More Related Content Similar to DataEd Slides: Getting (Re)Started with Data Stewardship (20) More from DATAVERSITY (20) DataEd Slides: Getting (Re)Started with Data Stewardship1. Getting (Re)Started
with Data Stewardship
© Copyright 2020 by Peter Aiken Slide # 1paiken@plusanythingawesome.com+1.804.382.5957 Peter Aiken, PhD
“If you don't know where you are going, any road will get you there.”
- Lewis Carroll
• I've been doing this a long time
• My work is recognized as useful
• Associate Professor of IS (vcu.edu)
• Founder, Data Blueprint (datablueprint.com)
• DAMA International (dama.org)
• MIT CDO Society (iscdo.org)
• Anything Awesome (plusanythingawesome.com)
• 11 books and dozens of articles
• Experienced w/ 500+ data
management practices worldwide
• Multi-year immersions
– US DoD (DISA/Army/Marines/DLA)
– Nokia
– Deutsche Bank
– Wells Fargo
– Walmart …
© Copyright 2020 by Peter Aiken Slide # 2https://plusanythingawesome.com
Peter Aiken, Ph.D.
2. • Why?
– Definitions
– Architectural context
– Confusion abounds: IT - data - business?
– Lack of correct educational focus
– The role of strategy
• How?
– Relationship with governance
– Fire station model
– Reactive foci
– Proactive foci
• When (SDLC)
– Differing cadence
– Need for different structural approach
– Foundational prerequisites
– Need for simplicity
• Take aways ➜ Q&A
3
Program
© Copyright 2020 by Peter Aiken Slide #https://plusanythingawesome.com
Getting (Re)Started with
Data Stewardship
© Copyright 2020 by Peter Aiken Slide # 4https://plusanythingawesome.com
Census?
• How many starting versus how many re-starting?
3. Data Decisions Variety
© Copyright 2020 by Peter Aiken Slide # 5https://plusanythingawesome.com
https://www.healthcatalyst.com/why-are-data-stewards-so-important-for-healthcare
Data Source Steward
Definitions
• Steward
– 1. a person who looks after the passengers on a ship, aircraft, or train and brings them meals.
• synonyms: flight attendant, cabin attendant, air hostess, purser "an air steward"
• a person responsible for supplies of food to a college, club, or other institution.
– 2. an official appointed to supervise arrangements or keep order at a large public event, for ex.
sporting event.
• synonyms: official, marshal, organizer "the race stewards"
• short for shop steward.
– 3. a person employed to manage another's property, especially a large house or estate.
• synonyms: (estate) manager, agent, overseer, custodian, caretaker; historical "the steward of the estate"
• a person whose responsibility it is to take care of something."farmers pride themselves on being stewards of the countryside"
• Stewarding
– 1. (of an official) supervise arrangements or keep order at (a large public event).
"the event was organized and stewarded properly"
– 2. manage or look after (another's property).
• Data Steward
– manage data assets on behalf of others and in the best interests of the organization (McGilvray, 2008)
– represent the interests of all stakeholders and take an enterprise perspective
– have dedicated time enough to be accountable and responsible
• Trust
– firm belief in the reliability, truth, ability, or strength of someone or something (google.com)
• Fiduciary
– involving trust, especially with regard to the relationship between a trustee and a beneficiary
(google.com)
© Copyright 2020 by Peter Aiken Slide # 6https://plusanythingawesome.com
4. Data Steward
• Business data steward
– Manage from the perspective of business elements (i.e. business definitions
and data quality)
• Technical data steward
– Focus on the use of data by systems and models (i.e. code operation)
• Project data steward
– Gather definitions, quality rules and issues for referral to business/technical stewards
• Domain data steward
– Manage data/metadata required across multiple business areas (i.e. customer data)
• Operational data steward
– Directly input data or instruct those who do; aid business
stewards identifying root cause and addressing issues
• Metadata Data Steward
– Manage metadata as an asset
• Legacy Data Steward
– Manage legacy data as an asset
• Data steward auditor
– Ensures compliance with data guidance
• Data steward manager
– Planning, organizing, leading and controlling
© Copyright 2020 by Peter Aiken Slide # 7https://plusanythingawesome.com
(list adapted from Plotkin, 2014)
one who actively directs the use of
organizational data assets in support
of specific mission objectives
Steward
• one who actively directs
© Copyright 2020 by Peter Aiken Slide # 8https://plusanythingawesome.com
, Data
5. Data
Steward
© Copyright 2020 by Peter Aiken Slide # 9https://plusanythingawesome.com
• What do data stewards do in our organization?
- Improve the organization's data assets value, and
- Advocate/evangelize for increasing the scope/rigor of
data-centric practices
- Ensure efficient/effective data management practices
© Copyright 2020 by Peter Aiken Slide # 10https://plusanythingawesome.com
DataManagement
BodyofKnowledge(DMBoKV2)
Practice
Areas
from The DAMA Guide to the Data Management Body of Knowledge 2E © 2017 by DAMA International
6. Governance and
Architecture
© Copyright 2020 by Peter Aiken Slide # 11https://plusanythingawesome.com
Example from: https://www.slideshare.net/AnthonyDehnashi/architecture-governance
https://plusanythingawesome.com
Corporate Governance
• "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 2020 by Peter Aiken Slide # 12https://plusanythingawesome.com
7. © Copyright 2020 by Peter Aiken Slide # 13https://plusanythingawesome.comhttps://plusanythingawesome.com
• "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 2020 by Peter Aiken Slide # 14https://plusanythingawesome.com
8. Data Footprints
• SQL Server
– 47,000,000,000,000 bytes
– Largest table 34 billion records 3.5 TBs
• Informix
– 1,800,000,000 queries/day
– 65,000,000 tables / 517,000 databases
• Teradata
– 117 billion records
– 23 TBs for one table
• DB2
– 29,838,518,078 daily queries
© Copyright 2020 by Peter Aiken Slide # 15https://plusanythingawesome.com
Architecture
• Things
– (components)
data structures
• The functions of the things
– (individually)
sources and uses of data
• How the things interact
– (as a system, towards a goal)
Efficiencies/effectiveness
© Copyright 2020 by Peter Aiken Slide # 16https://plusanythingawesome.com
9. Architectures: here, whether you like it or not
© Copyright 2020 by Peter Aiken Slide # 17https://plusanythingawesome.com
deviantart.com
• All organizations
have architectures
– Some are better
understood and
documented (and
therefore more
useful to the
organization) than
others
Data Architectures: here, whether you like it or not
© Copyright 2020 by Peter Aiken Slide # 18https://plusanythingawesome.com
deviantart.com
• All organizations
have data
architectures
– Some are better
understood and
documented (and
therefore more
useful to the
organization) than
others
10. Organizational
Architectures
• Amazon
– Traditional
structure
• Google
– Team of 3
• Facebook
– Do you really
have a structure?
• Microsoft
– Eliminate their
own products
• Apple
– Everything
revolves around
one individual
• Oracle
– Buys one
company after
another
© Copyright 2020 by Peter Aiken Slide # 19https://plusanythingawesome.com
Typically Managed Organizational Architectures
• Process Architecture
– Arrangement of inputs -> transformations = value -> outputs
– Typical elements: Functions, activities, workflow, events, cycles, products, procedures
• Systems Architecture
– Applications, software components, interfaces, projects
• Business Architecture
– Goals, strategies, roles, organizational structure, location(s)
• Security Architecture
– Arrangement of security controls in relation to IT Architecture
• Technical Architecture/Tarchitecture
– Relation of software capabilities/technology stack
• Structure of the technology infrastructure of an enterprise, solution or
system
– Typical elements: Networks, hardware, software platforms, standards/protocols
• Data/Information Architecture
– Arrangement of data assets supporting organizational strategy
– Typical elements: specifications expressed as entities, relationships, attributes,
definitions, values, vocabularies
© Copyright 2020 by Peter Aiken Slide # 20https://plusanythingawesome.com
11. • A specific definition
– 'Understanding an architecture'
– Documented and articulated as a (digital) blueprint illustrating the commonalities
and
interconnections among the
architectural components
– Ideally the understanding
is shared by systems and
humans
Understanding
© Copyright 2020 by Peter Aiken Slide # 21https://plusanythingawesome.com
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 the
objectives of multiple functions – Sunil Soares
• The exercise of authority and control over the
management of data assets – DM BoK
© Copyright 2020 by Peter Aiken Slide # 22https://plusanythingawesome.com
12. What is Data Governance?
© Copyright 2020 by Peter Aiken Slide # 23https://plusanythingawesome.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 2020 by Peter Aiken Slide # 24https://plusanythingawesome.com
Managing
Data
Decisions with
Guidance
Would
you
want
your
sole,
non-
depletable,
non-
degrading,
durable,
strategic
asset
managed
without
guidance?
13. Data/Information Architectures – Useful Definition
• Common vocabulary expressing
integrated requirements ensuring that
data assets are stored, arranged,
managed, and used in systems in support
of organizational strategy [Aiken 2010]
© Copyright 2020 by Peter Aiken Slide # 25https://plusanythingawesome.com
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 2020 by Peter Aiken Slide # 26https://plusanythingawesome.com
14. What do we teach knowledge workers about data?
© Copyright 2020 by Peter Aiken Slide # 27https://plusanythingawesome.com
What percentage of the deal with it daily?
What do we teach IT professionals about data?
© Copyright 2020 by Peter Aiken Slide # 28https://plusanythingawesome.com
• 1 course
– How to build a
new database
• What
impressions do IT
professionals get
from this
education?
– Data is a technical
skill that is needed
when developing
new databases
15. Bad Data Decisions Spiral
© Copyright 2020 by Peter Aiken Slide #
Bad data decisions
Technical deci-
sion makers are not
data knowledgable
Business decision
makers are not
data knowledgable
Poor organizational outcomes
Poor treatment of
organizational data
assets
Poor
quality
data
29https://plusanythingawesome.com
The role of strategy
© Copyright 2020 by Peter Aiken Slide # 30https://plusanythingawesome.com
Example from: https://slideplayer.com/slide/5082003/
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16. What is a Strategy?
© Copyright 2020 by Peter Aiken Slide # 31https://plusanythingawesome.com
• Current use derived from military
• "a pattern in a stream of decisions" [Henry Mintzberg]
Every Day
Low Price
Former Walmart Business Strategy
© Copyright 2020 by Peter Aiken Slide # 32https://plusanythingawesome.com
17. Wayne Gretzky’s
Definition of Strategy
© Copyright 2020 by Peter Aiken Slide #
He skates to where he
thinks the puck will be ...
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Strategy in Action: Napoleon faces a larger enemy
• Question?
– How do I defeat the competition when their forces
are bigger than mine?
• Answer:
– Divide
and
conquer!
– “a pattern
in a stream
of decisions”
© Copyright 2020 by Peter Aiken Slide # 34https://plusanythingawesome.com
18. Supply Line Metadata
(as part of a divide and conquer strategy)
© Copyright 2020 by Peter Aiken Slide # 35https://plusanythingawesome.com
First Divide
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19. Then Conquer
© Copyright 2020 by Peter Aiken Slide # 37https://plusanythingawesome.com
Complex Strategy
• First
– Hit both armies hard at just the right spot
• Then
– Turn right and defeat the Prussians
• Then
– Turn left and defeat the British
© Copyright 2020 by Peter Aiken Slide #
Whilesomeoneisshootingatyou!
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20. Strategy Example 1
© Copyright 2020 by Peter Aiken Slide #
Good Guys
(Us)
Bad Guys
(Them)
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Strategy Example 2
© Copyright 2020 by Peter Aiken Slide #
Good Guys
(Us)
Bad Guys
(Them)
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21. Strategy Example 3
© Copyright 2020 by Peter Aiken Slide #
Good Guys
(Us)
Bad Guys
(Them)
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Strategy Guides Workgroup Activities
© Copyright 2020 by Peter Aiken Slide #
A pattern
in a stream
of decisions
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22. Strategy that winds up only on a shelf is not useful
© Copyright 2020 by Peter Aiken Slide # 43https://plusanythingawesome.com
Data
Strategy
Data Strategy provides focus for stewardship efforts
Note: Reducing ROT increases data leverage
© Copyright 2020 by Peter Aiken Slide # 44https://plusanythingawesome.com
Organizational Data
Data Stewards
Technologies
Process
People
Less Data ROT ->
23. Getting Started with Data Stewardship
• Why?
– Stewardship terminology is not widely known
– We do not have agreed upon definitions
– It has become a de-facto standard
– Stewards work effectively with architectural components
– Strategy focuses steward leveraging activities
© Copyright 2020 by Peter Aiken Slide # 45https://plusanythingawesome.com
http://williamnava.com/philosophy-shaves-barber-21/
• Why?
– Definitions
– Architectural context
– Confusion abounds: IT - data - business?
– Lack of correct educational focus
– The role of strategy
• How?
– Relationship with governance
– Fire station model
– Reactive foci
– Proactive foci
• When (SDLC)
– Differing cadence
– Need for different structural approach
– Foundational prerequisites
– Need for simplicity
• Take aways ➜ Q&A
46
Program
© Copyright 2020 by Peter Aiken Slide #https://plusanythingawesome.com
Getting (Re)Started with
Data Stewardship
24. Data / Information Gap
Information
• Overly dependent upon:
– Human-beings
– Wetwear
– Knowledge workers
– Informal communications
– Often described
as the weakest link
© Copyright 2020 by Peter Aiken Slide # 47https://plusanythingawesome.com
Data
© Copyright 2020 by Peter Aiken Slide #
• Have little idea what data they have
• Do not know where it is (and)
• Do not know what their knowledge workers do with it
Put simply, organizations:
48https://plusanythingawesome.com
25. • Data stewardship happens 'pretty well' at
the workgroup level
– Defining characteristic of a workgroup
– Without guidance, what are the chances that all
workgroups are pulling toward the same objectives?
– Consider the time spent attempting informal practices
– Real value comes from making cross workgroup
connections work more smoothly
• Data chaff becomes sand
– Preventing smooth interoperation and exchanges
– Death by 1,000 cuts that have been difficult to account for
• Organizations and individuals lack
– Knowledge
– Skills
Workgroups get work done!
© Copyright 2020 by Peter Aiken Slide # 49https://plusanythingawesome.com
Separating the Wheat from the Chaff
• Better organized data increases in value
• Poor data management
practices are costing
organizations much money/time/effort
• Minimally 80% of organizational data is ROT
– Redundant
– Obsolete
– Trivial
• The question is
– Which data to eliminate?
© Copyright 2020 by Peter Aiken Slide #
Incomplete
https://plusanythingawesome.com 50https://plusanythingawesome.com
26. Reduce-Reuse-Recycle … Data?
• Reduce the amount of organizational data ROT
– Redundant, obsolete, trivial
• Reuse the remainder
– Fewer vocabulary items to resolve
– Greater quality engineering leverage
• Integration is impossible without information architecture
components (for mapping)
– Maintenance of these components
promotes greater reuse
• Shared data is typified by
organizational ability to use
information as a strategic asset
• However, assets are useless
without knowledge of the
asset characteristics
© Copyright 2020 by Peter Aiken Slide # 51https://plusanythingawesome.com
Data Assets Win!
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 √ √ √ √
• 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 2020 by Peter Aiken Slide # 52https://plusanythingawesome.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]
27. Data Strategy in Context
© Copyright 2020 by Peter Aiken Slide # 53https://plusanythingawesome.com
Organizational
Strategy
Data Strategy
IT Projects
Organizational Operations
Data
Governance
Data
asset support for
organizational
strategy
What the data
assets need to do to
support strategy
How well data is
supporting strategy
Operational
feedback
How IT
supports strategy
Other
aspects of
organizational
strategy
Data Governance & Data Stewards
© Copyright 2020 by Peter Aiken Slide # 54https://plusanythingawesome.com
Data Strategy
Data
Governance
What the data
assets do to support
strategy
How well the data
strategy is working
(Business Goals)
(Metadata)
Data Stewards
What is the
most effective
use of steward
investments?
(Metadata)
Progress,
plans,
problems
28. Implementation
© Copyright 2020 by Peter Aiken Slide # 55https://plusanythingawesome.com
DataLeadership
Feedback
Feedback
Data
Governance
Data
Improvement DataStewards
DataCommunityParticipants
DataGenerators/DataUsers
Data
Things
Happen
Organizational
Things
Happen
DIPs
Data Improves
Over
Time
Data Improves
As A Result of
Focus
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
≈
X
$
X
$
X
$
X
$
X
$
X
$
X
$
X
$
X $
Frameworks
© Copyright 2020 by Peter Aiken Slide # 56https://plusanythingawesome.com
• A system of ideas for
guiding analyses
• A means of organizing
project data
• Priorities for data decision
making
• A means of assessing
progress
– Don’t put up walls until
foundation inspection is passed
– Put the roof on ASAP
• Make it all dependent upon
continued funding
29. A Framework For Stewardship
© Copyright 2020 by Peter Aiken Slide #https://plusanythingawesome.com
A Framework For Stewardship
from https://www.trainingjournal.com/articles/feature/stewardship
Organizational Data
Challenges
Stewardship Engine
Regulation and Policy
A Framework for Data Stewardship
© Copyright 2020 by Peter Aiken Slide # 58https://plusanythingawesome.com
Monetary
Proactive Reactive
Stewardship Activities
Address Some
Other Time
Strategic Consideration
Non-monetary
Value
30. Domain expertise is less ← | → Domain expertise is greater
Roles more formally defined ← |→ Roles less formally defined
Encountergoverneddatamoredirectly←|→Encountergoverneddatalessdirectly
Moretimeisdedicated←|→Lesstimeisdedicated
IT/Systems Development
Leadership
(data decision makers)
Stewards
(data trustees)
Guidance
Decisions
Participants/Experts
(data subject matter experts)
Other Sources/Uses
(data makers & consumers)
IT/SystemsDevelopment
Data/feedback
Changes
Action
R
esources
Ideas
Data/Feedback
Components comprising the data community
© Copyright 2020 by Peter Aiken Slide # 59https://plusanythingawesome.com
Leadership
(data decision makers)
Stewards
(data trustees)
Guidance
Decisions
Participants/Experts
(data subject matter experts)
Other Sources/Uses
(data makers & consumers)
Data/feedback
Changes
Action
R
esources
Ideas
Data/Feedback
Basics Version
© Copyright 2020 by Peter Aiken Slide # 60https://plusanythingawesome.com
31. © Copyright 2020 by Peter Aiken Slide # 61https://plusanythingawesome.comhttps://plusanythingawesome.com
Data and Duct Tape
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32. © Copyright 2020 by Peter Aiken Slide # 63https://plusanythingawesome.comhttps://plusanythingawesome.com
Getting Started with Data Stewardship
• How?
– Transform tribal knowledge-based processes to data asset leveraging
– Understand stewards transform governance into by strategy focused action
– Apply a framework to your tasks
– Understand and get good at both reactive and proactive activities
– Attempt to incorporate leadership outside of traditional channels
– Know that you cannot accomplish
everything
© Copyright 2020 by Peter Aiken Slide # 64https://plusanythingawesome.com
https://hatrabbits.com/en/how-how-diagram/
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33. Keep the proper focus
• Wrong question:
– How should we mange this data?
• Right question:
– Should we include this
data item within the
scope of our current
management
practices?
© Copyright 2020 by Peter Aiken Slide # 65https://plusanythingawesome.comhttps://plusanythingawesome.com
• Why?
– Definitions
– Architectural context
– Confusion abounds: IT - data - business?
– Lack of correct educational focus
– The role of strategy
• How?
– Relationship with governance
– Fire station model
– Reactive foci
– Proactive foci
• When (SDLC)
– Differing cadence
– Need for different structural approach
– Foundational prerequisites
– Need for simplicity
• Take aways ➜ Q&A
66
Program
© Copyright 2020 by Peter Aiken Slide #https://plusanythingawesome.com
Getting (Re)Started with
Data Stewardship
34. Standard data
Data supply
Data literacy
Making a Better Data Governance Sandwich
© Copyright 2020 by Peter Aiken Slide #
Data literacy
Standard data
Data supply
67https://plusanythingawesome.com
Making a Better Data Governance Sandwich
© Copyright 2020 by Peter Aiken Slide #
Standard data
Data supply
Data literacy
68https://plusanythingawesome.com
35. Making a Better Data Sandwich
© Copyright 2020 by Peter Aiken Slide #
Standard data
Data supply
Data literacy
This cannot happen without data engineering and architecture!
Quality data engineering/
architecture work products
do not happen accidentally!
69https://plusanythingawesome.com
© Copyright 2020 by Peter Aiken Slide # 70https://plusanythingawesome.com
“Your Organization is
all about Data,
until it’s not about just Data”
What Business
are you in?
36. • Durable asset
- An asset that has a usable
life more than one year
• Reasonable project
deliverables
- 90 day increments
- Data evolution is measured in years
• Data
- Evolves - it is not created
- Significantly more stable
• Readymade data architectural components
- Prerequisite to agile development
• Only alternative is to create additional data siloes!
Data is not a Project
© Copyright 2020 by Peter Aiken Slide # 71https://plusanythingawesome.com
© Copyright 2020 by Peter Aiken Slide # 72https://plusanythingawesome.com
George Box
British Statistician
(1919-2013)
“All models are wrong, ...
... some are useful.”
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37. • A management paradigm that views any
manageable system as being limited in
achieving more of its goals by a small
number of constraints
• 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
© Copyright 2020 by Peter Aiken Slide # 73https://plusanythingawesome.com https://en.wikipedia.org/wiki/Theory_of_constraints
(TOC)
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Organizational Data Usage Practices
© Copyright 2020 by Peter Aiken Slide # 74https://plusanythingawesome.com
Data
Management
Practices
Duplicated but ETLed Data
(quality & transformations applied)
"Warehoused" Data
Learning/
Feedback
Marts
Analytics Practices
38. V1
Organizations
without
a formalized
data stewards
V3
Data Steward: Use data
to create strategic
opportunities
V4
Data Steward: both
Improve Operations
Innovation
The focus of data stewards should be sequenced
© Copyright 2020 by Peter Aiken Slide # 75https://plusanythingawesome.com
Only 1 is 10 organizations has a board
approved data strategy!
V2
Data Steward: Increase
organizational efficiencies/
effectiveness
X
X
Data Strategy in Context – THIS IS WRONG!
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Organizational Strategy
IT Strategy
Data Strategy
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39. Organizational Strategy
IT Strategy
This is correct …
© Copyright 2020 by Peter Aiken Slide #
Data Strategy
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theDataDoctrine.com
We are uncovering better ways of developing
IT systems by doing it and helping others do it.
Through this work we have come to value:
Data programmes preceding software development
Stable data structures preceding stable code
Shared data preceding completed software
Data reuse preceding reusable code
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That is, while there is value in the items on
the right, we value the items on the left more.
40. IT Business
Data
Perceived State of Data
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Data
Desired To Be State of Data
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IT Business
41. The Real State of Data
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Data
IT Business
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• Why?
– Definitions
– Architectural context
– Confusion abounds: IT - data - business?
– Lack of correct educational focus
– The role of strategy
• How?
– Relationship with governance
– Fire station model
– Reactive foci
– Proactive foci
• When (SDLC)
– Differing cadence
– Need for different structural approach
– Foundational prerequisites
– Need for simplicity
• Take aways ➜ Q&A
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Getting (Re)Started with
Data Stewardship
Program
42. Take Aways
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• Need for DS is increasing
– Increase in data volume
– Lack of practice improvement
• DS is a new discipline
– Must conform to constraints
– No one best way
• DS must be driven by a data
strategy complimenting
organizational strategy
• Comparing DS frameworks can
be useful
• DS directs data management
efforts
• The language of DS is
metadata
• Process improvement can
improve DS practices
10 Data Stewardship Practices to Avoid
1. Buy-in but not Committing:
Business vs. IT
2. Ready, Fire, Aim
3. Trying to Solve World Hunger or
Boil the Ocean
4. The Goldilocks Syndrome
5. Committee Overload
6. Failure to Implement
7. Not Dealing with Change
Management
8. Assuming that Technology Alone
is the Answer
9. Not Building Sustainable and
Ongoing Processes
10. Ignoring “Data Shadow Systems”
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43. • Data Governance: How to
Design, Deploy, and Sustain
an Effective Data
Governance Program
• John Ladley
• Amazon Best Sellers Rank:
#641,937 in Books (See Top
100 in Books)
– #242 in Management Information
Systems
– #209 in Library Management
– #380 in Database Storage & Design
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Upcoming Events (All webinars begin @ 17:00 UTC/2:00 PM NYC)
Essential Metadata Strategies
13 October 2020
Getting Data Quality Right -
Success Stories
10 November 2020
Necessary Prerequisites to Data
Success:
Exorcising the Seven Deadly
Data Sins
8 December 2020
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Brought to you by:
44. Event Pricing
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• 20% off
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select titles
• My Book Store @
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• Enter the code
"anythingawesome" at the
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where it says to
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peter@plusanythingawesome.com +1.804.382.5957
Questions?
Thank You!
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