choose a systems methodology
Customize methodology for data orientation and business focus
Develop and implement metadata strategy
Integrate new methodology in systems development and maintenance
Strategic Plan for Info needed to ensure the integration of business needs and systems responsibilities
Data orientation and Metadata management are essential to success of information asset management
Methodology should already have a data orientation, and be robust enough to support customization for individual company culture
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9. Metadata Management Best Practices
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Data Administration Objectives
Build a framework for accurately capturing, sharing, distributing, securing and leveraging a company's data resources, including creating and refining data models and establishing and maintaining an enterprise data repository
Strategically plan for a company's future information requirements
Support data self-reliance and efficient use of data in business practices
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10. Principles of Metadata Management
Establish a metadata strategy / policy
Create or adopt a metadata standards set
Establish and maintain data / metadata stewardship role and function
Establish and maintain collection of relevant metadata
Publish relevant metadata
Maintain metadata standards set
Maintain metadata content in all systems
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11. Keys to Metadata Management
Develop metadata strategy before embarking on evaluating, purchasing and installing complex management products
Products / tools are necessary for effective management of metadata
Senior management commitment to metadata management is required - cost and time issues
Explanation of WHY metadata is needed and the purpose of each type of metadata
Policies to ensure acronyms and abbreviations are interoperable
Procedures to ensure policies are implemented correctly
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12. Enterprise Metadata Strategy
Metadata Management Best Practices
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Enterprise Metadata Strategy
Offer recognition of value of data and its metadata (corporate assets)
Establish information requirements and instill data management / metadata management practices into organization
Address data quality, data reuse, data integrity issues for legacy applications and new development
Promote enterprise use of data management tools and techniques
Highlight importance of central data administration
Measurement of value of information
Policy is a set of broad, high-level principles that form the guiding framework within which metadata mgt can operate
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(C) Alabama Yankee Systems, LLC

13. (C) 2005 - 2006 AMSmith@ewsolutions.com
Metadata Challenge
Broad: some metadata for every production application and structure
Deep: detailed metadata for critical production applications and structures
Decision points:
What groups have “pain”? Why does “pain” exist?
What processes can be leveraged for maintenance?
What metadata is readily available and will be useful?
Who owns metadata in an organization?
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14. Metadata Management Best Practices
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Metadata Strategy Components
Metadata Responsibility and Usage
Metadata Elements
Metadata Sources
Metadata Quality
Metadata Storage and Products
Metadata Standards and Procedures
Metadata Training
Metadata Measurement
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15. (C) 2005 - 2006 AMSmith@ewsolutions.com
Kinds of Metadata
Direct:
Byproduct of original source – information systems that create, maintain and dispense data
Indirect:
Created after direct metadata – derived from system artifacts, uses of system, analysis and decision-making
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16. Metadata Management Best Practices
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Metadata Committee
Data Administration
Data Analysts
Repository Administrator
Database Administration
Data Stewards
Rotating Application Development programmers
Essential to success of Metadata strategy
Composition should be business (data stewards) and IS for balance
Committee leader should be manager of Data Administration, who has both business and IS perspectives
Programmers and other developers join committee as their projects/requests are addressed
Regular meetings for continuity
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17. Metadata Responsibilities
Data Stewardship: responsible for consistency and integrity of data objects under their control; usually from functional business units
Data Custodians: responsible for syntactical value of data; usually from Data Administration and/or Database Administration
Jointly establish standards and procedures for proper use, quality control and integration (“stewardship team”)
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18. Key Metadata Management Tasks
Establish data owners, custodians and users
Formalize data stewardship committee
Define corporate data and process standards
Define edit philosophy and user education philosophy
Centralize information object identification and control processes and impact assessment
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19. Key Metadata Management Tasks
Metadata Management Best Practices
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Key Metadata Management Tasks
Define basic enterprise information through an enterprise data model
Develop application data and process models based on enterprise model - define application information
Oversee application development and implement change control procedures
Define data and metadata access processes and choose appropriate tools
Enterprise Data models are high level and should only be concerned about the COMMON categories of information for an enterprise. An Enterprise Data Model should NOT take 7 years to develop and should be done at a level that is useful to the enterprise as a whole.
Application data models can serve as a basis for and Enterprise model, especially if the application data models are built using common terms, naming conventions, and draw on the subject matter experts for COMMON catagories as well as the specific areas of interest for the application.
The staff involved in EDM should be in charge of the modeling effort, and should be overseeing the use of the models in application development (both data models and process models).
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20. Metadata Management Best Practices
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Metadata Responsibility and Use
Establish standards and procedures
Proper use, quality control and measurement
Integration with methodology and business
Data Ownership – syntactical value of data
Data Stewardship – consistency and integrity of metadata
Data owner: responsible for syntactical value (usually DA)
Data Steward: one clearly defined set of individuals are responsible for consistency and integrity of each component of data (users). Distributes responsibility of data management to functional areas, who are most dependent in the data's quality and availability
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21. Metadata Management Best Practices
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Metadata Elements and Sources
Business definitions and business names
Systems definitions and systems names
CASE models and element relationships
Data element sources and targets (programs, files, databases, etc...)
Methods for consolidating Metadata from multiple sources
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22. (C) 2005 - 2006 AMSmith@ewsolutions.com
Quality: Imperative!
Low-quality metadata creates:
Replicated dictionaries / repositories / metadata storage
Inconsistent metadata
Competing sources of metadata “truth”
High quality metadata creates:
Confident, cross-organizational development
Consistent understanding of the values of the data resources
Metadata “knowledge” across the organization
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23. Metadata Management Best Practices
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Metadata Quality - 1
Data Accuracy: how well data values represent the actual business requirements
Data Completeness: how well available data meets current and future business information demands
Data Currency: how timely are data values
Data Consistency
Data Integrity: conformation of source data values to those allowed by business rules (data characteristics, default values, referential integrity constraints, derived data values)
Data Source and Target
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24. Metadata Management Best Practices
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Metadata Quality - 2
Data Version: which data values best represent the actual state at a point in time
Data Translation: how data values were converted between variations of the same data characteristics (for format and value variations)
Data Integration: steps to reduce data redundancy and data variability (e.g., 10 versus 7 positions; data code translation)
Data Summarization
Data Recasting: primary key changes, content and meaning changes, missing periods of data
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25. Metadata Management Best Practices
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Metadata Standards
Established by Metadata Committee
Naming standards
Abbreviations (systems and business)
Class words
Code values
Business names and definitions
CASE modeling standards
Entity and element creation/modification procedures
Storage and accessibility of standards and procedures
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26. Choosing or Creating a Standard
What schema should an organization use for metadata (i.e. how do we structure metadata)?
Use a standard schema (good for interoperability) or develop one (may provide better support for local needs)
Choice may require significant compromise – combination approach may be acceptable
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27. Metadata Management Best Practices
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Metadata Storage and Products
Central versus distributed storage
Active versus passive storage
Physical requirements of storage facility
Metadata products, capabilities and integration
Repository
CASE dictionary
Warehouse manager
Query tool data dictionary
Tool Time
Each company makes its own decisions on these issues
Make the decisions!!
Integration of multiple products is major problem after deciding what Metadata to capture and store
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28. Metadata Management Best Practices
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Metadata Training
Systems
Data Administration
Database Administration
Application Development and maintenance programming
Executive
Business
Primary users (e.g., data stewards)
Secondary users
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29. Metadata Management Best Practices
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Metadata Measurement
Measure use and effectiveness of metadata
Measure success of quality control program
Measure acceptance and success of stewardship
Integration of metadata strategy into systems methodology and business practices
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30. Metadata Management Best Practices
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Cultural Change Required
Data orientation and a focus on metadata require a conscious cultural change from individually developed applications to a unified acceptance and usage of data as the foundation of information and knowledge
Change is unsettling to all creatures - expectations and reactions must be anticipated, addressed and resolved
To be effective, cultural change must be managed in a spirit of co-operation and mutual accountability
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31. Metadata Management Best Practices
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Conclusions
Metadata Strategy can assist in achievement of data and information / intelligence goals
Metadata Strategy should be part of a comprehensive customized systems methodology and developed in conjunction with the business community
Establishment and implementation of metrics and a permanent committee for implementation are fundamental to the success of a Metadata Strategy
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32. Metadata Management Best Practices
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Questions and Answers
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33. Metadata Reference Sources
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