RWDG Slides: Glossaries, Dictionaries, and Catalogs Result in Data Governance

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Copyright © 2020 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
Non-Invasive Data Governance™ is a trademark of Robert S. Seiner & KIK Consulting
#RWDG @RSeiner
Real-World Data Governance
Glossaries, Dictionaries, and Catalogs
Result in Data Governance
Monthly Webinar Series Hosted by DATAVERSITY
Robert S. Seiner – KIK Consulting / TDAN.com
February 20, 2020 – 11:00 a.m. PT / 2:00 p.m. ET

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#RWDG @RSeiner
Glossaries, Dictionaries, Catalogs Result in DG
Introduction
Real-World Data Governance – Monthly Webinar Series
March 19, 2020 – Achieving Data Quality with Data Governance – With Special Guest Anthony Algmin
Third Thursday each Month @ 2pm EST – Register at TDAN.com, KIKconsulting.com, DATAVERSITY.net
Non-Invasive Data Governance Book
ISBN 9781935504856 / Technics Publishing / Amazon.com
Speaking @ DATAVERSITY Events
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Non-Invasive Data Governance / Metadata Governance Online Learning Plans
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Produced by DATAVERSITY – Subscribe for emails
KIK Consulting & Educational Services
KIKConsulting.com
Home of Non-Invasive Data Governance™

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#RWDG @RSeiner
• In the webinar I will share:
– How Glossaries, Dictionaries, and Catalogs Add Value
– What Should Be Included in These Assets
– Who Has Responsibility for These Assets
– When These Assets Will Be Valuable to Your Organization
– Where the Discipline Results in Data Governance
Abstract

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#RWDG @RSeiner
• Data Governance
– Data Governance is the Execution and Enforcement of Authority
Over the Management of Data and Data-Related Resources.
• Data Stewardship
– Data Stewardship is the Formalization of Accountability
Over the Management of Data and Data-Related Resources.
– A Data Steward is a person that is held formally accountable for their
relationship to the data they define, produce and use.
Definitions

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#RWDG @RSeiner
• Non-Invasive Data Governance™
– The practice of:
• applying formal accountability & behavior
• through non-invasive roles & responsibilities
• to existing and / or new processes
• to assure that the definition, production & usage of data
• assures regulatory compliance, security, privacy, protection & quality.
– Non-Invasive describes how governance is applied to assure
non-threatening management of valuable data assets.
– The goal is to be
» Transparent
» Supportive
» Collaborative.
Definitions

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#RWDG @RSeiner
• Business Glossary
– A Business Glossary differs from a Data Dictionary in that its focal point, Data
Governance, goes beyond a Data Warehouse or database. A Business Glossary is a
means of sharing internal vocabulary within an organization. Dataversity
• Data Dictionary
– A Data Dictionary is a description of data in business terms, also including information
about the data such as data types, details of structure, and security restrictions.
Dataversity
• Data Catalog
– A data catalog informs customers about that available data sets and metadata around a
topic and assists users in locating it quickly. A data catalog differs from a data dictionary
in its ability for searching and retrieving information. Dataversity
Definitions

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#RWDG @RSeiner
• Business Glossary
– A Business Glossary differs from a Data Dictionary in that its focal point, Data
Governance, goes beyond a Data Warehouse or database. A Business Glossary is a
means of sharing internal vocabulary within an organization. Dataversity
• Data Dictionary
– A Data Dictionary is a description of data in business terms, also including information
about the data such as data types, details of structure, and security restrictions.
Dataversity
• Data Catalog
– A data catalog informs customers about that available data sets and metadata around a
topic and assists users in locating it quickly. A data catalog differs from a data dictionary
in its ability for searching and retrieving information. Dataversity
Definitions
The Dataversity What-Is series of articles and online courses
are an excellent resource for data-focused definitions.

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#RWDG @RSeiner
• Every action people take with data falls under one of these three actions.
There are Three Actions People Can Take With Data
Define Data Produce Data
Use Data
Data will not govern itself!
Glossaries, Dictionaries and Catalogs
Enable Data Definition, Production and Usage!

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#RWDG @RSeiner
• These tools add value by improving the …
– Understanding of the Data and Information
– Knowledge of What Data is Available and Who the Data Stewards Are
– Confidence People Have in the Data They Need
– Discipline Associated with Defining, Producing and Using Data
– Ability to Leverage the Data to Improve Business Outcomes
How Glossaries, Dictionaries, and Catalogs Add Value

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– Understanding of the Data and Information
• Terminology provides semantic consistency in what things are called.
• Naming adds value in data reference.
• Definition explains specifically what the data is.
• Attributes provide characteristics of the data required to use it.
• Inventory lists the available data and information resources.
• Lineage shares where the data came from and what was done to it.
• Report lists share who receives information from where, when and how.

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– Knowledge of What Data is Available and Who Stewards the Data
• Databases available for query, sharing and integration.
• Sources of unstructured data such as documents, diagrams, audio, video …
• Associates people names and departments with data sources.
• Impact analysis by keeping track of who defines, produces, uses the data.
• Business rule, Regulatory rule, Privacy rule, Quality rules to all Stewards.
• Location, tools, permissions, authority, technology assoc w/using the data.

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– Confidence People Have in the Data They Need
• The antidote is facts … and facts require data.
• Reliance that the data is accurately defined and produced for use.
• Trust improves with knowledge about anything … including data.
• Reduces time tracking down the appropriate data.
• Reduces time spent manipulating the data.
• Improves chances that data or reports will match.
• Confidence breeds confidence.

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– Discipline Associated with Defining, Producing and Using Data
• Formal structure for collecting the metadata associated with CDEs.
• Two out of three ain’t bad. – No! It’s good!
• Defining data for how it will be produced and used.
• Producing data based on how it is defined for use.
• Using data based on how it is defined and produced.
• Application of accountability for metadata.
• The metadata will not govern itself!

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– Ability to Leverage the Data to Improve Business Outcomes
• Follow the Data Governance Bill of “Rights”.
• “Right” people using “Right” data in the “Right” way for the
“Right” reason resulting in the “Right” business outcome …
• Business outcomes result from the quality and value of data.
• Works both ways – good (bad) data = good (bad) results.
• There are no facts without data.
• Decision based on assumption is always a risk.

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• The metadata that should be included in the:
– Business Glossary
– Data Dictionary
– Data Catalog
– Metadata Repository
– Data Management Inventory
What Should Be Included in These Assets

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• Business Term – apart from data
• Business Definition – of the term
• Business Category – part of business where this belongs
• Related Terms – other associated terms
• Source of the Term – where is the data located, where did it come from
• Relationship to Data Domains – what subject matter does this data fall in
• Linkage to Data – what data do we have about this term
• Term Stewardship – who is responsible for the term

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– Data Dictionary
• Resource – database, system, warehouse, lake, platform …
• Element – piece of data in the data resource
• Attributes – data type, positions, nulls, characteristics
• Definition – how is the data defined per this resource
• Linkages – standards, aliases, glossary term, …
• Relationships – where else the data exist
• Lineage – where the data came from
• Rules – quality, business, classification, sharing, collection … rules

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– Data Catalog
• Similar to what is found in a metadata repository but focused
• Inventory of data resources – past, present & future
• Inventory of accountability and stewardship – common data matrix
• Categories and lists of available reports and datasets
• Directions to the data – like a card catalog
• Categories of business, protection and regulatory rules
• “Ownership” of data resources and governance metadata

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• Catch-all phrase for all things metadata
• Can include metadata from Glossaries, Dictionaries and Catalogs
• Business metadata – data that will help the Business get value from data
• Technical metadata – data from tools in your environment
• Conceptual, Logical, Physical data models
• Business models, frameworks, predictive models
• Processes – flow charts, swim lanes diagrams, dependencies, …
• Rules – guidelines for governed behavior
• Metrics – where measurements of progress, acceptance are stored

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• Often the focus of audits of the data, information and records
• Active and passive data resources
• Classification – confidential, private, sensitive, public, open …
• Activities associated with the handling of the data – data at rest & in motion
• Data resources sources – internal and external
• Guidelines for data definition, production and usage
• Category – application, SaaS, subscription, …
• Ownership – department responsible for documentation and rules

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#RWDG @RSeiner
• These people have responsibility for the value that comes from:
– Data Dictionary
– Data Catalog
Who Has Responsibility for These Assets

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• Data Governance Administrator / Office – responsible
• Business Leadership – defining the requirements
• Business Analysts – liaison between the business and IT
• Project Manager – overseeing the effort, cracking the whip!
• Technician – supporting the tool, templates, … eventual migration
• Data Modelers – conceptual and logical models
• Council – results approval

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– Data Dictionary
• Business and Tactical Leadership – defining the requirements
• Application Development – provide resource element lists

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– Data Catalog
• Business Leadership – defining the requirements
• Business Analysts – inventory data used by the business

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• Business and Technical Leadership – defining the requirement
• Data Modelers – data models and definition documentation
• Application Developers – systems, programs, file layouts

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• Data Governance and Records Administrator / Office – responsible
• Business Leadership – defining the requirement
• Partners incl Legal, Audit, Counsel – assure auditability, legalities

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#RWDG @RSeiner
• These assets will add value to your organization when:
– Data is Being Defined
– Data is Being Produced
– Data is Being Used
– Data is Being Shared
– Data is Being Protected
When These Assets Will Be Valuable to Your Organization

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#RWDG @RSeiner
• By formalizing the process of collecting data definition.
• By preventing the collection of “cheeseburger” definitions.
• By providing a data definition resource that can be validated.
• By providing data definition that can be communicated and shared.
• By improving people’s understanding of the data.
• By improving people’s knowledge of the data that is available.
• By providing clear rules and roles associated with data definition.
• By formalizing the data definition process.

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• By formalizing the process of producing quality data.
• By providing data producers with clear data definition and expectations.
• By providing data producers clear understanding how the data is used.
• By formalizing requirements for how the data must be produced.
• By providing clear rules and roles associated with data production.
• By formalizing the data production process.

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• By formalizing the process of using data appropriately.
• By providing data producers clear understanding how the data is used.
• By providing data users with knowledge of how to share and protect data.
• By formalizing requirements for how the data must be used.
• By providing clear rules and roles associated with data usage.
• By formalizing the data usage process.

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• By formalizing the process of sharing data.
• By providing people w/clear rules and roles associated with sharing data.
• By providing detailed knowledge of classification and handling of data.
• By formalizing requirements for how the data can be shared.
• By making the rules actionable as part of everyday activities.
• By formalizing the data sharing process.

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• By formalizing the process of protecting data.
• By providing people w/clear rules for protecting data.
• By providing detailed knowledge of classification and handling of data.
• By formalizing requirements for how the data must be protected.
• By making the rules actionable as part of everyday activities.
• By formalizing the data protection process.

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#RWDG @RSeiner
• The disciplines associated w/these assets will results in Data Governance when:
Where the Discipline Results in Data Governance

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• By formalizing accountability for data definition.
• By executing and enforcing authority over data definition.
• By providing a place where the data definition will be collected.
• By providing a place where the data definition is available.
• By providing an instrument that will encourage interaction.
• By providing auditable documentation associated with data definition.
• By improving people’s understanding of how data is defined.
• By improving people’s ability to define data based on asset availability.

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• By formalizing accountability for data production.
• By executing and enforcing authority over data production.
• By providing a place where the data production rules will be collected.
• By providing auditable documentation associated with data production.
• By improving people’s understanding of how and when data is produced.
• By improving people’s ability to produce data based on their knowledge.

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• By formalizing accountability for data usage.
• By executing and enforcing authority over data usage.
• By providing a place where the data usage rules will be collected.
• By providing a place where the data usage rules can be found.
• By providing auditable documentation associated with data usage.
• By improving people’s understanding of how data can/should be used.
• By improving people’s ability to use data based on their knowledge.

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• By formalizing accountability for data sharing.
• By executing and enforcing authority over data sharing.
• By providing a place where the data sharing rules will be collected.
• By providing a place where the data sharing rules can be found.
• By providing auditable documentation associated with data sharing.
• By improving people’s understanding of how data can be shared.
• By improving people’s ability to share data based on their knowledge.

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• By formalizing accountability for data protection.
• By executing and enforcing authority over data protection.
• By providing a place where the data protection rules will be collected.
• By providing a place where the data protection rules can be found.
• By providing auditable documentation associated with data protection.
• By improving people’s understanding of how data can be protection.
• By improving people’s ability to protect data based on their knowledge.

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#RWDG @RSeiner
• Metadata Governance:
– Metadata Governance is real and necessary.
– The metadata will not govern itself.
– The metadata in these assets will only be as good as the associated discipline.
– Focus on accountability for data/metadata definition, production and usage.
– Start and stay non-invasive in your approach to formalizing accountability.
Final Thoughts
Final
Thoughts!

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#RWDG @RSeiner
• In the webinar I shared:
– How glossaries, dictionaries, and catalogs add value
– What should be included in these assets
– Who has responsibility for these assets
– When these assets will be valuable to your organization
– Where the discipline results in Data Governance
Summary

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#RWDG @RSeiner
Questions and Answers
Meet me in the Dataversity Community
to continue the conversation.
https://community.dataversity.net/

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#RWDG @RSeiner
• Robert S. Seiner
KIK Consulting & Educational Services – KIKconsulting.com
The Data Administration Newsletter – TDAN.com
Post Office Box 112571, Upper St. Clair, Pennsylvania 15241
412.220.9643, 412.220.9644 (Fax)
rseiner@kikconsulting.com
rseiner@tdan.com
@RSeiner @TDAN_com
#RWDG
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RWDG Slides: Glossaries, Dictionaries, and Catalogs Result in Data Governance

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