Metadata Governance Webinar

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Copyright © 2016 Robert S. Seiner – KIK Consulting & Educational Services / TDAN.com
Non-Invasive Data Governance™ is a trademark of Robert S. Seiner & KIK Consulting
#RWDG
Robert S. Seiner
KIK Consulting & Educational Services, LLC – KIKconsulting.com
The Data Administration Newsletter, LLC – TDAN.com
Real-World Data Governance
Metadata to Support Data Governance
Monthly Webinar Series Hosted by DATAVERSITY
January 21, 2016 – 2:00 p.m. EST

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• Real-World Data Governance – Monthly Webinar Series – Third Thursday @ 2pET
– February 18, 2016 – The Data Model as a Data Governance Artifact
– March 17, 2016 – Writing Data Governance Policies & Procedures
– April 21, 2016 – How to Implement Data Governance Best Practice
– Register On-Line at KIKconsulting.com, TDAN.com, DATAVERSITY.net
• The Data Administration Newsletter (TDAN.com)
– Monthly On-Line Publication
– January 2016 Issue Available
– Content re Data Governance, Metadata,
Data Modeling, Agile, BigData, MDM
– Register for monthly email newsletters at TDAN.com
What’s New?

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• Non-Invasive Data Governance:
The Path of Least Resistance and Greatest Success
– ISBN 9781935504856 / Technics Publishing – September 2014
• KIKConsulting.com
– Home of Non-Invasive Data Governance™
• How to Build & Implement a Non-Invasive Data Governance™ Program
– Two Day Public Class – Pittsburgh, Pennsylvania – March 21 & 22, 2016
• DATAVERSITY Conferences
– Enterprise Data Governance On-Line
Anywhere / Anyhow – January 27
edgo.dataversity.net
– Enterprise Data World 2016
San Diego, California – April 17-22
edw2016.dataversity.net
What’s New?

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• Metadata is a by-product of executing and enforcing authority over the
management of data.
• Metadata is also a by-product of formalizing accountability for the
management of data.
• It is impossible to deliver a successful Data Governance program without it.
• Identifying the appropriate metadata and applying the appropriate level of
governance around the metadata is a critical success factor.
Abstract

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• This webinar will cover:
– The Relationship between Good Governance and Metadata
– Selecting the First and Right Metadata to Manage
– Using the Metadata to Support Your Program
– Using the Program to Support Your Metadata
– Building Governance Metadata into Everyday Events
Abstract

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Definitions
• 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.
• Metadata
– Data about Data.
– Data recorded in IT tools that improves both the
business and technical understanding of the
definition, production and usage of data.

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Definitions
• Non-Invasive Data Governance™
– The practice of applying formal accountability & behavior to assure quality,
effective use, compliance, security and protection of data.
– Non-Invasive describes how governance is applied to assure
non-threatening management of valuable data assets.
– The goal is to be
» Transparent
» Supportive
» Collaborative.

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• [to] gov·ern [data]
v. gov·erned, gov·ern·ing, gov·erns
– To make and administer the public policy and affairs [of data]
– To exercise sovereign authority [in data]
– To control the speed or magnitude [of data]
– To regulate [data]
– To control the actions or behavior [of data]
– To keep under control [data]; to restrain [data]
– To exercise a deciding or determining influence [on data]
– To exercise political authority [over data]
– To have or exercise a determining influence [over data]
FreeDictionary.com [Bob Seiner]
Definitions

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• Two Way Street
– Metadata is a by-product of formal data governance practices.
– Metadata itself must be governed as data.
– You can’t have one without the other.
old blue eyes
The Relationship between Good Governance and Metadata

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• Metadata is a By-Product
– First of all … and perhaps most important
Formalizing accountability requires the recording of who is accountable for what.
– Recording means “write it down”.

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– To improve quality requires the recording and use of standards.
– To improve understanding requires the recording and sharing of business
vocabulary, glossaries and dictionaries.
– To improve protection requires formal recording and communications of protection
rules as they apply to everyday handling of data.
– To improvement analytical capabilities requires the recording of the best available
data in the best available resource.

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– The information that is recorded is metadata.
– Successful governance of data requires that the metadata associated with the
governed discipline is well defined, produced and used.
– Data Governance is all about the “Bill of Rights”
• Getting the “right” people
• Involved at the “right” time
• To do the “right” thing
• With the “right” information
• To make the “right” decision
– Metadata is a part of each of these “rights”

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• Metadata itself must be Governed
– The metadata will not define, produce and use itself.
– Someone must be formally accountable for
• defining what metadata is or will be required
• producing the metadata and making certain it is collected and made available
• using the metadata to perform their job function
– The accumulation of metadata must be built into data processes that are governed.
– Not “Data Governance Processes”
– The Selection of Metadata Must Be Governed!

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• Someone Must Define What Metadata is Required
– Not only define what metadata data is required …
– … But also define the metadata that is identified as being required.
– Improve “Understanding of Data and Data-Related Assets”.
– Improve consistency in the collection of metadata
• What is metadata collected
• Where the metadata is collected from
• When the metadata will be collected
• Who will collect the metadata
• How will people access and used the metadata
• Why the metadata is necessary to govern data
Selecting the First and Right Metadata to Manage
D
E
F
I
N
E

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• Someone Must Produce the Metadata
– Metadata is created by using industry tools
• Data modeling tools – data definition and design metadata
• Database tools – physical database metadata
• Data movement tools – extraction, transformation, loading metadata
• Data analytics tools – location, timing, scientific metadata
• Data quality tools – standards, vocabulary, glossary metadata
• Data protection tools – classification, handling, enforcement metadata
• Workflow tools – process steps, accountability, outcome metadata
– Improve Reliability
• Standards for collecting metadata
• Formal accountability for metadata that is collected
P
R
O
D
U
C
E

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• Someone Must Use the Metadata
– Use metadata to improve analytical capabilities
• Where is the best data & metadata
• When they can get the data
• How is the best data & metadata defined
• How is the best data & metadata produced
• How the best data & metadata can be used
– Use metadata to improve protection
• Communicate classification schema
• Communicate handling rules associated with schema
• Identify who stewards the data
• Enforce handling rules with stewards
U
S
E

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• How will you use the program?
– Data Definition Governance
• Improve Understanding
• Improve Consistency
– Data Production Governance
• Improve Data Quality
• Improve Reliability
– Data Usage Governance
• Improve Analytical Capabilities
• Improve Protection
Using the Metadata to Support Your Program
What Roles will people play?

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• Data Governance Operating Model of Roles & Responsibilities
– Executive Level
• Steering Committee
– Strategic Level
• Data Governance Council
– Tactical Level
• Data Domain Stewards
• Data Steward Coordinators
– Operational Level
• Data Definers, Data Producers, Data Users
– Support Level
• Data Governance Program Team
• Information Technology – Data and System SMEs

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Using the Program to Support Your Metadata
• Remember what Data Governance is in the First Place:
– Execution and enforcement of authority over the management of
[meta] data and [meta] data related assets.
• Remember what Data Stewardship is in the First Place:
– Formalization of accountability for the management of
[meta] data and [meta] data related assets.

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• Formalize the Accountability to:
– Build Governance into Every Major Data Happening – Govern Processes
– Build the Definition of Metadata into Every Project – Govern Projects
– Build the Collection of Metadata into Every Activity – Govern Tools
– Build the Usage of Metadata into Everything You Do – Govern Distribution

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• “Active” Data Governance
– Pro-Active – Through Method / Process / Projects
– Re-Active – Through Issue Resolution / Everyday
• Overlay Roles & Responsibilities Over Existing Methodology & Work-Flow
• Data Stewardship Conflict Resolution Paths

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• System Development Life Cycle (SDLC)
Application Development Life Cycle (ADLC)
Data Development Methodology (DDM)
DB Development Methodology (DbDM)
– Planning (Roles, Time Commitments, Tasks)
– Requirements
– Analysis
– Design
– Development
– Testing
– Implementation
– Maintenance
– Enhancement
Building Governance Metadata into Project Events

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DATA DEFINER
DATA
PRODUCER
DATA STEWARD
COORDINATOR
MASTER DATA
DEVELOPMENT
LIFE CYCLE
(MDDLC)
INFORMATION
GATHERING
(DOMAIN, SYSTEM,
STEWARDS)
OPERATIONAL DATA STEWARDS
DATA USER
DATA DOMAIN
STEWARD
(or designee)
DATA DOMAIN / LOB/FUNCTIONAL AREA
ASSESSMENT &
REQUIREMENTS
PLANNING &
ANALYSIS
SOLUTION DESIGN
SOLUTION
DEVELOPMENT
SOLUTION TESTING
SOLUTION
IMPLEMENTATION
SOLUTION
MONITORING &
MAINTENANCE
Activity initiated re: this domain,
Data Domain Steward is involved
in identifying and recording info
related Domains, Systems,
Stewards per issue or task.
Steward Coordinator is involved in
identifying Operational Stewards
in this LOB/FA that should
participate in this work flow.
Assure appropriate business
meta-data is recorded.
Propose alternatives
for data definition
solution that best fits
with defined
requirements.
Provide input to the
development of the
data production
solution.
Provide definition
requirements &
gathering document.
Define data needed to
operate business &
report results.
Test data solution
from a definition
perspective. Assure
that appropriate
business meta-data is
recorded.
Produce user
requirements. Use
data needed to
operate business &
report results.
Coordinate activities of
Operational Stewards including
project timelines, status reporting,
tactical decision making. Assure
appropriate business meta-data is
recorded.
Provide data
definition guidance to
build the appropriate
solution.
Provide data usage
guidance to build the
appropriate solution.
Coordinate tasks associated
conducting planning and analysis
steps.
for data production
that best fits with the
data definition
solution and defined
requirements.
for data usage
with defined
requirements.
steps. Accept or Resolve solution
from the Steward Coordinator.
Coordinate activities of all
individuals related to development
work including timelines, status,
tactical decision making.
SYSTEM SMEs
IT
DATA SMEs
Test data solution
from a production
perspective. Assure
that appropriate
recorded.
Test data solution
from a usage
perspective. Assure
that appropriate
recorded.
Coordinate activities of the
Operational Stewards related to
testing work including timelines,
status, tactical decision making.
solution implementation including
timelines, status, tactical decision
making.
solution monitoring &
maintenance including timelines,
Perform EIS system testing.
Assure that appropriate technical
Perform EIS data testing. Assure
that appropriate technical meta-
data is recorded.
Coordinate and manage all
technical aspects of data solution
development. Assure that
appropriate technical meta-data is
recorded.
technical aspects of system
solution development. Assure
data is recorded.
Coordinate system design with
Data Domain Stewards and
Steward Coordinators.
Coordinate data design with Data
Domain Stewards and Steward
Coordinators.
planning and analysis with Data
Coordinators.
technical aspects of data planning
and analysis with Data Domain
Stewards and Steward
Coordinators.
assessment & requirements
gathering with Data Domain
Coordinators.
technical aspects of data
Coordinators.
information gathering with Data
Coordinators. Assure appropriate
technical meta-data is recorded.
Participate in data
definition information
gathering as needed.
Participate in data
production
information gathering
as needed.
Participate in data
usage information
solution implementation.
maintenance.
implementation.
monitoring & maintenance.
Coordinate business tasks
associated with solution testing
steps.
associated with solution
implementation.
As part of daily job,
identify operation
data issues pertaining
to their domain of
data.
identify operation
to their domain of
data.
identify operation
to their domain of
data.

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#RWDG
DATA DEFINER
DATA
PRODUCER
DATA STEWARD
COORDINATOR
MASTER DATA
DEVELOPMENT
LIFE CYCLE
(MDDLC)
INFORMATION
GATHERING
(DOMAIN, SYSTEM,
STEWARDS)
OPERATIONAL DATA STEWARDS
DATA USER
DATA DOMAIN
STEWARD
(or designee)
DATA DOMAIN / LOB/FUNCTIONAL AREA
ASSESSMENT &
REQUIREMENTS
PLANNING &
ANALYSIS
SOLUTION DESIGN
SOLUTION
DEVELOPMENT
SOLUTION TESTING
SOLUTION
IMPLEMENTATION
SOLUTION
MONITORING &
MAINTENANCE
Data Domain Steward is involved
in identifying and recording info
related Domains, Systems,
Stewards per issue or task.
Steward Coordinator is involved in
identifying Operational Stewards
in this LOB/FA that should
participate in this work flow.
Assure appropriate business
for data definition
with defined
requirements.
Provide input to the
development of the
data production
solution.
Provide definition
requirements &
gathering document.
Define data needed to
operate business &
report results.
Test data solution
from a definition
perspective. Assure
that appropriate
recorded.
Produce user
requirements. Use
data needed to
operate business &
report results.
Coordinate activities of
Operational Stewards including
project timelines, status reporting,
tactical decision making. Assure
appropriate business meta-data is
recorded.
Provide data
definition guidance to
build the appropriate
solution.
Provide data usage
guidance to build the
appropriate solution.
steps.
for data production
that best fits with the
data definition
solution and defined
requirements.
for data usage
with defined
requirements.
steps. Accept or Resolve solution
from the Steward Coordinator.
Coordinate activities of all
individuals related to development
work including timelines, status,
tactical decision making.
SYSTEM SMEs
IT
DATA SMEs
Test data solution
from a production
perspective. Assure
that appropriate
recorded.
Test data solution
from a usage
perspective. Assure
that appropriate
recorded.
testing work including timelines,
solution implementation including
timelines, status, tactical decision
making.
maintenance including timelines,
Perform EIS system testing.
Assure that appropriate technical
Perform EIS data testing. Assure
data is recorded.
development. Assure that
appropriate technical meta-data is
recorded.
solution development. Assure
data is recorded.
Coordinate system design with
Data Domain Stewards and
Steward Coordinators.
Coordinate data design with Data
Coordinators.
planning and analysis with Data
Coordinators.
technical aspects of data planning
and analysis with Data Domain
Coordinators.
Coordinators.
Coordinators.
Participate in data
definition information
Participate in data
production
information gathering
as needed.
Participate in data
usage information
solution implementation.
maintenance.
implementation.
associated with solution testing
steps.
implementation.
identify operation
to their domain of
data.
identify operation
to their domain of
data.
identify operation
to their domain of
data.
Sample metadata
Data Requirements
Data Models
Database Design
DATA Mapping
Data etl process
Reports & queries
Business glossary
Business rules

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Sample metadata
Master data subject areas
Specific data elements
Appropriate stewards
Systems, databases
System of record

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Building Governance Metadata into Everyday Events

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Sample metadata
Quality issues
Quality rules
Resolution
Compliance rules
Protection rules
Business vocabulary
Data requirements

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• Data Quality Methodology / Issue Resolution Process
– Qualify & Prioritize Data Issue
– Identify Affected Data Domain
– Identify Affected Data Stewards
– Conduct Data Systems & Data Resource Discovery
– Conduct Root Cause Analysis
– Conduct Cost-Benefit Analysis
– Analyze & Recommend Resolution
– Gain Approval, Funding, Resources
– Resolve Data Issue
• Cross Reference DQ Methodology & Resources
– Who does What and When?

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Sample metadata
Stakeholders
Common data matrix
Issue solution
Testing results
Change management
Solution metrics

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#RWDG
• This webinar covered:
– The Relationship between Good Governance and Metadata
– Selecting the First and Right Metadata to Manage
– Using the Metadata to Support Your Program
– Using the Program to Support Your Metadata
– Building Governance Metadata into Project / Everyday Events
Wrap Up

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• Real-World Data Governance – Monthly Webinar Series – Third Thursday @ 2pET
– February 18, 2016 – The Data Model as a Data Governance Artifact
– Register On-Line at KIKconsulting.com, TDAN.com, DATAVERSITY.net
Upcoming Webinars

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Contact
Information
• Robert S. Seiner
KIK Consulting & Educational Services, LLC – KIKconsulting.com
The Data Administration Newsletter, LLC – TDAN.com
Post Office Box 112571, Upper St. Clair, Pennsylvania 15241
412.220.9643, 412.220.9644 (Fax)
rseiner@kikconsulting.com
rseiner@tdan.com

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