Post on 07-Jun-2020
transcript
The Case for the Top Data Job
Rethinking the Essence of a Critically Lacking Business
Function
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Peter Aikenpeter@datablueprint.com +1 804 382 5957
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Data
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Peter Aiken• Full time in information technology since 1981• IT engineering research and project background• University teaching experience since 1979• Seven books and dozens of articles• Research Areas
– reengineering, data reverse engineering, software requirements engineering, information engineering, human-computer interaction, systems integration/systems engineering, strategic planning, and DSS/BI
• Director– George Mason University/Hypermedia Laboratory (1989-1993)
• DoD Computer Scientist– Reverse Engineering Program Manager/Office of the Chief Information Officer (1992-1997)
• Visiting Scientist– Software Engineering Institute/Carnegie Mellon University (2001-2002)
• Published Papers– Communications of the ACM, IBM Systems Journal, InformationWEEK, Information & Management, Information
Resources Management Journal, Hypermedia, Information Systems Management, Journal of Computer Information Systems and IEEE Computer & Software
• DAMA International President (http://dama.org)
– 2001 DAMA International Individual Achievement Award (with Dr. E. F. "Ted" Codd)– 2005 DAMA Community Award
• Founding Advisor/International Association for Information and Data Quality (http://iaidq.org)
• Founding Advisor/Meta-data Professionals Organization (http://metadataprofessional.org)
• Founding Director Data Blueprint 19992
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Someone Notable Thinks DM is Important
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excerpt from President Obama's 2012 State of the Union Address
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Organizations Surveyed
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• Results from more than 500 organizations
• 32% government
• Appropriate public company representation
• Enough data to demonstrate European organization DM practices are generally more mature
Local Government4%
State Government Agencies17%
Federal Government11%
Public Companies 58%
International Organizations10%
• Approximately, 10% percent of organizations achieve parity and (potential positive returns) on their DM investments.
• Only 30% of DM investments achieve tangible returns at all.• Seventy percent of organizations have very small or no tangible
return on their DM investments. - datablueprint.com 6/18/2012 © Copyright this and previous years by Data Blueprint - all rights reserved!
Largely Ineffective
Investments
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Investment <= Return10%
Investment > Return20%
Return ≈ 070%
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58 Commonly Used Chief Officer Titles
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• Chief Accounting Officer, Chief Administrative Officer, Chief Analytics Officer, Chief Audit Officer, Chief Brand Officer, Chief Business Officer, Chief Channel Officer, Chief Commercial Officer, Chief Communications Officer, Chief Compliance Officer, Chief Creative Officer, Chief Data Officer, Chief Executive Officer, Chief Financial Officer, Chief Human Resources Officer, Chief Information Officer, Chief Information Security Officer, Chief Innovation Officer, Chief Investment Officer, Chief Immigration Officer, Chief Geospatial Information Officer, Chief Knowledge Officer, Chief Leadership Officer, Chief Learning Officer, Chief Legal Officer, Chief Marketing Officer, Chief Marketing Information Officer, Chief Medical Officer, Chief Merchandising Officer, Chief Networking Officer, Chief Operating Officer, Chief Process Officer, Chief Procurement Officer, Chief Product Officer, Chief Research Information Officer, Chief Risk Officer, Chief Science Officer, Chief Stores Officer, Chief Strategy Officer, Chief Technology Officer, Chief Visionary Officer, Chief Web Officer
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The "Chief Officer" Title
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• 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.
[dictionary.com]
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• A new emphasis on the data • Data demand is increasing• The amount of data is
increasing year over year• Atmosphere of heightened
public and corporate sensitivity to security, privacy, and compliance
• New initiatives within the organization (BI, SOA, Dim Data marts)
• Maintain a competitive advantage and profitability by leveraging information as an asset
Driver: Information Overload
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Data InflationUnit Size What it means
Bit (b) 1 or 0 Short for “binary digit”, after the binary code (1 or 0) computers use to store and process data
Byte (B) 8 bits Enough information to create an English letter or number in computer code. It is the basic unit of computing
Kilobyte (KB) 1,000, or 210, bytes From “thousand” in Greek. One page of typed text is 2KB
Megabyte (MB)
1,000KB; 220 bytes From “large” in Greek. The complete works of Shakespeare total 5MB. A typical pop song is about 4MB
Gigabyte (GB)
1,000MB; 230 bytes From “giant” in Greek. A two-hour film can be compressed into 1-2GB
Terabyte (TB) 1,000GB; 240 bytes From “monster” in Greek. All the catalogued books in America’s Library of Congress total 15TB
Petabyte (PB) 1,000TB; 250 bytes All letters delivered by America’s postal service this year will amount to around 5PB. Google processes around 1PB every hour
Exabyte (EB) 1,000PB; 260 bytes Equivalent to 10 billion copies of The Economist
Zettabyte (ZB)
1,000EB; 270 bytes The total amount of information in existence this year is forecast to be around 1.2ZB
Yottabyte (YB)
1,000ZB; 280 bytes Currently too big to imagine
The prefixes are set by an intergovernmental group, the International Bureau of Weights and Measures. Source: The Economist Yotta and Zetta were added in 1991; terms for larger amounts have yet to be established
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5% Sales Increase Versus Data Volume
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1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016
Sales Data Volume
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A likely state of your data
Very
Silo
’ed or
conf
lictin
g data
sour
ces
Multiple Data Sources
Inconsistent data
definitions of
common terms
IT are data
owners Lots of
Data….Minimum
Informatio
n
Inconsistent Data Quality
Difficult to report and mine against
Redundancy
Multiple changes to source system
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History (such as it is)• Automate existing manual processing • Data management was simple
– Running millions of punched cards through banks of sorting, collating and tabulating machines
– Results printed on paper or punched onto more cards
– Data management meant physically storing and hauling around punched cards
• Tasks (check signing, calculating, and machine control) were implemented to provide automated support for departmental-based processing
• Creating information silos12
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Payroll Application(3rd GL)
Payroll Data(database)
R& D Applications(researcher supported, no documentation)
R & DData(raw)
Mfg. Data(home grown
database) Mfg. Applications(contractor supported)
FinanceData
(indexed)
Finance Application(3rd GL, batch system, no source)
Marketing Application(4rd GL, query facilities, no reporting, very large)
Marketing Data(external database)
Personnel Data(database)
Personnel App.(20 years old,
un-normalized data)
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Typical System Evolution
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Data Processing Manager
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Chief Information Officer
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CIO Responsibilities
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A job title commonly given to the most senior executive in an enterprise responsible for the information technology and computer systems that support enterprise goals
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CIO average tenure ...
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... and reporting relationships have remained stable for five years
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Qualifications
Leadership capabilities, business acumen and strategic perspectives have taken precedence over technical skills
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Data
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Skills Desired of CIOs• Technical/business
competencies • Timely and effective
execution• Being collaborative• Business knowledge• Creating a strategic vision• Inspire/leadership
responsibilities• Politically astute• Business acumen• Know of funding flows and
critical levers • Human capital management
• Talent evaluation, development, goal-setting and performance management
• Strategic-value creation• Creating revenue-
generating opportunities • Leadership• Influence others through
consensus building, storytelling, communications, modeling
• Networking, self-promotion, negotiating, empathy
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Data
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CIO Roles
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Data
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CIO Business & Technology Priorities
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Gartner 2008 Business Priorities
Top 10 Business Priorities Top 10 Technology Priorities
Business process improvement Business intelligence applications
Attracting and retaining new customers Enterprise applications (ERP, CRM, etc.)
Creating innovative products and services Servers and storage technologies
Expanding into new markets or geographies Legacy modernization/enhancement
Reducing enterprise costs Technical infrastructure
Improving enterprise workforce effectiveness Security technologies
Expanding current customer relationships Networking, voice and data
Increasing the use of information/analytics Collaboration technologies
Targeting customers/markets more effectively Document management
Acquiring new companies/capabilities Service-oriented architecture SOA
Data
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CIO Concerns 2007
1. People leadership2. Managing budgets3. Business alignment4. Infrastructure refresh5. Security6. Compliance7. Resource management8. Managing customers9. Managing change10. Board politics
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Data
1. Integrating systems and processes2. Strategic planning/aligning IT and organizational goals3. Project management improvements4. Security and privacy measures5. Lowering costs6. Line of business initiatives7. Staff development/retention/recruitment - datablueprint.com 6/18/2012 © Copyright this and previous years by Data Blueprint - all rights reserved!
Initiatives that will provide greatest value in FY 2008
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TechAmerica’s Nineteenth Annual Survey of Federal Chief Information Officers February 2009
Data
83.00%
76.00%
71.00%
68.00%
68.00%
66.00%
64.00%
64.00%
61.00%
60.00%
BI/Analytics
Virtualization
Governance/Risk/Compliance
Customer Collaboration
Mobility Solutions
Self-service Portals
Applications Harmonization
Business Process Management
Service-oriented Architecture
Unified Communications
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CIOs have visionary plans/CIO innovation is not limited to IT solutions
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Data
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2010 Gartner Top 10 CIO Technology Priorities
1. Cloud computing2. Virtualization3. Mobile technologies4. IT management5. Business intelligence6. Networking7. Voice and data communications8. Enterprise applications9. Collaboration technologies10. Infrastructure, and Web 2.0
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Data
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Global CIO: The Top 10 Issues For 20111. Seeing And Shaping The Future: Analytics2. The Budget Trap Becomes The Competitive-
Performance Gap: Doing more with less3. The iPad Explosion: Mobile Strategies4. Digitizing The Enterprise5. Social Media: From Grudging Acceptance To Hair-On-
Fire Evangelism6. Customer Engagement Soars To Unprecedented Levels7. Enabling The Massively Adaptable Data Center8. The CIO As Chief Acceleration Officer9. The Importance Of Being Global10. Optimizing Opportunities With Optimized Systems
http://www.informationweek.com/news/global-cio/interviews/229000361?pgno=1
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Data
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CIO's top 3 selection of business strategies in 2011 and projected for 2014
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Data
2005 2006 2007 2008 2009 2010 2011 0.000
0.200
0.400
0.600
0.800
IT/Infor
mation S
ecurity
/Privacy
Virtualiz
ation
Data ce
nter/IT
effici
encie
s/Clou
d
Social M
edia
Impro
ving p
eople
/leade
rship
BI/ana
lytics
Standa
rdizat
ion/co
nsolida
tion
IT workfor
ce de
velop
ment
IT gover
nance
Risk m
anag
emen
t
Mobile
applic
ations/
techn
ologie
s
Inform
ation S
harin
g
Imple
menting
plans/
initativ
es/ach
ieving
resul
ts
Acquisit
ion/pr
oject m
gt
Process
/syste
m integ
ration
Strateg
ic plan
ning
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Top Five Concerns
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Data
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We ask much of our CIOs
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It truly is a delicate balancing act!
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CFO Necessary Prerequisites/Qualifications
• CPA• CMA• Masters of Accountancy• Other recognized degrees/certifications
• These are necessary but insufficient prerequisites/qualifications
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With respect to CIOs• CIOs are not adopting data-centric
methods• Responsible for a great deal more
than just the organizational information
• Become expert in a vast array of skills in a rapidly changing environment
• A specific set of knowledge skills and abilities is required to manage organizational data as an asset
• These abilities are missing in most organizations.
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Comment from CIOs
• Most CIO’s today are challenged with being “experts” on technology (infrastructure and application), business process, relationship management and data management). None are successful at all and most have a bent towards only one of those areas, depending upon where they began their career and the path they took to attain their CIO role.
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Data Data
Data
Information
Fact Meaning
Request
A Model Specifying Relationships Among Important Terms
[Built on definition by Dan Appleton 1983]
Intelligence
Use
1. Each FACT combines with one or more MEANINGS. 2. Each specific FACT and MEANING combination is referred to as a DATUM. 3. An INFORMATION is one or more DATA that are returned in response to a
specific REQUEST 4. INFORMATION REUSE is enabled when one FACT is combined with more than
one MEANING.5. INTELLIGENCE is INFORMATION associated with its USES.
Wisdom & knowledge are often used synonymously
Data
Data
Data Data
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StandardData
Interrelationships among data management processes
Data Program Coordination
OrganizationalData Integration
DataStewardship
Data SupportOperations
Data Asset Use
Organizational Strategies
Goals
IntegratedModels
BusinessData
Business Value
Application Models & Designs
Feedback
Implementation
Direction
DataDevelopment
Guidance
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Assign responsibilities for data.
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Manage data coherently.
Share data across boundaries.
Engineer data delivery systems.
Maintain data availability.
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Data Program Coordination
Organizational Data Integration
Data Stewardship
Data Development
Data Support Operations
Data Management
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Our practices are ad hoc and dependent upon "heroes" and heroic efforts
Initial(1)
Repeatable(2) We have experience and have
the ability to implement disciplined processes
Capability Maturity Model Levels
Defined(3)
We have experience that we have standardized so that all in the organization
can follow it
Managed(4)
We manage our processes so that the whole organization can follow
our standard guidance
Optimizing(5)
We have a process for improving our
capabilities
One concept for process improvement, others include:
• Norton Stage Theory• TQM• TQdM• TDQM• ISO 9000
and focus on understanding current processes and determining where to make improvements.
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Assessment Components
Data Management Practice AreasData Management Practice AreasData program coordination
DM is practiced as a coherent and coordinated set of activities
Organizational data integration
Delivery of data is support of organizational objectives – the currency of DM
Data stewardship Designating specific individuals caretakers for certain data
Data development
Efficient delivery of data via appropriate channels
Data support Ensuring reliable access to data
4
Capability Maturity Model Levels
Examples of practice maturity
1 – Initial Our DM practices are ad hoc and dependent upon "heroes" and heroic efforts
2 - Repeatable We have DM experience and have the ability to implement disciplined processes
3 - Documented We have standardized DM practices so that all in the organization can perform it with uniform quality
4 - Managed We manage our DM processes so that the whole organization can follow our standard DM guidance
5 - Optimizing We have a process for improving our DM capabilities
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Development guidance
Data Adminstration
Support systems
Asset recovery capability
Development training
0 1 2 3 4 5Nokia Industry Competition All Respondents
Data Management Practices Assessment
Challenge
Challenge
Challenge
Client
Result 1
Result 2
Result 3
Result 4
Result 5
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Data Program Coordination
Organizational Data Integration
Data Stewardship
Data Development
Data Support Operations
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Data Management Practices Measurement (DMPA)
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Focus: Implementation
and Access
Focus: Guidance and
Facilitation
Optimizing (V)
Managed (IV)
Documented (III)
Repeatable (II)
Initial (I)
• CMU's Software Engineering Institute (SEI) Collaboration• Results from hundreds organizations in
various industries including:– Public Companies – State Government Agencies– Federal Government– International Organizations• Defined industry standard• Steps toward defining data
management "state of the practice"
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Comparison of DM Maturity 2007-2012
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0
1
2
3
Data Program Coordination Organizational Data Integration Data Stewardship Data Development Data Support Operations
2007 Maturity Levels 2012 Maturity Levels
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Designing for Evolution is Different than Creating New Systems
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Common Organizational Data (and corresponding data needs requirements)
New Organizational
Capabilities
Systems Development
Activities
Create
Evolve
Future State
(Version +1)
Data Architectures are Developed in Response to Organizational Needs
! ! ! !
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Organizational Needs
become instantiated and integrated into an Data/Information
Architecture
Informa(on)System)Requirements
authorizes and articulates sa
tisfy
spe
cific
org
aniz
atio
nal n
eeds
Results
Increasing scope and depth of information architecture utility
Individual SDLC Effort
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Individual SDLC efforts make increasing use from IA
• Over time the:– Number of requests increase– Utility of the results increase– Amount of metadata contributed by
new systems development increases
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Requirements
Design
Implement
Requests Results
Individual SDLC Effort
Requirements
Design
Implement
Requests
Results
Individual SDLC Effort
Requirements
Design
Implement
Requests
Organized system
metadata
Organized system
metadata
Organized system
metadata
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Arguments for not reporting to IT1. IT does not feel the true impact of poor DM practices
• Data problems can and often do delay IT projects and this causes the organization to pay more for IT services than it should. However the impact to the business of unmanaged/unmanageable data is greater than on IT. The business is more likely to suffer publicly from data problems while the impact of IT-related data failures is less likely to become know outside of the organization.
2. IT does not that they do not know organizational business rules that govern data and its use. • IT's focus on technical knowledge leaves little resources and few cycles to devote to
understanding how data is used by the business for various decisions.3. IT does not own or control access to the subject matter expertise ultimately needed
to implement business driven data centric data development practices. • Again, the focus on technical implementation details, keeps IT fully occupied with "how"
concerns. There is very little time for understanding business oriented, "what" problems.4. Only the business can competently assign values on various data uses.
• Defining what “good enough” for data management practices cannot be done from an IT perspective.
5. Reporting to IT has been expected because IT owned the method. • Since IT specializes in methods, IT was assumed to be the function to also manage the data.
Most non-IT folks have no idea that methods can be used to develop flexible, adaptable, and reusable data.
6. CIOs are already slammed. • Since CIOs are generally unsuccessful at remaining data-focused it is best to create a
position solely dedicated to just that function. 44
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Arguments for reporting to the business1. Appropriate division of labor.
• Since IT has its hand full with the how's of the systems, it is appropriate that the business take ownership of defining the organizational "what."
2. Reduction in organizational system requirements translations.
• The current organizational cycle begins with the business defining system requirements to IT who codifies these and relates them back to the business for verification.
3. Encourages business to learn appropriate IT-derived methods. • Maintaining the requirements (the "whats") in the business will
reduce translations and encourage broadly based, information systems-oriented thinking.
4. Better encourages data and architectural component reuse. • The longer-term focus of data is – at odds with IT development cycle
– DM is a program not a project.
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CIO’s are generally unsuccessful at remaining data-focused
• Question:– What is the hardest part of doing analysis?
• Answer:– Not doing design!
• Question:– What is the hardest part of a
CIO's job?• Answer:
– Remaining data focused!• Anything the CIO does that is not ...
– ... applying organizational data assets to the implementation of organizational strategy ...
... is a similar distraction46
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Enterprise Data Strategy Choices
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Q1Keeping the doors open
(little or no proactive data management)
Q2Increasing
organizational efficiencies/
effectiveness
Q3Using data to
create strategic
opportunities
Q4Both
Improve Operations
Inno
vatio
n
The Top Job• Finance• Operations• Sale/Marketing• HR• Risk• Technology/CIO
– Align IT initiatives with business goals– Improving IT operations performance– Cultivating the IT/business partnership– Cost control/expense management– Implementing new systems– Leading change efforts– Driving business innovation– Redesigning business processes– Developing and refining business strategy– Negotiating with IT vendors– Managing IT crises– Developing market strategies & technologies– Security management– Studying trends to identify opportunities
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Where does data go?
48... data
Information
Top Operations Job
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TDJ Reporting
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Top Job
Top Finance Job
Top Technology Job
Top Marketing Job
TopData Job
• There is enough work to justify the function• There is not much talent
Data Governance Organization
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Reporting Particulars1. Report outside of IT
and the current CIO altogether;
2. Report to the same organizational structure that the CFO and other "top" jobs report into; and
3. Focus on activities that are outside of (and more importantly) upstream from any system development lifecycle activities (SDLC).
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t
t
Strategy
Goals/Objectives
Systems/Applications
Network/Infrastructure
Data/Information
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t
• In support of strategy, the organization develops specific goals/objectives
• The goals/objectives drive the development of specific systems/applications
• Development of systems/applications leads to network/infrastructure requirements
• Data/information are typically considered after the systems/applications and network/infrastructure have been articulated
• Problems with this approach:– This ensures that data is formed
around the application and not the organizational information requirements
– Process are narrowly formed around applications
– Very little data reuse is possible
Application-Centric Development Flow
Original articulation from Doug Bagley @ Walmart
t
t
Strategy
Goals/Objectives
Data/Information
Network/Infrastructure
Systems/Applications
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t
• In support of strategy, the organization develops specific goals/objectives
• The goals/objectives drive the development of specific data/information assets with an eye to organization-wide usage
• Network/infrastructure components are developed to support organization-wide use of data
• Development of systems/applications is derived from the data/network architecture
• Advantages of this approach:– Data/information assets are
developed from an organization-wide perspective
– Systems support organizational data/information needs and compliment organizational process flows
– Data/information reuse is maximized
Data-Centric Development Flow
Original articulation from Doug Bagley @ Walmart
Advanced Data Practices• Cloud• MDM• Mining• Analytics• Warehousing• SOA
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• 5 Data Management Practices Areas– Data Program
Management– Organizational Data
Integration– Data Stewardship– Data Development– Data Support
Operations• Are necessary but
insufficient prerequisites to organizational data leveraging applications including:
– Cloud– MDM– Data Quality– Warehousing– Services
Hierarchy of Data Management PracticesData Management: Basics & Self Actualizing (after Maslow)
Basic Data Management Practices– Data Program Management– Organizational Data Integration– Data Stewardship– Data Development– Data Support Operations
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New division of labor
54
Business IT
Data Governance
Data Architecture Management
Data Quality Management
Document & Content Management
Data Warehousing/BI/Analytics
Reference & Master Data Management
Database Operations Management
Data Development
Metadata Management Metadata Operations Management
Data Security Specification Data Security Management
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Proposition
1. A rather serious gap exists in most organizations
2. The TDJ should be a business function
3. Any time the TDJ is paying attention to anything other than data supportfor strategy, they are diluting their own effectiveness
4. The TDJ is be a business leader who is the CTO's primary customer; requiring new, not-widely available KSAs
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Final Observation
• Fred Brooks Jr.'s argumentthat data representation is the essence of programming. – "Show me your flowchart and
conceal your tables, and I shall continue to be mystified. Show me your tables, and I won't usually need your flowchart; it'll be obvious."
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Experience PebblesContact Information:
Peter Aiken, Ph.D.
Department of Information Systems School of BusinessVirginia Commonwealth UniversitySnead Hall Room B4217301 West Main StreetRichmond, Virginia 23284-4000http://business.vcu.edu
Data Blueprint 10124C West Broad StreetGlen Allen VA 23060+1.804.521.4056http://datablueprint.com
office: +1.804.883.7594cell: +1.804.382.5957
e-mail: peter@datablueprint.comweb: http://peteraiken.net
57
http
://tw
itter
.com
/pai
ken