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© Copyright 2021 by Peter Aiken Slide # 1
peter.aiken@anythingawesome.com +1.804.382.5957 Peter Aiken, PhD
Achieving a common understanding
Data Programs:
(Management Versus Governance)
Peter Aiken, Ph.D.
• I've been doing this a long time
• My work is recognized as useful
• Associate Professor of IS (vcu.edu)
• Institute for Defense Analyses (ida.org)
• DAMA International (dama.org)
• MIT CDO Society (iscdo.org)
• Anything Awesome (anythingawesome.com)
• Experienced w/ 500+ data
management practices worldwide
• Multi-year immersions
– US DoD (DISA/Army/Marines/DLA)
– Nokia
– Deutsche Bank
– Wells Fargo
– Walmart
– HUD …
• 12 books and
dozens of articles
© Copyright 2021 by Peter Aiken Slide # 2
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+
• DAMA International President 2009-2013/2018/2020
• DAMA International Achievement Award 2001
(with Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
Data Intelligence to
Empower Your Data
Driven Enterprise
Enterprise Data Challenges
95% of organizations integrate at least
six types of data across 10 data
management technologies. IDC
94% integrate data across hybrid cloud
environments. IDC
73% of companies rank managing
sensitive data for security, privacy and
governance a top five data management
challenge. 451 Research
75% will deploy multiple data hubs for
data sharing and governance by 2024.
Gartner
Metadata-Driven Intelligence Fuels Data
Management Execution
VISIB ILITY, C ON TEXT, C ON TR OL & C OLLA B OR ATION
What data do we
have?
Where did it come
from?
Where is it now?
How has it changed
since it was first
captured?
How is it used?
How accurate
is it?
Is it sensitive?
What rules or
restrictions apply?
How can
I access it?
Who is accountable?
What do others say
about it?
DATA IN
CONTEXT
• A central and current source
for metadata provides
enterprise-wide data visibility
• Technical metadata with
business context, data fitness,
and governance limits risk and
speeds decision-making
• Automation of metadata
shortens process timelines
and delivers more tools for
effective data management
Active Metadata Management Delivers Greater Insight
and New Efficiency
• Data lineage to
accelerate determination
of pedigree and fitness
for use
• Impact analysis to inform
planning and reduce
deployed defects
• Sensitive data discovery,
classification and
visibility mitigates risk
• Data pipeline code
generation and
orchestration for faster
time to value
• Discovery and navigation
aids drive stakeholder
literacy and efficiency
Data Intelligence: Where Data Stakeholders Unite…
Harvest Curate Govern Activate Socialize
Data
Intelligence
Data
Governance
Data Design
Data Quality
Dev/OPS
Data/OPS
Enterprise
Architecture
Transformation
and Innovation
Portfolio
Management
Enterprise
Collaboration
Service
Management
Risk &
Compliance
…Connect and Collaborate
erwin Data Intelligence
erwin Data Literacy
• Enterprise business glossary
• Data governance workflows
• AI + business-friendly search
• Interactive mind maps
• Social collaboration
• … and more
erwin Data Catalog
• Automated metadata scanning
• Auto-documented mapping
• Dynamic data lineage
• Data profiling
• Impact analysis
• … and more
erwin Data Intelligence Suite
Standard Data Connectors Smart Data Connectors
Combines data cataloging and data literacy capabilities to support both IT and
business needs, delivering enterprise data governance and business enablement.
A U T O M A T I O N
Data
Protection
Data
Operations
Data
Governance
A Platform for Data Empowerment
any data, from anywhere, to Empower Everyone
Data Security and Endpoint Management
Policy and Access Management
Audit and Compliance
Backup and Recovery
Data Movement
Data Modeling
Data Systems Performance Monitoring
Data DevOps and Preparation
Data Catalog
Data Literacy
Data Profiling and Quality
Enterprise Architecture and Business
Process Modeling
Data Intelligence
Where Next Meets Now.
Visit us at Quest.com to learn more
https://anythingawesome.com
Program
© Copyright 2021 by Peter Aiken Slide # 3
Program
Data
Management
Data
Governance
Versus
• Understanding
– Data debt
– Data management
– Data governance
– Most don't know or care
• Required success factors
– Data governance
– Data management
– Working with the rest of the organization
• Messaging
– Critical importance
– Data program
– Singular foci: improving data's role in organizational strategy achievement
• Strategy
– Each’s relationship to the other
– Data challenge characteristics
– Resource constraints
– Data strategy is more about process than product
• Takeaways / Q&A
Data / Information Gap
Information
• Overly dependent upon:
– Human-beings
– Wetwear
– Knowledge workers
– Informal communications
– Often described
as the weakest link
© Copyright 2021 by Peter Aiken Slide # 4
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Data
Data management & data governance
address this challenge:
DG governs the activities of DM
How old is your profession?
© Copyright 2021 by Peter Aiken Slide # 5
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Augusta Ada King
Countess of Lovelace
(1815-52)
• 8,000+ years
• formalize practices
• GAAP
Confusion
• IT thinks data is a business problem
– "If they can connect to the server, then my job is done!"
• The business thinks IT is managing data adequately
– "Who else would be taking care of it?"
© Copyright 2021 by Peter Aiken Slide # 6
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Data Debt
• The time and effort it will take to
return your data to a governed
state from its likely current state of
ungoverned
• Getting back to zero
– Involves undoing existing stuff
– Likely new
skills are
required
• At zero-must start from scratch
– Typically requires annual proof of value
• Now you need to get good at both
– Almost all data challenges involve
interoperability
– Little guidance at optimizing data
management practices
– Very little guidance as to how to get
back to zero
© Copyright 2021 by Peter Aiken Slide # 7
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You must address data debt
• Slows progress
• Decreases quality
• Increases costs
© Copyright 2021 by Peter Aiken Slide # 8
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https://www.merkleinc.com/blog/are-you-buried-alive-data-debt
https://johnladley.com/a-bit-more-on-data-debt/
https://uk.nttdataservices.com/en/blog/2020/february/how-to-get-rid-of-your-data-debt
© Copyright 2021 by Peter Aiken Slide # 9
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Misunderstanding Data Management
Data Management - Wikipedia Definition
Note: This is a broad definition
and encompasses professions
with no technical contact data
management technologies
such as database
management systems
"Data Resource Management is the development and execution of
architectures, policies, practices and procedures that properly
manage the full data lifecycle needs of an enterprise." http://dama.org
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© Copyright 2021 by Peter Aiken Slide # 11
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Data Management
"Understanding the
current and future data
needs of an enterprise and
making that data effective
and efficient in supporting
business activities"
Aiken, P, Allen, M. D., Parker, B., Mattia, A., "Measuring Data
Management's Maturity: A Community's Self-Assessment" IEEE
Computer (research feature April 2007)
Blind Persons and the Elephant
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http://www.dailymirror.lk/print/opinion/editorial-we-need-to-become-channels-of-peace/172-27164
It is like a fan!
It is like a snake!
It is like a wall!
It is like a rope!
It is like a tree!
© Copyright 2021 by Peter Aiken Slide # 13
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Unrefined
data management
definition
Sources
Uses
Data Management
Sources
Reuse
Data Management
➜ ➜
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More refined
data management
definition
Better still data management definition
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Sources
➜ Use
➜Reuse
➜
Formal Data Reuse Management
© Copyright 2021 by Peter Aiken Slide # 16
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Data
Management
Body
of
Knowledge
(DM
BoK
V2)
11
Practice
Areas
from The DAMA Guide to the Data Management Body of Knowledge 2E © 2017 by DAMA International
DATA
ARCHITECTURE
MANAGEMENT
DATA
MODELLING
DATA STORAGE
& OPERATIONS
MANAGEMENT
DATA SECURITY
MANAGEMENT
REFERENCE &
MASTER DATA
MANAGEMENT
DATA QUALITY
MANAGEMENT
META DATA
MANAGEMENT
DOCUMENT &
CONTENT
MANAGEMENT
DATA
WAREHOUSE
& BUSINESS
INTELLIGENCE
MANAGEMENT
DATA
GOVERNANCE
› Value Chain Analysis
› Related Data
Architecture
› Lifecycle
Management
› External Codes
› Internal Codes
› Customer Data
› Product Data
› Dimension
Management
› Acquisition
› Recovery
› Tuning
› Retention
› Purging
› Standards
› Classifications
› Administration
› Authentication
› Auditing
› Enterprise,
Conceptual & Logical
Data modelling
› Analysis
› Database Design
› Implementation
› Architecture
› Implementation
› Training
& Support
› Monitoring
& Tuning
› Big Data
› Acquisition & Storage
› Backup & Recovery
› Content Management
› Retrieval
› Retention
› Architecture
› Integration
› Control
› Delivery
› Specification
› Analysis
› Measurement
› Improvement
› Strategy
› Organisation & Roles
› Policies & Standards
› Issues
› Valuation
DATA
INTEGRATION &
INTEROPERABILITY
› Integration Patterns
› Applicability
› Data in motion
› Challenges
Iteration 1
© Copyright 2021 by Peter Aiken Slide # 17
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Data
Strategy
Data
Governance
BI/
Warehouse
Perfecting
operations in 3
data management
practice areas
1X
1X
1X
Metadata
Data
Quality
Iteration 2
© Copyright 2021 by Peter Aiken Slide # 18
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Data
Strategy
Data
Governance
BI/
Warehouse
Perfecting
operations in 3
data management
practice areas
Metadata
2X
2X
1X
Iteration 3
© Copyright 2021 by Peter Aiken Slide # 19
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Data
Strategy
Data
Governance
BI/
Warehouse
Reference &
Master Data
Perfecting
operations in 3
data management
practice areas
1X
3X
3X
• "Corporate governance - which
can be defined narrowly as the
relationship of a company to its
shareholders or, more broadly,
as its relationship to society….",
Financial Times, 1997.
• "Corporate governance is about
promoting corporate fairness,
transparency and accountability"
James Wolfensohn, World Bank, President
Financial Times, June 1999.
• “Corporate governance deals
with the ways in which suppliers
of finance to corporations assure
themselves of getting a return on
their investment”,
The Journal of Finance, Shleifer and
Vishny, 1997.
Corporate Governance
© Copyright 2021 by Peter Aiken Slide # 20
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• "Corporate governance - which
can be defined narrowly as the
relationship of a company to its
shareholders or, more broadly,
as its relationship to society….",
Financial Times, 1997.
• "Corporate governance is about
promoting corporate fairness,
transparency and accountability"
James Wolfensohn, World Bank, President
Financial Times, June 1999.
• “Corporate governance deals
with the ways in which suppliers
of finance to corporations assure
themselves of getting a return on
their investment”,
The Journal of Finance, Shleifer and
Vishny, 1997.
© Copyright 2021 by Peter Aiken Slide # 21
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https://www.marketwatch.com/story/maximizing-shareholder-value-can-no-longer-be-a-companys-main-purpose-business-roundtable-2019-08-19
• "Putting structure around how organizations align IT strategy with
business strategy, ensuring that companies stay on track to achieve
their strategies and goals, and implementing good ways to measure
IT’s performance.
• It makes sure that all stakeholders’ interests
are taken into account and that
processes provide measurable results.
• Framework should answer some key
questions, such as how the IT department
is functioning overall, what key metrics
management needs and what return IT
is giving back to the business from the
investment it’s making." CIO Magazine (May 2007)
IT Governance Institute, 5 areas of focus:
• Strategic Alignment
• Value Delivery
• Resource Management
• Risk Management
• Performance Measures
• "Putting structure around how organizations align IT strategy with
business strategy, ensuring that companies stay on track to achieve
their strategies and goals, and implementing good ways to measure
IT’s performance.
• It makes sure that all stakeholders’ interests
are taken into account and that
processes provide measurable results.
• Framework should answer some key
questions, such as how the IT department
is functioning overall, what key metrics
management needs and what return IT
is giving back to the business from the
investment it’s making." CIO Magazine (May 2007)
IT Governance Institute, 5 areas of focus:
• Strategic Alignment
• Value Delivery
• Resource Management
• Risk Management
• Performance Measures
IT Governance
© Copyright 2021 by Peter Aiken Slide # 22
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Elevator Pitch
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An elevator pitch, elevator speech,
or elevator statement is a short
description of an idea, product, or
company that explains the concept in a
way such that any listener can
understand it in a short period of time.
(Wikipedia)
7 Data Governance Definitions
• The formal orchestration of people, process, and technology to enable
an organization to leverage data as an enterprise asset – The MDM Institute
• A convergence of data quality, data management, business process
management, and risk management surrounding the handling of data in an
organization – Wikipedia
• A system of decision rights and accountabilities for information-related
processes, executed according to agreed-upon models which describe who
can take what actions with what information, and when, under what
circumstances, using what methods – Data Governance Institute
• The execution and enforcement of authority over the management of data
assets and the performance of data functions – KiK Consulting
• A quality control discipline for assessing, managing, using, improving,
monitoring, maintaining, and protecting organizational
information – IBM Data Governance Council
• Data governance is the formulation of policy to optimize,
secure, and leverage information as an enterprise asset
by aligning multiple functional objectives – Sunil Soares
• The exercise of authority and control over the
management of data assets – DM BoK
© Copyright 2021 by Peter Aiken Slide # 24
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Would
you
want
your
sole,
non-
depletable,
non-
degrading,
durable,
strategic
asset
managed
without
guidance?
What is Data Governance?
© Copyright 2021 by Peter Aiken Slide # 25
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Managing
Data
with
Guidance
Would
you
want
your
sole,
non-
depletable,
non-
degrading,
durable,
strategic
asset
managed
without
guidance?
What is Data Governance?
© Copyright 2021 by Peter Aiken Slide # 26
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Managing
Data
Decisions with
Guidance
• October 2021
– Conti (infamous ransomware gang) released thousands of files stolen from the UK jewelry store Graff
• Now, the hackers would like the world to know that they regret their decision, perhaps in part because
they released files belonging to very powerful people. …
– “We found that our sample data was not properly reviewed before being uploaded to the blog,” the hackers wrote in an
announcement published on Thursday. “Conti guarantees that any information pertaining to members of Saudi Arabia, UAE,
and Qatar families will be deleted without any exposure and review.”
– “Our Team apologizes to His Royal Highness Prince Mohammed bin Salman and any other members of the Royal Families
whose names were mentioned in the publication for any inconvenience,” the hackers added.
• Imagine being a big-time ransomware hacker, thinking that you’re pretty tough, fancying yourself a master
criminal, giving yourself an intimidating online alias, maybe even being able, in certain circumstances, to
call down violence on your enemies, and then realizing one day that you’d accidentally hacked a guy who
had a journalist kidnapped, tortured to death and then dismembered with a bone saw for criticizing him.
• They are adding new compliance procedures to make sure this won’t happen again:
– The hackers also said that other than publishing the data on their site, they did not sell it or trade, and that from now on they will
“implement a more rigid data review process for any future operations.”
• We have talked before about the compliance function at ransomware firms. If you run a legal company,
you have a compliance department to make sure that you don’t do anything illegal, or at least, if your
company is really big, to keep the illegality within acceptable limits. If you run a criminal gang, you have
concerns that are different in degree but directionally similar: Your whole business is doing illegal things,
sure, but you don’t want to do too many things that are too illegal. You want to do crimes that make you
money, but not crimes that get you shut down. You want to steal information from rich people and extort
money from them. But not Mohammed bin Salman! Good lord!
© Copyright 2021 by Peter Aiken Slide # 27
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https://news.bloomberglaw.com/banking-law/matt-levines-money-stuff-elon-musk-did-some-tweets
https://www.vice.com/en/article/n7nw8m/conti-ransomware-hackers-apologize-to-arab-royal-families-for-leaking-their-data
Definition: The exercise of authority, control, and shared decision-making (planning, monitoring, and
enforcement) over the management of data assets.
Goals:
1. Enable an organization to manage its data as an asset.
2. Define, approve, communicate, and implement principles, policies, procedures, metrics, tools, and responsibilities for data
management.
3. Monitor and guide policy compliance, data usage, and management activities.
Activities:
1. Define Data Governance for the Organization (P)
1.Develop Data Governance Strategy
2. Perform Readiness Assessment
3. Perform Discovery and Business Alignment
4. Develop Organizational Touchpoints
2. Define the Data Governance Strategy (P)
1. Define the Data Governance Operating
Framework
2. Develop Goals, Principles, and Policies
3. Underwrite Data Management Projects
4. Engage Change Management
5. Engage in Issue Management
6. Assess Regulatory Compliance Requirements
3. Implement Data Governance (O)
1. Sponsor Data Standards and Procedures
2. Develop a Business Glossary
3. Co-ordinate with Architecture Groups
4. Sponsor Data Asset Valuation
4. Embed Data Governance (C,O)
Inputs:
• Business Strategies
& Goals
• IT Strategies &
Goals
• Data Management
and Data Strategies
• Organization Policies
& Standards
• Business Culture
Assessment
• Data Maturity
Assessment
• IT Practices
• Regulatory
Requirements
Deliverables:
• Data Governance Strategy
• Data Strategy
• Business / Data Governance
Strategy Roadmap
• Data Principles, Data
Governance Policies,
Processes
• Operating Framework
• Roadmap and Implementation
Strategy
• Operations Plan
• Business Glossary
• Data Governance Scorecard
• Data Governance Website
• Communications Plan
• Recognized Data Value
• Maturing Data Management
Practices
Suppliers:
• Business Executives
• Data Stewards
• Data Owners
• Subject Matter Experts
• Maturity Assessors
• Regulators
• Enterprise Architects
Consumers:
• Data Governance Bodies
• Project Managers
• Compliance Team
• DM Communities of Interest
• DM Team
• Business Management
• Architecture Groups
• Partner Organizations
Participants:
• Steering Committees
• CIO
• CDO / Chief Data
Stewards
• Executive Data Stewards
• Coordinating Data
Stewards
• Business Data Stewards
• Data Governance Bodies
Techniques:
• Concise Messaging
• Contact List
• Logo
Tools:
• Websites
• Business Glossary Tools
• Workflow Tools
• Document Management Tools
• Data Governance Scorecards
Metrics:
• Compliance to regulatory and
internal data policies.
• Value
• Effectiveness
• Sustainability
(P) Planning, (C) Control, (D) Development, (O) Operations
Data Governance and Stewardship
• Compliance Team
• DM Executives
• Change Managers
• Enterprise Data
Architects
• Project Management
Office
• Governance Bodies
• Audit
• Data Professionals
Technical
Drivers
Business
Drivers
Data Governance
© Copyright 2021 by Peter Aiken Slide # 28
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DATA
ARCHITECTURE
MANAGEMENT
DATA
MODELLING
DATA STORAGE
& OPERATIONS
MANAGEMENT
DATA SECURITY
MANAGEMENT
REFERENCE &
MASTER DATA
MANAGEMENT
DATA QUALITY
MANAGEMENT
META DATA
MANAGEMENT
DOCUMENT &
CONTENT
MANAGEMENT
DATA
WAREHOUSE
& BUSINESS
INTELLIGENCE
MANAGEMENT
DATA
GOVERNANCE
› Value Chain
Analysis
› Related Data
Architecture
› Lifecycle
Management
› External Codes
› Internal Codes
› Customer Data
› Product Data
› Dimension
Management
› Acquisitio
n
› Recovery
› Tuning
› Retention
› Purging
› Standards
› Classification
s
› Administratio
n
› Authenticatio
n
› Auditing
› Enterprise,
Conceptual &
Logical Data
modelling
› Analysis
› Database Design
› Implementation
› Architecture
› Implementation
› Training
& Support
› Monitoring
& Tuning
› Big Data
› Acquisition & Storage
› Backup & Recovery
› Content Management
› Retrieval
› Retention
› Architectur
e
› Integration
› Control
› Delivery
› Specification
› Analysis
› Measuremen
t
› Improvement
› Strategy
› Organisation & Roles
› Policies & Standards
› Issues
› Valuation
DATA
INTEGRATION &
INTEROPERABILITY
› Integration Patterns
› Applicability
› Data in motion
› Challenges
Acknowledgement: Dr. Christopher Bradley chris.Bradley@dmadvisors.co.uk
As a topic, data has confounding characteristics
Complex &
detailed
• Outsiders do not
want to hear about
or discuss any
aspects of
challenges/solutions
• Most are unqualified
re: architecture/
engineering
Taught
inconsistently
• Focus is on
technology
• Business impact is
not addressed
Not well
understood
• Lack of standards/
poor literacy/
unknown
dependencies
• (Re)learned by
every
workgroup
© Copyright 2021 by Peter Aiken Slide #
Wally Easton Playing Piano
https://www.youtube.com/watch?v=NNbPxSvII-Q
29
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Program
© Copyright 2021 by Peter Aiken Slide # 30
Program
Data
Management
Data
Governance
Versus
• Understanding
– Data debt
– Data management
– Data governance
– Most don't know or care
• Required success factors
– Data governance
– Data management
– Working with the rest of the organization
• Messaging
– Critical importance
– Data program
– Singular foci: improving data's role in organizational strategy achievement
• Strategy
– Each’s relationship to the other
– Data challenge characteristics
– Resource constraints
– Data strategy is more about process than product
• Takeaways / Q&A
What is the Difference Between DG and DM?
• Data Governance
– Policy level guidance
– Setting general guidelines/direction
– Top down is required for most data challenges
– Example: All information not marked
public should be considered confidential
• Data Management
– The business function of planning for,
controlling and delivering data/information assets
– Intense, detailed technical - too complex for any one individual to comprehend
– Example: Delivering data to solve business challenges
© Copyright 2021 by Peter Aiken Slide # 31
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Poor data manifests as multifaceted organizational challenges
© Copyright 2021 by Peter Aiken Slide # 32
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Root cause analysis is part of data governance
© Copyright 2021 by Peter Aiken Slide # 33
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IT
System
Business
Challenge
Business
Process
Business
Challenge
IT
Process
Business
Challenge
Business
System
Business
Challenge
IT
Process
Business
Challenge
IT
System
Business
Challenge
Business
Process
Business
Challenge
Poor results
Consistency Encourages Quality Analysis
© Copyright 2021 by Peter Aiken Slide # 34
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IT
System
Business
Challenge
Business
Process
Business
Challenge
IT
Process
Business
Challenge
Business
System
Business
Challenge
IT
Process
Business
Challenge
IT
System
Business
Challenge
Business
Process
Business
Challenge
Eliminating data debt
requires a team with
specialized skills
deployed to create a
repeatable process
and develop sustained
organizational
skillsets
Organizational Data Machine
© Copyright 2021 by Peter Aiken Slide # 35
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Inputs
(from Citizens and others)
Outputs
(to Citizens and others)
Organizational
Data Machine
(ODM)
ODM
How to determine what data to manage formally?
© Copyright 2021 by Peter Aiken Slide # 36
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All
inputs
are
data
All
outputs
are
data
All
inputs
are
data
All
inputs
are
data
All
inputs
are
data
All
outputs
are
data
All
outputs
are
data
All
outputs
are
data
All
inputs
are
data
All
outputs
are
data
All
inputs
are
data
All
outputs
are
data
All
inputs
are
data
All
outputs
are
data
Too much requires expensive and slow bureaucracy ←→ Too little misses opportunities
Too much requires expensive and slow bureaucracy ←→ Too little misses opportunities
Interoperability is the primary value determinant
ODM
Why is Data Governance important?
• Cost organizations
millions each year in
– Productivity
– Redundant and
siloed efforts
– Poorly thought out
hardware and
software purchases
– Delayed decision
making using
inadequate information
– Reactive instead of
proactive initiatives
– 20-40% of IT spending
can be reduced through
better data governance
© Copyright 2021 by Peter Aiken Slide # 37
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Data Governance Role: Produce systemic organizational changes that impact
data and work practices over time
© Copyright 2021 by Peter Aiken Slide # 38
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Data
Leadership
Feedback
Data
Governance
Data
Improvement
Data
Stewards
Data
Community
Participants
Data
Generators/Data
Users
Data
Things
Happen
Organizational
Things
Happen
DIPs
Data
Improves
Over
Time
Data
Improves As
A Result of
Focus
Feedback
X
$
X
$
X
$
X
$
X
$
X
$
X
$
X
$
X $ $
© Copyright 2021 by Peter Aiken Slide # 39
https://anythingawesome.com
Data and Duct Tape
© Copyright 2021 by Peter Aiken Slide # 40
https://anythingawesome.com
© Copyright 2021 by Peter Aiken Slide # 41
https://anythingawesome.com
Organizational Combined (DM & DG) Success Criteria
• 1 set of directions (at a time)
• Don't require the 'rest of us' to
learn too much
• The organization gets to tell you
that things are getting better
• Organizationally, we have
gotten good at compliance
• The entire organization is
measure-ably more data literate
• Moved from: Refocusing data
efforts to support organizational
strategy
to
Optimizing data efforts
supporting organizational strategy
© Copyright 2021 by Peter Aiken Slide # 42
https://anythingawesome.com
https://www.cultofpedagogy.com/co-constructing-success-criteria/
https://anythingawesome.com
Program
© Copyright 2021 by Peter Aiken Slide # 43
Program
Data
Management
Data
Governance
Versus
• Understanding
– Data debt
– Data management
– Data governance
– Most don't know or care
• Required success factors
– Data governance
– Data management
– Working with the rest of the organization
• Messaging
– Critical importance
– Data program
– Singular foci: improving data's role in organizational strategy achievement
• Strategy
– Each’s relationship to the other
– Data challenge characteristics
– Resource constraints
– Data strategy is more about process than product
• Takeaways / Q&A
Bad Data Decisions/
Illiteracy Spiral
© Copyright 2021 by Peter Aiken Slide # 44
https://anythingawesome.com
Bad data decisions
Technical
decision makers
are not data literate
Business decision
makers are not
data literate
Poor organizational outcomes
Poor treatment of
organizational data
assets
Poor
quality
data
© Copyright 2021 by Peter Aiken Slide # 45
https://anythingawesome.com
© Copyright 2021 by Peter Aiken Slide # 46
https://anythingawesome.com
Insufficient
Quality and
Quantity of
Training
Data
Limited
Results
Machine
Learning
Today
Differences between Programs and Projects
• Programs are Ongoing, Projects End
– Managing a program involves long term strategic planning and
continuous process improvement is not required of a project
• Programs are Tied to the Financial Calendar
– Program managers are often responsible for delivering
results tied to the organization's financial calendar
• Program Management is Governance Intensive
– Programs are governed by a senior board that provides direction,
oversight, and control while projects tend to be less governance-intensive
• Programs Have Greater Scope of Financial Management
– Projects typically have a straight-forward budget and project financial
management is focused on spending to budget while program planning,
management and control is significantly more complex
• Program Change Management is an Executive Leadership
Capability
– Projects employ a formal change management process while at the program
level, change management requires executive leadership skills and program
change is driven more by an organization's strategy and is subject to market
conditions and changing business goals
© Copyright 2021 by Peter Aiken Slide #
Adapted from http://top.idownloadnew.com/program_vs_project/ and http://management.simplicable.com/management/new/program-management-vs-project-management
Your data program must
last at least as long as
your HR program!
47
https://anythingawesome.com
A Single Focus
• Chief
– The head or leader of an organized body of people;
the person highest in authority: the chief of police
• Chief Financial Officer (CFO)
– Individual possessing the knowledge, skills, and abilities to be both
the final authority and decision-maker in organizational financial
matters
• Chief Risk Officer (CRO)
– Individual possessing the knowledge, skills, and abilities makes
decisions and implements risk management
• Chief Medical Officer (CMO)
– Responsible for organizational medical matters. The organization,
and the public, has similar expectations for any of chief officer –
especially after the Sarbanes-Oxley bill.
© Copyright 2021 by Peter Aiken Slide # 48
https://anythingawesome.com
[dictionary.com]
• Chief
– The head or leader of an organized body of people;
the person highest in authority: the chief of police
• Chief Financial Officer (CFO) ← does not balance books
– Individual possessing the knowledge, skills, and abilities to be both
the final authority and decision-maker in organizational financial
matters
• Chief Risk Officer (CRO) ← does not test software
– Individual possessing the knowledge, skills, and abilities makes
decisions and implements risk management
• Chief Medical Officer (CMO) ← does not perform surgery
– Responsible for organizational medical matters. The organization,
and the public, has similar expectations for any of chief officer –
especially after the Sarbanes-Oxley bill.
Top Data Job
© Copyright 2021 by Peter Aiken Slide # 49
https://anythingawesome.com
• Dedicated solely to data asset leveraging
• Unconstrained by an IT project mindset
• Reporting to the business
Top
Operations
Job
Top Job
Top
Finance
Job
Top
IT
Job
Top
Marketing
Job
Data Governance Organization
Top
Data
Job
Enterprise
Data
Executive
Chief
Data
Officer
https://anythingawesome.com
Program
© Copyright 2021 by Peter Aiken Slide # 50
Program
Data
Management
Data
Governance
Versus
• Understanding
– Data debt
– Data management
– Data governance
– Most don't know or care
• Required success factors
– Data governance
– Data management
– Working with the rest of the organization
• Messaging
– Critical importance
– Data program
– Singular foci: improving data's role in organizational strategy achievement
• Strategy
– Each’s relationship to the other
– Data challenge characteristics
– Resource constraints
– Data strategy is more about process than product
• Takeaways / Q&A
What is Strategy?
• Current use derived from military
- a pattern in a stream of decisions
[Henry Mintzberg]
© Copyright 2021 by Peter Aiken Slide # 51
https://anythingawesome.com
A thing
General Dwight D. Eisenhower
© Copyright 2021 by Peter Aiken Slide # 52
https://anythingawesome.com
“In preparing for battle I have always found that plans
are useless, but planning is indispensable …”
https://quoteinvestigator.com/2017/11/18/planning/
–
“In preparing for battle I have always found that plans
are useless, but planning is indispensable …”
https://quoteinvestigator.com/2017/11/18/planning/
How much Data (by the minute?)
For the entirety of 2020, every
minute of every day:
• Zoom hosted 208,000+
participants
• Netflix streamed 400,000+ hours
of video (697,000 in 2019)
• YouTube users uploaded 500
hours of video
• Consumers spent $1M online
• LinkedIn users applied for
69,000+ jobs
• Spotify added 28 songs
• Amazon shipped 6,659 packages
• Users spent $3,805
using mobile apps
© Copyright 2021 by Peter Aiken Slide # 53
https://anythingawesome.com
https://www.domo.com/learn/data-never-sleeps-8
© Copyright 2021 by Peter Aiken Slide #
There will
never be less
data than
right now! 54
https://anythingawesome.com
As articulated by Micheline Casey
Supply/demand for data talent
https://www.logianalytics.com/bi-trends/3-keys-understanding-data/
Growth of Data vs. Growth of Data Analysts
• Stored data accumulating at
28% annual growth rate
• Data analysts in workforce
growing at 5.7% growth rate
© Copyright 2021 by Peter Aiken Slide # 55
https://anythingawesome.com
Data Assets Win!
• Today, data is the most powerful, yet underutilized and poorly
managed organizational asset
• Data is your
– Sole
– Non-depletable
– Non-degrading
– Durable
– Strategic
• Asset
– Data is the new oil!
– Data is the new (s)oil!
– Data is the new bacon!
• As such, data deserves:
– It's own strategy
– Attention on par with similar
organizational assets
– Professional ministration
to make up for past neglect
© Copyright 2021 by Peter Aiken Slide #
2020 American Airlines market value ~ $6b
AAdvantage valued between $19.5-$31.5
United market value ~ 9$b
MileagePlus ~ $22b
https://www.forbes.com/sites/advisor/2020/07/15/how-airlines-make-billions-from-monetizing-frequent-flyer-programs/?sh=66da87a614e9
Data
Assets
Financial
Assets
Real
Estate Assets
Inventory
Assets
Non-
depletable
Available for
subsequent
use
Can be
used up
Can be
used up
Non-
degrading √ √ Can degrade
over time
Can degrade
over time
Durable Non-taxed √ √
Strategic
Asset √ √ √ √
56
https://anythingawesome.com
Asset: A resource controlled by the organization as a result of past events or
transactions and from which future economic benefits are expected to flow [Wikipedia]
Data Assets Win!
Separating the Wheat from the Chaff
© Copyright 2021 by Peter Aiken Slide # 57
https://anythingawesome.com
Is well organized data worth more?
Pre-Information Age Metadata
• Examples of information architecture achievements that
happened well before the information age:
– Page numbering
– Alphabetical order
– Table of contents
– Indexes
– Lexicons
– Maps
– Diagrams
© Copyright 2021 by Peter Aiken Slide # 58
https://anythingawesome.com
Example from: How to make sense of any mess
by Abby Covert (2014) ISBN: 1500615994
"While we can arrange things
with the intent to communicate
certain information, we can't
actually make information. Our
users do that for us."
https://www.youtube.com/watch?v=60oD1TDzAXQ&feature=emb_logo
https://www.youtube.com/watch?v=r10Sod44rME&t=1s
https://www.youtube.com/watch?v=XD2OkDPAl6s
Remove the structure & things fall apart rapidly
• Better organized data increases in value
© Copyright 2021 by Peter Aiken Slide # 59
https://anythingawesome.com
Separating the Data Wheat from the Data Chaff
• Better organized data increases in value
• Poor data management practices are
costing organizations money/time/effort
• 80% of organizational data is ROT
– Redundant
– Obsolete
– Trivial
• The question is which
data to eliminate?
– Most enterprise data
is never analyzed
© Copyright 2021 by Peter Aiken Slide # 60
https://anythingawesome.com
Data Strategy and Governance in Strategic Context
© Copyright 2021 by Peter Aiken Slide # 61
https://anythingawesome.com
Data asset support for
organizational strategy
What the data assets do to
better support strategy
How well the data strategy is working
Operational
feedback
How data is
delivered by IT
How IT
supports strategy
Other aspects of
organizational strategy
Organizational
Strategy
Data Strategy
Data
Governance
IT Projects
Organizational Operations
(Business Goals)
(Metadata)
(Metadata/
Business Goals)
Data Governance/Management in Strategic Context
© Copyright 2021 by Peter Aiken Slide # 62
https://anythingawesome.com
(Business Goals)
(Metadata)
Data asset support for
organizational strategy
What the data assets do to
better support strategy
How well the data strategy is working
Organizational
Strategy
Data
Governance
Data Strategy
Data
Management
Implement agreed
upon improved data
support for strategy?
Progress,
plans, problems
© Copyright 2021 by Peter Aiken Slide # 63
https://anythingawesome.com
https://en.wikipedia.org/wiki/Theory_of_constraints
(TOC)
• A management paradigm that views any
manageable system as being limited in
achieving more of its goals by a small
number of constraints(Eliyahu M. Goldratt)
• There is always at least one constraint, and
TOC uses a focusing process to identify the
constraint and restructure the rest of the
organization to address it
• TOC adopts the common idiom "a chain
is no stronger than its weakest link,"
processes, organizations, etc., are
vulnerable because the weakest
component can damage or break them or
at least adversely affect the outcome
Theory of Constraints
© Copyright 2021 by Peter Aiken Slide # 64
https://anythingawesome.com
Identify the current constraints,
the components of the system
limiting goal realization
Make quick
improvements
to the constraint
using existing
resources
Review other activities in the process facilitate proper alignment and support of constraint
If the constraint
persists, identify other
actions to eliminate
the constraint
Repeat until the
constraint is
eliminated
Alleviate
Focus evolve from reactive to proactive
Strategy helps both your data governance and data management programs
© Copyright 2021 by Peter Aiken Slide # 65
https://anythingawesome.com
Over time increase capacity and improve
Strategy
Cycle
Singular foci
• Improving data's role in
organizational strategy
achievement
• Highest level data guidance
available ...
• Focusing data activities on
business-goal achievement ...
• Providing guidance when
faced with a stream of
decisions or uncertainties
• Data strategy most usefully
articulates how data can be
best used to support
organizational strategy
• This usually involves a
balance of remediation and
proactive measures
© Copyright 2021 by Peter Aiken Slide # 66
https://anythingawesome.com
Getting Started with Data Governance
© Copyright 2021 by Peter Aiken Slide # 67
https://anythingawesome.com
(Occurs once) (Repeats)
Execute plan
Evaluate results
Revise plan
Apply change management
Strategy
Cycle
Assess context
Define DG roadmap
Secure executive mandate
Assign Data Stewards (1st round)
https://anythingawesome.com
Program
© Copyright 2021 by Peter Aiken Slide #
Program
68
Program
Data
Management
Data
Governance
Versus
• Understanding
– Data debt
– Data management
– Data governance
– Most don't know or care
• Required success factors
– Data governance
– Data management
– Working with the rest of the organization
• Messaging
– Critical importance
– Data program
– Singular foci: improving data's role in organizational strategy achievement
• Strategy
– Each’s relationship to the other
– Data challenge characteristics
– Resource constraints
– Data strategy is more about process than product
• Takeaways / Q&A
Data
Management
Data
Governance
Versus
Takeaways
• This discipline has not had 8,000 years
to formalize practices ➡ GAAP
• Your data requires professional
ministration to make up for past neglect
• Your folks don't know how to use or improve it effectively
• You likely require a new business data program
• Data governance and data management are major data program
components, in concert, they must focus on
1. Improving organizational data
2. Improving the way people use data
3. Improving how people use better data to support strategy
© Copyright 2021 by Peter Aiken Slide # 69
https://anythingawesome.com
This can only be accomplished incrementally using an
iterative, approach focusing on one aspect at a
time and applying formal transformation methods
data program!
business
Upcoming Events
Data Strategy Best Practices
11 January 2022
Data Modeling Fundamentals
8 February 2022
Data Stewards - Defining and Assigning
8 March 2022
© Copyright 2021 by Peter Aiken Slide # 70
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Brought to you by:
All Times: 19:00 UTC (2:00 PM NYC) | Presented by: Peter Aiken, PhD
Note: clicking any webinar title opens the registration link
Event Pricing
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• 20% off
directly from the publisher
on select titles
• My Book Store @
http://anythingawesome.com
• Enter the code
"anythingawesome" at the
Technics bookstore checkout
where it says to
"Apply Coupon" anythingawesome
Peter.Aiken@AnythingAwesome.com +1.804.382.5957
Thank You!
© Copyright 2021 by Peter Aiken Slide # 72
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Data Management vs. Data Governance Program

  • 1. © Copyright 2021 by Peter Aiken Slide # 1 peter.aiken@anythingawesome.com +1.804.382.5957 Peter Aiken, PhD Achieving a common understanding Data Programs: (Management Versus Governance) Peter Aiken, Ph.D. • I've been doing this a long time • My work is recognized as useful • Associate Professor of IS (vcu.edu) • Institute for Defense Analyses (ida.org) • DAMA International (dama.org) • MIT CDO Society (iscdo.org) • Anything Awesome (anythingawesome.com) • Experienced w/ 500+ data management practices worldwide • Multi-year immersions – US DoD (DISA/Army/Marines/DLA) – Nokia – Deutsche Bank – Wells Fargo – Walmart – HUD … • 12 books and dozens of articles © Copyright 2021 by Peter Aiken Slide # 2 https://anythingawesome.com + • DAMA International President 2009-2013/2018/2020 • DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd • DAMA International Community Award 2005
  • 2. Data Intelligence to Empower Your Data Driven Enterprise
  • 3. Enterprise Data Challenges 95% of organizations integrate at least six types of data across 10 data management technologies. IDC 94% integrate data across hybrid cloud environments. IDC 73% of companies rank managing sensitive data for security, privacy and governance a top five data management challenge. 451 Research 75% will deploy multiple data hubs for data sharing and governance by 2024. Gartner
  • 4. Metadata-Driven Intelligence Fuels Data Management Execution VISIB ILITY, C ON TEXT, C ON TR OL & C OLLA B OR ATION What data do we have? Where did it come from? Where is it now? How has it changed since it was first captured? How is it used? How accurate is it? Is it sensitive? What rules or restrictions apply? How can I access it? Who is accountable? What do others say about it? DATA IN CONTEXT • A central and current source for metadata provides enterprise-wide data visibility • Technical metadata with business context, data fitness, and governance limits risk and speeds decision-making • Automation of metadata shortens process timelines and delivers more tools for effective data management
  • 5. Active Metadata Management Delivers Greater Insight and New Efficiency • Data lineage to accelerate determination of pedigree and fitness for use • Impact analysis to inform planning and reduce deployed defects • Sensitive data discovery, classification and visibility mitigates risk • Data pipeline code generation and orchestration for faster time to value • Discovery and navigation aids drive stakeholder literacy and efficiency
  • 6. Data Intelligence: Where Data Stakeholders Unite… Harvest Curate Govern Activate Socialize
  • 7. Data Intelligence Data Governance Data Design Data Quality Dev/OPS Data/OPS Enterprise Architecture Transformation and Innovation Portfolio Management Enterprise Collaboration Service Management Risk & Compliance …Connect and Collaborate
  • 8. erwin Data Intelligence erwin Data Literacy • Enterprise business glossary • Data governance workflows • AI + business-friendly search • Interactive mind maps • Social collaboration • … and more erwin Data Catalog • Automated metadata scanning • Auto-documented mapping • Dynamic data lineage • Data profiling • Impact analysis • … and more erwin Data Intelligence Suite Standard Data Connectors Smart Data Connectors Combines data cataloging and data literacy capabilities to support both IT and business needs, delivering enterprise data governance and business enablement. A U T O M A T I O N
  • 9. Data Protection Data Operations Data Governance A Platform for Data Empowerment any data, from anywhere, to Empower Everyone Data Security and Endpoint Management Policy and Access Management Audit and Compliance Backup and Recovery Data Movement Data Modeling Data Systems Performance Monitoring Data DevOps and Preparation Data Catalog Data Literacy Data Profiling and Quality Enterprise Architecture and Business Process Modeling Data Intelligence Where Next Meets Now. Visit us at Quest.com to learn more
  • 10. https://anythingawesome.com Program © Copyright 2021 by Peter Aiken Slide # 3 Program Data Management Data Governance Versus • Understanding – Data debt – Data management – Data governance – Most don't know or care • Required success factors – Data governance – Data management – Working with the rest of the organization • Messaging – Critical importance – Data program – Singular foci: improving data's role in organizational strategy achievement • Strategy – Each’s relationship to the other – Data challenge characteristics – Resource constraints – Data strategy is more about process than product • Takeaways / Q&A Data / Information Gap Information • Overly dependent upon: – Human-beings – Wetwear – Knowledge workers – Informal communications – Often described as the weakest link © Copyright 2021 by Peter Aiken Slide # 4 https://anythingawesome.com Data Data management & data governance address this challenge: DG governs the activities of DM
  • 11. How old is your profession? © Copyright 2021 by Peter Aiken Slide # 5 https://anythingawesome.com Augusta Ada King Countess of Lovelace (1815-52) • 8,000+ years • formalize practices • GAAP Confusion • IT thinks data is a business problem – "If they can connect to the server, then my job is done!" • The business thinks IT is managing data adequately – "Who else would be taking care of it?" © Copyright 2021 by Peter Aiken Slide # 6 https://anythingawesome.com
  • 12. Data Debt • The time and effort it will take to return your data to a governed state from its likely current state of ungoverned • Getting back to zero – Involves undoing existing stuff – Likely new skills are required • At zero-must start from scratch – Typically requires annual proof of value • Now you need to get good at both – Almost all data challenges involve interoperability – Little guidance at optimizing data management practices – Very little guidance as to how to get back to zero © Copyright 2021 by Peter Aiken Slide # 7 https://anythingawesome.com You must address data debt • Slows progress • Decreases quality • Increases costs © Copyright 2021 by Peter Aiken Slide # 8 https://anythingawesome.com https://www.merkleinc.com/blog/are-you-buried-alive-data-debt https://johnladley.com/a-bit-more-on-data-debt/ https://uk.nttdataservices.com/en/blog/2020/february/how-to-get-rid-of-your-data-debt
  • 13. © Copyright 2021 by Peter Aiken Slide # 9 https://anythingawesome.com Misunderstanding Data Management Data Management - Wikipedia Definition Note: This is a broad definition and encompasses professions with no technical contact data management technologies such as database management systems "Data Resource Management is the development and execution of architectures, policies, practices and procedures that properly manage the full data lifecycle needs of an enterprise." http://dama.org © Copyright 2021 by Peter Aiken Slide # 10 https://anythingawesome.com
  • 14. © Copyright 2021 by Peter Aiken Slide # 11 https://anythingawesome.com Data Management "Understanding the current and future data needs of an enterprise and making that data effective and efficient in supporting business activities" Aiken, P, Allen, M. D., Parker, B., Mattia, A., "Measuring Data Management's Maturity: A Community's Self-Assessment" IEEE Computer (research feature April 2007) Blind Persons and the Elephant © Copyright 2021 by Peter Aiken Slide # 12 https://anythingawesome.com http://www.dailymirror.lk/print/opinion/editorial-we-need-to-become-channels-of-peace/172-27164 It is like a fan! It is like a snake! It is like a wall! It is like a rope! It is like a tree!
  • 15. © Copyright 2021 by Peter Aiken Slide # 13 https://anythingawesome.com Unrefined data management definition Sources Uses Data Management Sources Reuse Data Management ➜ ➜ © Copyright 2021 by Peter Aiken Slide # 14 https://anythingawesome.com More refined data management definition
  • 16. Better still data management definition © Copyright 2021 by Peter Aiken Slide # 15 https://anythingawesome.com Sources ➜ Use ➜Reuse ➜ Formal Data Reuse Management © Copyright 2021 by Peter Aiken Slide # 16 https://anythingawesome.com Data Management Body of Knowledge (DM BoK V2) 11 Practice Areas from The DAMA Guide to the Data Management Body of Knowledge 2E © 2017 by DAMA International DATA ARCHITECTURE MANAGEMENT DATA MODELLING DATA STORAGE & OPERATIONS MANAGEMENT DATA SECURITY MANAGEMENT REFERENCE & MASTER DATA MANAGEMENT DATA QUALITY MANAGEMENT META DATA MANAGEMENT DOCUMENT & CONTENT MANAGEMENT DATA WAREHOUSE & BUSINESS INTELLIGENCE MANAGEMENT DATA GOVERNANCE › Value Chain Analysis › Related Data Architecture › Lifecycle Management › External Codes › Internal Codes › Customer Data › Product Data › Dimension Management › Acquisition › Recovery › Tuning › Retention › Purging › Standards › Classifications › Administration › Authentication › Auditing › Enterprise, Conceptual & Logical Data modelling › Analysis › Database Design › Implementation › Architecture › Implementation › Training & Support › Monitoring & Tuning › Big Data › Acquisition & Storage › Backup & Recovery › Content Management › Retrieval › Retention › Architecture › Integration › Control › Delivery › Specification › Analysis › Measurement › Improvement › Strategy › Organisation & Roles › Policies & Standards › Issues › Valuation DATA INTEGRATION & INTEROPERABILITY › Integration Patterns › Applicability › Data in motion › Challenges
  • 17. Iteration 1 © Copyright 2021 by Peter Aiken Slide # 17 https://anythingawesome.com Data Strategy Data Governance BI/ Warehouse Perfecting operations in 3 data management practice areas 1X 1X 1X Metadata Data Quality Iteration 2 © Copyright 2021 by Peter Aiken Slide # 18 https://anythingawesome.com Data Strategy Data Governance BI/ Warehouse Perfecting operations in 3 data management practice areas Metadata 2X 2X 1X
  • 18. Iteration 3 © Copyright 2021 by Peter Aiken Slide # 19 https://anythingawesome.com Data Strategy Data Governance BI/ Warehouse Reference & Master Data Perfecting operations in 3 data management practice areas 1X 3X 3X • "Corporate governance - which can be defined narrowly as the relationship of a company to its shareholders or, more broadly, as its relationship to society….", Financial Times, 1997. • "Corporate governance is about promoting corporate fairness, transparency and accountability" James Wolfensohn, World Bank, President Financial Times, June 1999. • “Corporate governance deals with the ways in which suppliers of finance to corporations assure themselves of getting a return on their investment”, The Journal of Finance, Shleifer and Vishny, 1997. Corporate Governance © Copyright 2021 by Peter Aiken Slide # 20 https://anythingawesome.com • "Corporate governance - which can be defined narrowly as the relationship of a company to its shareholders or, more broadly, as its relationship to society….", Financial Times, 1997. • "Corporate governance is about promoting corporate fairness, transparency and accountability" James Wolfensohn, World Bank, President Financial Times, June 1999. • “Corporate governance deals with the ways in which suppliers of finance to corporations assure themselves of getting a return on their investment”, The Journal of Finance, Shleifer and Vishny, 1997.
  • 19. © Copyright 2021 by Peter Aiken Slide # 21 https://anythingawesome.com https://www.marketwatch.com/story/maximizing-shareholder-value-can-no-longer-be-a-companys-main-purpose-business-roundtable-2019-08-19 • "Putting structure around how organizations align IT strategy with business strategy, ensuring that companies stay on track to achieve their strategies and goals, and implementing good ways to measure IT’s performance. • It makes sure that all stakeholders’ interests are taken into account and that processes provide measurable results. • Framework should answer some key questions, such as how the IT department is functioning overall, what key metrics management needs and what return IT is giving back to the business from the investment it’s making." CIO Magazine (May 2007) IT Governance Institute, 5 areas of focus: • Strategic Alignment • Value Delivery • Resource Management • Risk Management • Performance Measures • "Putting structure around how organizations align IT strategy with business strategy, ensuring that companies stay on track to achieve their strategies and goals, and implementing good ways to measure IT’s performance. • It makes sure that all stakeholders’ interests are taken into account and that processes provide measurable results. • Framework should answer some key questions, such as how the IT department is functioning overall, what key metrics management needs and what return IT is giving back to the business from the investment it’s making." CIO Magazine (May 2007) IT Governance Institute, 5 areas of focus: • Strategic Alignment • Value Delivery • Resource Management • Risk Management • Performance Measures IT Governance © Copyright 2021 by Peter Aiken Slide # 22 https://anythingawesome.com
  • 20. Elevator Pitch © Copyright 2021 by Peter Aiken Slide # 23 https://anythingawesome.com An elevator pitch, elevator speech, or elevator statement is a short description of an idea, product, or company that explains the concept in a way such that any listener can understand it in a short period of time. (Wikipedia) 7 Data Governance Definitions • The formal orchestration of people, process, and technology to enable an organization to leverage data as an enterprise asset – The MDM Institute • A convergence of data quality, data management, business process management, and risk management surrounding the handling of data in an organization – Wikipedia • A system of decision rights and accountabilities for information-related processes, executed according to agreed-upon models which describe who can take what actions with what information, and when, under what circumstances, using what methods – Data Governance Institute • The execution and enforcement of authority over the management of data assets and the performance of data functions – KiK Consulting • A quality control discipline for assessing, managing, using, improving, monitoring, maintaining, and protecting organizational information – IBM Data Governance Council • Data governance is the formulation of policy to optimize, secure, and leverage information as an enterprise asset by aligning multiple functional objectives – Sunil Soares • The exercise of authority and control over the management of data assets – DM BoK © Copyright 2021 by Peter Aiken Slide # 24 https://anythingawesome.com
  • 21. Would you want your sole, non- depletable, non- degrading, durable, strategic asset managed without guidance? What is Data Governance? © Copyright 2021 by Peter Aiken Slide # 25 https://anythingawesome.com Managing Data with Guidance Would you want your sole, non- depletable, non- degrading, durable, strategic asset managed without guidance? What is Data Governance? © Copyright 2021 by Peter Aiken Slide # 26 https://anythingawesome.com Managing Data Decisions with Guidance
  • 22. • October 2021 – Conti (infamous ransomware gang) released thousands of files stolen from the UK jewelry store Graff • Now, the hackers would like the world to know that they regret their decision, perhaps in part because they released files belonging to very powerful people. … – “We found that our sample data was not properly reviewed before being uploaded to the blog,” the hackers wrote in an announcement published on Thursday. “Conti guarantees that any information pertaining to members of Saudi Arabia, UAE, and Qatar families will be deleted without any exposure and review.” – “Our Team apologizes to His Royal Highness Prince Mohammed bin Salman and any other members of the Royal Families whose names were mentioned in the publication for any inconvenience,” the hackers added. • Imagine being a big-time ransomware hacker, thinking that you’re pretty tough, fancying yourself a master criminal, giving yourself an intimidating online alias, maybe even being able, in certain circumstances, to call down violence on your enemies, and then realizing one day that you’d accidentally hacked a guy who had a journalist kidnapped, tortured to death and then dismembered with a bone saw for criticizing him. • They are adding new compliance procedures to make sure this won’t happen again: – The hackers also said that other than publishing the data on their site, they did not sell it or trade, and that from now on they will “implement a more rigid data review process for any future operations.” • We have talked before about the compliance function at ransomware firms. If you run a legal company, you have a compliance department to make sure that you don’t do anything illegal, or at least, if your company is really big, to keep the illegality within acceptable limits. If you run a criminal gang, you have concerns that are different in degree but directionally similar: Your whole business is doing illegal things, sure, but you don’t want to do too many things that are too illegal. You want to do crimes that make you money, but not crimes that get you shut down. You want to steal information from rich people and extort money from them. But not Mohammed bin Salman! Good lord! © Copyright 2021 by Peter Aiken Slide # 27 https://anythingawesome.com https://news.bloomberglaw.com/banking-law/matt-levines-money-stuff-elon-musk-did-some-tweets https://www.vice.com/en/article/n7nw8m/conti-ransomware-hackers-apologize-to-arab-royal-families-for-leaking-their-data Definition: The exercise of authority, control, and shared decision-making (planning, monitoring, and enforcement) over the management of data assets. Goals: 1. Enable an organization to manage its data as an asset. 2. Define, approve, communicate, and implement principles, policies, procedures, metrics, tools, and responsibilities for data management. 3. Monitor and guide policy compliance, data usage, and management activities. Activities: 1. Define Data Governance for the Organization (P) 1.Develop Data Governance Strategy 2. Perform Readiness Assessment 3. Perform Discovery and Business Alignment 4. Develop Organizational Touchpoints 2. Define the Data Governance Strategy (P) 1. Define the Data Governance Operating Framework 2. Develop Goals, Principles, and Policies 3. Underwrite Data Management Projects 4. Engage Change Management 5. Engage in Issue Management 6. Assess Regulatory Compliance Requirements 3. Implement Data Governance (O) 1. Sponsor Data Standards and Procedures 2. Develop a Business Glossary 3. Co-ordinate with Architecture Groups 4. Sponsor Data Asset Valuation 4. Embed Data Governance (C,O) Inputs: • Business Strategies & Goals • IT Strategies & Goals • Data Management and Data Strategies • Organization Policies & Standards • Business Culture Assessment • Data Maturity Assessment • IT Practices • Regulatory Requirements Deliverables: • Data Governance Strategy • Data Strategy • Business / Data Governance Strategy Roadmap • Data Principles, Data Governance Policies, Processes • Operating Framework • Roadmap and Implementation Strategy • Operations Plan • Business Glossary • Data Governance Scorecard • Data Governance Website • Communications Plan • Recognized Data Value • Maturing Data Management Practices Suppliers: • Business Executives • Data Stewards • Data Owners • Subject Matter Experts • Maturity Assessors • Regulators • Enterprise Architects Consumers: • Data Governance Bodies • Project Managers • Compliance Team • DM Communities of Interest • DM Team • Business Management • Architecture Groups • Partner Organizations Participants: • Steering Committees • CIO • CDO / Chief Data Stewards • Executive Data Stewards • Coordinating Data Stewards • Business Data Stewards • Data Governance Bodies Techniques: • Concise Messaging • Contact List • Logo Tools: • Websites • Business Glossary Tools • Workflow Tools • Document Management Tools • Data Governance Scorecards Metrics: • Compliance to regulatory and internal data policies. • Value • Effectiveness • Sustainability (P) Planning, (C) Control, (D) Development, (O) Operations Data Governance and Stewardship • Compliance Team • DM Executives • Change Managers • Enterprise Data Architects • Project Management Office • Governance Bodies • Audit • Data Professionals Technical Drivers Business Drivers Data Governance © Copyright 2021 by Peter Aiken Slide # 28 https://anythingawesome.com DATA ARCHITECTURE MANAGEMENT DATA MODELLING DATA STORAGE & OPERATIONS MANAGEMENT DATA SECURITY MANAGEMENT REFERENCE & MASTER DATA MANAGEMENT DATA QUALITY MANAGEMENT META DATA MANAGEMENT DOCUMENT & CONTENT MANAGEMENT DATA WAREHOUSE & BUSINESS INTELLIGENCE MANAGEMENT DATA GOVERNANCE › Value Chain Analysis › Related Data Architecture › Lifecycle Management › External Codes › Internal Codes › Customer Data › Product Data › Dimension Management › Acquisitio n › Recovery › Tuning › Retention › Purging › Standards › Classification s › Administratio n › Authenticatio n › Auditing › Enterprise, Conceptual & Logical Data modelling › Analysis › Database Design › Implementation › Architecture › Implementation › Training & Support › Monitoring & Tuning › Big Data › Acquisition & Storage › Backup & Recovery › Content Management › Retrieval › Retention › Architectur e › Integration › Control › Delivery › Specification › Analysis › Measuremen t › Improvement › Strategy › Organisation & Roles › Policies & Standards › Issues › Valuation DATA INTEGRATION & INTEROPERABILITY › Integration Patterns › Applicability › Data in motion › Challenges Acknowledgement: Dr. Christopher Bradley chris.Bradley@dmadvisors.co.uk
  • 23. As a topic, data has confounding characteristics Complex & detailed • Outsiders do not want to hear about or discuss any aspects of challenges/solutions • Most are unqualified re: architecture/ engineering Taught inconsistently • Focus is on technology • Business impact is not addressed Not well understood • Lack of standards/ poor literacy/ unknown dependencies • (Re)learned by every workgroup © Copyright 2021 by Peter Aiken Slide # Wally Easton Playing Piano https://www.youtube.com/watch?v=NNbPxSvII-Q 29 https://anythingawesome.com https://anythingawesome.com Program © Copyright 2021 by Peter Aiken Slide # 30 Program Data Management Data Governance Versus • Understanding – Data debt – Data management – Data governance – Most don't know or care • Required success factors – Data governance – Data management – Working with the rest of the organization • Messaging – Critical importance – Data program – Singular foci: improving data's role in organizational strategy achievement • Strategy – Each’s relationship to the other – Data challenge characteristics – Resource constraints – Data strategy is more about process than product • Takeaways / Q&A
  • 24. What is the Difference Between DG and DM? • Data Governance – Policy level guidance – Setting general guidelines/direction – Top down is required for most data challenges – Example: All information not marked public should be considered confidential • Data Management – The business function of planning for, controlling and delivering data/information assets – Intense, detailed technical - too complex for any one individual to comprehend – Example: Delivering data to solve business challenges © Copyright 2021 by Peter Aiken Slide # 31 https://anythingawesome.com Poor data manifests as multifaceted organizational challenges © Copyright 2021 by Peter Aiken Slide # 32 https://anythingawesome.com
  • 25. Root cause analysis is part of data governance © Copyright 2021 by Peter Aiken Slide # 33 https://anythingawesome.com IT System Business Challenge Business Process Business Challenge IT Process Business Challenge Business System Business Challenge IT Process Business Challenge IT System Business Challenge Business Process Business Challenge Poor results Consistency Encourages Quality Analysis © Copyright 2021 by Peter Aiken Slide # 34 https://anythingawesome.com IT System Business Challenge Business Process Business Challenge IT Process Business Challenge Business System Business Challenge IT Process Business Challenge IT System Business Challenge Business Process Business Challenge Eliminating data debt requires a team with specialized skills deployed to create a repeatable process and develop sustained organizational skillsets
  • 26. Organizational Data Machine © Copyright 2021 by Peter Aiken Slide # 35 https://anythingawesome.com Inputs (from Citizens and others) Outputs (to Citizens and others) Organizational Data Machine (ODM) ODM How to determine what data to manage formally? © Copyright 2021 by Peter Aiken Slide # 36 https://anythingawesome.com All inputs are data All outputs are data All inputs are data All inputs are data All inputs are data All outputs are data All outputs are data All outputs are data All inputs are data All outputs are data All inputs are data All outputs are data All inputs are data All outputs are data Too much requires expensive and slow bureaucracy ←→ Too little misses opportunities Too much requires expensive and slow bureaucracy ←→ Too little misses opportunities Interoperability is the primary value determinant ODM
  • 27. Why is Data Governance important? • Cost organizations millions each year in – Productivity – Redundant and siloed efforts – Poorly thought out hardware and software purchases – Delayed decision making using inadequate information – Reactive instead of proactive initiatives – 20-40% of IT spending can be reduced through better data governance © Copyright 2021 by Peter Aiken Slide # 37 https://anythingawesome.com ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ ≈ Data Governance Role: Produce systemic organizational changes that impact data and work practices over time © Copyright 2021 by Peter Aiken Slide # 38 https://anythingawesome.com Data Leadership Feedback Data Governance Data Improvement Data Stewards Data Community Participants Data Generators/Data Users Data Things Happen Organizational Things Happen DIPs Data Improves Over Time Data Improves As A Result of Focus Feedback X $ X $ X $ X $ X $ X $ X $ X $ X $ $
  • 28. © Copyright 2021 by Peter Aiken Slide # 39 https://anythingawesome.com Data and Duct Tape © Copyright 2021 by Peter Aiken Slide # 40 https://anythingawesome.com
  • 29. © Copyright 2021 by Peter Aiken Slide # 41 https://anythingawesome.com Organizational Combined (DM & DG) Success Criteria • 1 set of directions (at a time) • Don't require the 'rest of us' to learn too much • The organization gets to tell you that things are getting better • Organizationally, we have gotten good at compliance • The entire organization is measure-ably more data literate • Moved from: Refocusing data efforts to support organizational strategy to Optimizing data efforts supporting organizational strategy © Copyright 2021 by Peter Aiken Slide # 42 https://anythingawesome.com https://www.cultofpedagogy.com/co-constructing-success-criteria/
  • 30. https://anythingawesome.com Program © Copyright 2021 by Peter Aiken Slide # 43 Program Data Management Data Governance Versus • Understanding – Data debt – Data management – Data governance – Most don't know or care • Required success factors – Data governance – Data management – Working with the rest of the organization • Messaging – Critical importance – Data program – Singular foci: improving data's role in organizational strategy achievement • Strategy – Each’s relationship to the other – Data challenge characteristics – Resource constraints – Data strategy is more about process than product • Takeaways / Q&A Bad Data Decisions/ Illiteracy Spiral © Copyright 2021 by Peter Aiken Slide # 44 https://anythingawesome.com Bad data decisions Technical decision makers are not data literate Business decision makers are not data literate Poor organizational outcomes Poor treatment of organizational data assets Poor quality data
  • 31. © Copyright 2021 by Peter Aiken Slide # 45 https://anythingawesome.com © Copyright 2021 by Peter Aiken Slide # 46 https://anythingawesome.com Insufficient Quality and Quantity of Training Data Limited Results Machine Learning Today
  • 32. Differences between Programs and Projects • Programs are Ongoing, Projects End – Managing a program involves long term strategic planning and continuous process improvement is not required of a project • Programs are Tied to the Financial Calendar – Program managers are often responsible for delivering results tied to the organization's financial calendar • Program Management is Governance Intensive – Programs are governed by a senior board that provides direction, oversight, and control while projects tend to be less governance-intensive • Programs Have Greater Scope of Financial Management – Projects typically have a straight-forward budget and project financial management is focused on spending to budget while program planning, management and control is significantly more complex • Program Change Management is an Executive Leadership Capability – Projects employ a formal change management process while at the program level, change management requires executive leadership skills and program change is driven more by an organization's strategy and is subject to market conditions and changing business goals © Copyright 2021 by Peter Aiken Slide # Adapted from http://top.idownloadnew.com/program_vs_project/ and http://management.simplicable.com/management/new/program-management-vs-project-management Your data program must last at least as long as your HR program! 47 https://anythingawesome.com A Single Focus • Chief – The head or leader of an organized body of people; the person highest in authority: the chief of police • Chief Financial Officer (CFO) – Individual possessing the knowledge, skills, and abilities to be both the final authority and decision-maker in organizational financial matters • Chief Risk Officer (CRO) – Individual possessing the knowledge, skills, and abilities makes decisions and implements risk management • Chief Medical Officer (CMO) – Responsible for organizational medical matters. The organization, and the public, has similar expectations for any of chief officer – especially after the Sarbanes-Oxley bill. © Copyright 2021 by Peter Aiken Slide # 48 https://anythingawesome.com [dictionary.com] • Chief – The head or leader of an organized body of people; the person highest in authority: the chief of police • Chief Financial Officer (CFO) ← does not balance books – Individual possessing the knowledge, skills, and abilities to be both the final authority and decision-maker in organizational financial matters • Chief Risk Officer (CRO) ← does not test software – Individual possessing the knowledge, skills, and abilities makes decisions and implements risk management • Chief Medical Officer (CMO) ← does not perform surgery – Responsible for organizational medical matters. The organization, and the public, has similar expectations for any of chief officer – especially after the Sarbanes-Oxley bill.
  • 33. Top Data Job © Copyright 2021 by Peter Aiken Slide # 49 https://anythingawesome.com • Dedicated solely to data asset leveraging • Unconstrained by an IT project mindset • Reporting to the business Top Operations Job Top Job Top Finance Job Top IT Job Top Marketing Job Data Governance Organization Top Data Job Enterprise Data Executive Chief Data Officer https://anythingawesome.com Program © Copyright 2021 by Peter Aiken Slide # 50 Program Data Management Data Governance Versus • Understanding – Data debt – Data management – Data governance – Most don't know or care • Required success factors – Data governance – Data management – Working with the rest of the organization • Messaging – Critical importance – Data program – Singular foci: improving data's role in organizational strategy achievement • Strategy – Each’s relationship to the other – Data challenge characteristics – Resource constraints – Data strategy is more about process than product • Takeaways / Q&A
  • 34. What is Strategy? • Current use derived from military - a pattern in a stream of decisions [Henry Mintzberg] © Copyright 2021 by Peter Aiken Slide # 51 https://anythingawesome.com A thing General Dwight D. Eisenhower © Copyright 2021 by Peter Aiken Slide # 52 https://anythingawesome.com “In preparing for battle I have always found that plans are useless, but planning is indispensable …” https://quoteinvestigator.com/2017/11/18/planning/ – “In preparing for battle I have always found that plans are useless, but planning is indispensable …” https://quoteinvestigator.com/2017/11/18/planning/
  • 35. How much Data (by the minute?) For the entirety of 2020, every minute of every day: • Zoom hosted 208,000+ participants • Netflix streamed 400,000+ hours of video (697,000 in 2019) • YouTube users uploaded 500 hours of video • Consumers spent $1M online • LinkedIn users applied for 69,000+ jobs • Spotify added 28 songs • Amazon shipped 6,659 packages • Users spent $3,805 using mobile apps © Copyright 2021 by Peter Aiken Slide # 53 https://anythingawesome.com https://www.domo.com/learn/data-never-sleeps-8 © Copyright 2021 by Peter Aiken Slide # There will never be less data than right now! 54 https://anythingawesome.com As articulated by Micheline Casey
  • 36. Supply/demand for data talent https://www.logianalytics.com/bi-trends/3-keys-understanding-data/ Growth of Data vs. Growth of Data Analysts • Stored data accumulating at 28% annual growth rate • Data analysts in workforce growing at 5.7% growth rate © Copyright 2021 by Peter Aiken Slide # 55 https://anythingawesome.com Data Assets Win! • Today, data is the most powerful, yet underutilized and poorly managed organizational asset • Data is your – Sole – Non-depletable – Non-degrading – Durable – Strategic • Asset – Data is the new oil! – Data is the new (s)oil! – Data is the new bacon! • As such, data deserves: – It's own strategy – Attention on par with similar organizational assets – Professional ministration to make up for past neglect © Copyright 2021 by Peter Aiken Slide # 2020 American Airlines market value ~ $6b AAdvantage valued between $19.5-$31.5 United market value ~ 9$b MileagePlus ~ $22b https://www.forbes.com/sites/advisor/2020/07/15/how-airlines-make-billions-from-monetizing-frequent-flyer-programs/?sh=66da87a614e9 Data Assets Financial Assets Real Estate Assets Inventory Assets Non- depletable Available for subsequent use Can be used up Can be used up Non- degrading √ √ Can degrade over time Can degrade over time Durable Non-taxed √ √ Strategic Asset √ √ √ √ 56 https://anythingawesome.com Asset: A resource controlled by the organization as a result of past events or transactions and from which future economic benefits are expected to flow [Wikipedia] Data Assets Win!
  • 37. Separating the Wheat from the Chaff © Copyright 2021 by Peter Aiken Slide # 57 https://anythingawesome.com Is well organized data worth more? Pre-Information Age Metadata • Examples of information architecture achievements that happened well before the information age: – Page numbering – Alphabetical order – Table of contents – Indexes – Lexicons – Maps – Diagrams © Copyright 2021 by Peter Aiken Slide # 58 https://anythingawesome.com Example from: How to make sense of any mess by Abby Covert (2014) ISBN: 1500615994 "While we can arrange things with the intent to communicate certain information, we can't actually make information. Our users do that for us." https://www.youtube.com/watch?v=60oD1TDzAXQ&feature=emb_logo https://www.youtube.com/watch?v=r10Sod44rME&t=1s https://www.youtube.com/watch?v=XD2OkDPAl6s
  • 38. Remove the structure & things fall apart rapidly • Better organized data increases in value © Copyright 2021 by Peter Aiken Slide # 59 https://anythingawesome.com Separating the Data Wheat from the Data Chaff • Better organized data increases in value • Poor data management practices are costing organizations money/time/effort • 80% of organizational data is ROT – Redundant – Obsolete – Trivial • The question is which data to eliminate? – Most enterprise data is never analyzed © Copyright 2021 by Peter Aiken Slide # 60 https://anythingawesome.com
  • 39. Data Strategy and Governance in Strategic Context © Copyright 2021 by Peter Aiken Slide # 61 https://anythingawesome.com Data asset support for organizational strategy What the data assets do to better support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy Organizational Strategy Data Strategy Data Governance IT Projects Organizational Operations (Business Goals) (Metadata) (Metadata/ Business Goals) Data Governance/Management in Strategic Context © Copyright 2021 by Peter Aiken Slide # 62 https://anythingawesome.com (Business Goals) (Metadata) Data asset support for organizational strategy What the data assets do to better support strategy How well the data strategy is working Organizational Strategy Data Governance Data Strategy Data Management Implement agreed upon improved data support for strategy? Progress, plans, problems
  • 40. © Copyright 2021 by Peter Aiken Slide # 63 https://anythingawesome.com https://en.wikipedia.org/wiki/Theory_of_constraints (TOC) • A management paradigm that views any manageable system as being limited in achieving more of its goals by a small number of constraints(Eliyahu M. Goldratt) • There is always at least one constraint, and TOC uses a focusing process to identify the constraint and restructure the rest of the organization to address it • TOC adopts the common idiom "a chain is no stronger than its weakest link," processes, organizations, etc., are vulnerable because the weakest component can damage or break them or at least adversely affect the outcome Theory of Constraints © Copyright 2021 by Peter Aiken Slide # 64 https://anythingawesome.com Identify the current constraints, the components of the system limiting goal realization Make quick improvements to the constraint using existing resources Review other activities in the process facilitate proper alignment and support of constraint If the constraint persists, identify other actions to eliminate the constraint Repeat until the constraint is eliminated Alleviate
  • 41. Focus evolve from reactive to proactive Strategy helps both your data governance and data management programs © Copyright 2021 by Peter Aiken Slide # 65 https://anythingawesome.com Over time increase capacity and improve Strategy Cycle Singular foci • Improving data's role in organizational strategy achievement • Highest level data guidance available ... • Focusing data activities on business-goal achievement ... • Providing guidance when faced with a stream of decisions or uncertainties • Data strategy most usefully articulates how data can be best used to support organizational strategy • This usually involves a balance of remediation and proactive measures © Copyright 2021 by Peter Aiken Slide # 66 https://anythingawesome.com
  • 42. Getting Started with Data Governance © Copyright 2021 by Peter Aiken Slide # 67 https://anythingawesome.com (Occurs once) (Repeats) Execute plan Evaluate results Revise plan Apply change management Strategy Cycle Assess context Define DG roadmap Secure executive mandate Assign Data Stewards (1st round) https://anythingawesome.com Program © Copyright 2021 by Peter Aiken Slide # Program 68 Program Data Management Data Governance Versus • Understanding – Data debt – Data management – Data governance – Most don't know or care • Required success factors – Data governance – Data management – Working with the rest of the organization • Messaging – Critical importance – Data program – Singular foci: improving data's role in organizational strategy achievement • Strategy – Each’s relationship to the other – Data challenge characteristics – Resource constraints – Data strategy is more about process than product • Takeaways / Q&A Data Management Data Governance Versus
  • 43. Takeaways • This discipline has not had 8,000 years to formalize practices ➡ GAAP • Your data requires professional ministration to make up for past neglect • Your folks don't know how to use or improve it effectively • You likely require a new business data program • Data governance and data management are major data program components, in concert, they must focus on 1. Improving organizational data 2. Improving the way people use data 3. Improving how people use better data to support strategy © Copyright 2021 by Peter Aiken Slide # 69 https://anythingawesome.com This can only be accomplished incrementally using an iterative, approach focusing on one aspect at a time and applying formal transformation methods data program! business Upcoming Events Data Strategy Best Practices 11 January 2022 Data Modeling Fundamentals 8 February 2022 Data Stewards - Defining and Assigning 8 March 2022 © Copyright 2021 by Peter Aiken Slide # 70 https://anythingawesome.com Brought to you by: All Times: 19:00 UTC (2:00 PM NYC) | Presented by: Peter Aiken, PhD Note: clicking any webinar title opens the registration link
  • 44. Event Pricing © Copyright 2021 by Peter Aiken Slide # 71 https://anythingawesome.com • 20% off directly from the publisher on select titles • My Book Store @ http://anythingawesome.com • Enter the code "anythingawesome" at the Technics bookstore checkout where it says to "Apply Coupon" anythingawesome Peter.Aiken@AnythingAwesome.com +1.804.382.5957 Thank You! © Copyright 2021 by Peter Aiken Slide # 72 Book a call with Peter to discuss anything - https://anythingawesome.com/OfficeHours.html