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Presented by Peter Aiken, Ph.D.
Data Architecture Requirements
Bryan Hogan, CDMP• Data Consultant • Certified Data
Management Professional
• Experience in …. – Organizational Data
Management Assessments – Data Strategy Development – ETL Process Development – Reporting Solutions – Software Development
• Worked in …. – Healthcare – Non-Profit – Finance
2Copyright 2016 by Data Blueprint Slide #
Peter Aiken, Ph.D.• 30+ years in data management • Repeated international recognition • Founder, Data Blueprint (datablueprint.com) • Associate Professor of IS (vcu.edu)
• DAMA International (dama.org) • 9 books and dozens of articles • Experienced w/ 500+ data
management practices • Multi-year immersions:
– US DoD (DISA/Army/Marines/DLA) – Nokia – Deutsche Bank – Wells Fargo – Walmart – …
• DAMA International President 2009-2013
• DAMA International Achievement Award 2001 (with Dr. E. F. "Ted" Codd
• DAMA International Community Award 2005
PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA
MONETIZINGDATA MANAGEMENT
Unlocking the Value in Your Organization’sMost Important Asset.
The Case for theChief Data OfficerRecasting the C-Suite to LeverageYour Most Valuable Asset
Peter Aiken andMichael Gorman
3Copyright 2016 by Data Blueprint Slide #
We believe ...
Data Assets
Financial Assets
RealEstate Assets
Inventory Assets
Non-depletable
Available for subsequent
use
Can be used up
Can be used up
Non-degrading √ √ Can degrade
over timeCan 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!
• Our mission is to unlock business value by – Strengthening your data management capabilities – Providing tailored solutions, and – Building lasting partnerships
4Copyright 2016 by Data Blueprint Slide #
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]
5Copyright 2016 by Data Blueprint Slide #
Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• NGO Data Architecture Case Study
• Take Aways, References & Q&A
You can accomplish Advanced Data Practices without becoming proficient in the Foundational Data Management Practices however this will: • Take longer • Cost more • Deliver less • Present
greaterrisk(with thanks to Tom DeMarco)
Data Management Practices Hierarchy
Advanced Data
Practices • MDM • Mining • Big Data • Analytics • Warehousing • SOA
Foundational Data Management Practices
Data Platform/Architecture
Data Governance Data Quality
Data Operations
Data Management Strategy
Technologies
Capabilities
Copyright 2016 by Data Blueprint Slide # 6
Data$Management$Strategy
Data Management GoalsCorporate CultureData Management FundingData Requirements Lifecycle
DataGovernance
Governance ManagementBusiness GlossaryMetadata Management
DataQuality
Data Quality FrameworkData Quality Assurance
DataOperations
Standards and ProceduresData Sourcing
Platform$&$Architecture
Architectural FrameworkPlatforms & Integration
Supporting$Processes
Measurement & AnalysisProcess ManagementProcess Quality AssuranceRisk ManagementConfiguration Management
Component Process$Areas
DMM℠ Structure of 5 Integrated DM Practice Areas
Data architecture implementation
Data Governance
Data Management
Strategy
Data Operations
PlatformArchitecture
SupportingProcesses
Maintain fit-for-purpose data, efficiently and effectively
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Manage data coherently
Manage data assets professionally
Data life cycle management
Organizational support
Data Quality
The DAMA Guide to the Data Management Body of Knowledge
8Copyright 2016 by Data Blueprint Slide #
Data Management Functions
Published by DAMA International
• The professional association for Data Managers (40 chapters worldwide)
DMBoK organized around
• Primary data management functions focused around data delivery to the organization
• Organized around several environmental elements
Data Architecture Management
9Copyright 2016 by Data Blueprint Slide #
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
10Copyright 2016 by Data Blueprint Slide #
Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• NGO Data Architecture Case Study
• Take Aways, References & Q&A
Architecture is both the process and product of planning, designing and constructing space that reflects functional, social, and aesthetic considerations. A wider definition may comprise all design activity from the macro-level (urban design, landscape architecture) to the micro-level (construction details and furniture). In fact, architecture today may refer to the activity of designing any kind of system and is often used in the IT world.
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Architecture
Architectures: here, whether you like it or not
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deviantart.com
• All organizations have architectures – Some are better
understood and documented (and therefore more useful to the organization) than others
Architecture Representation• Architectures are the symbolic
representation of the structure, use and reuse of resources
• Common components are represented using standardized notation
• Are sufficiently detailed to permit both business analysts and technical personnel to separately read the same model, and come away with a common understanding and yet they are developed effectively
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Understanding• 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
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OrganizationalArchitectures• 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
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• 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 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
Typically Managed Organizational Architectures
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• The underlying (information) design principals upon which construction is based
– Source: http://architecturepractitioner.blogspot.com/
• … are plans, guiding the transformation of strategic organizational information needs into specific information systems development projects
– Source: Internet
• A framework providing a structured description of an enterprise’s information assets — including structured data and unstructured or semistructured content — and the relationship of those assets to business processes, business management, and IT systems.
– Source: Gene Leganza, Forrester 2009
• "Information architecture is a foundation discipline describing the theory, principles, guidelines, standards, conventions, and factors for managing information as a resource. It produces drawings, charts, plans, documents, designs, blueprints, and templates, helping everyone make efficient, effective, productive and innovative use of all types of information."
– Source: Information First by Roger & Elaine Evernden, 2003 ISBN 0 7506 5858 4 p.1.
• Defining the data needs of the enterprise and designing the master blueprints to meet those needs
– Source: DM BoK
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Information Architecture
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Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• NGO Data Architecture Case Study
• Take Aways, References & Q&A
Data Architecture – A Useful Definition
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• Common vocabulary expressing integrated requirements ensuring that data assets are stored, arranged, managed, and used in systems in support of organizational strategy [Aiken 2010]
Data Architecture – A More Useful Definition
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• A structure of data-based information assets supporting implementation of organizational strategy (or strategies) [Aiken 2010]
• Most organizations have data assets that are not supportive of strategies - i.e., information architectures that are not helpful
• The really important question is: how can organizations more effectively use their information architectures to support strategy implementation?
Database Architecture Focus
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Program F
Program E
Program DProgram G
Program H
Program I
Applicationdomain 2Application
domain 3
databasearchitecture
engineeringeffort
Data
DataData
Data
Data Data
Data
Focus of asoftware
architectureengineering
effort Program A
Program B
Program C
Program F
Program E
Program DProgram G
Program H
Program I
Applicationdomain 1
Applicationdomain 2Application
domain 3
Data
Focus of a
Data
Data
Data Architecture Focus has Greater Potential Business Value
• Broader focus than either software architecture or database architecture
• Analysis scope is on the system wide use of data
• Problems caused by data exchange or interface problems
• Architectural goals more strategic than operational
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Why is Data Architecture Important?• Poorly understood
– Data architecture asset value is not well understood
• Inarticulately explained
– Little opportunity to obtain learning and experience
• Indirectly experienced
– Cost organizations millions each year in productivity, redundant and siloed efforts
– Example: Poorly thought out software purchases
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Moon Lighting
Practical Application of Data Architecting
Person Job Class
Employee Position
BR1) Zero, one, or more EMPLOYEES can be associated
with one PERSON
BR2) Zero, one, or more EMPLOYEES can be associated with one JOB CLASS;
BR3) Zero, one, or more EMPLOYEES can be associated with one POSITION
BR4) One or more POSITIONS can be associated with one JOB CLASS.
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Job Sharing
Running Query
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Optimized Query
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Repeat 100s, thousands, millions of times ...
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Death by 1000 Cuts
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Lack of coherent data architecture is a hidden expense• How does poor data architecture cost money? • Consider the opposite question:
– Were your systems explicitly designed to be integrated or otherwise work together?
– If not then what is the likelihood that they will work well together?
– They cannot be helpful as long as their structure is unknown
• Organizations spend between 20 - 40% of their IT budget evolving their data - including: – Data migration
• Changing the location from one place to another
– Data conversion • Changing data into another form, state, or product
– Data improving • Inspecting and manipulating, or re-keying data to prepare it for
subsequent use - Source: John Zachman
29Copyright 2016 by Data Blueprint Slide #
PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA
MONETIZINGDATA MANAGEMENT
Unlocking the Value in Your Organization’sMost Important Asset.
• Goal must be shared IT/business understanding – No disagreements = insufficient communication
• Data sharing/exchange is largely and highly automated and thus dependent on successful engineering – It is critical to engineer a sound foundation of data modeling basics
(the essence) on which to build advantageous data technologies • Modeling characteristics change over the course of analysis
– Different model instances may be useful to different analytical problems • Incorporate motivation (purpose statements) in all modeling
– Modeling is a problem defining as well as a problem solving activity - both are inherent to architecture
• Use of modeling is much more important than selection of a specific modeling method
• Models are often living documents – The more easily it adapts to change, the resource utilization
• Models must have modern access/interface/search technologies – Models need to be available in an easily searchable manner
• Utility is paramount – Adding color and diagramming objects customizes models and allows for a more
engaging and enjoyable user review process
Data Architecting for Business Value
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Inspired by: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2
Architecture Example
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Poor Quality Foundation
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What they think they are purchasing!
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Levels of Abstraction, Completeness and Utility
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• Models more downward facing - detail
• Architecture is higher level of abstraction - integration
• In the past architecture attempted to gain complete (perfect) understanding
– Not timely
– Not feasible
• Focus instead on architectural components
– Governed by a framework
– More immediate utility
• http://www.architecturalcomponentsinc.com
Too Much Detail
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What do you use an information architecture for?
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Illustration by murdock23 @ http://designfestival.com/information-architecture-as-part-of-the-web-design-process/
Web Developers Understand IA
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http://www.jeffkerndesign.com
Web Developers Understand IA
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http://www.jeffkerndesign.com
How are data structures expressed as architectures?
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A B
C D
A B
C D
A
D
C
B
• Details are organized into larger components
• Larger components are organized into models
• Models are organized into architectures
How are Data Models Expressed as Architectures?
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More Granular
More Abstract
• Attributes are organized into entities/objects – Attributes are characteristics of "things" – Entitles/objects are "things" whose information is
managed in support of strategy – Examples
• Entities/objects are organized into models – Combinations of attributes and entities are structured
to represent information requirements – Poorly structured data, constrains organizational
information delivery capabilities – Examples
• Models are organized into architectures – When building new systems, architectures are used
to plan development – More often, data managers do not know what
existing architectures are and - therefore - cannot make use of them in support of strategy implementation
– Why no examples?
Data Data
Data
Information
Fact Meaning
Request
Data must be Architected to Deliver Value
[Built on definitions from Dan Appleton 1983]
Intelligence
Strategic 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 STRATEGIC USES. 6. DATA/INFORMATION must formally arranged into an ARCHITECTURE.
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Wisdom & knowledge are often used synonymously
Data
Data
Data Data
How do data structures support organizational strategy?
• Two answers
– Achieving efficiency and effectiveness goals
– Providing organizational dexterity for rapid implementation
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Computers
Human resources
Communication facilities
Software
Managementresponsibilities
Policies,directives,and rules
Data
What Questions Can Data Architectures Address?• How and why do the data
components interact? • Where do they go? • When are they needed? • Why and how will the
changes be implemented? • What should be managed
organization-wide and what should be managed locally?
• What standards should be adopted?
• What vendors should be chosen?
• What rules should govern the decisions?
• What policies should guide the process?
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! ! ! !
Data Architectures produce and are made up of information models that 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
45Copyright 2016 by Data Blueprint Slide #
Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• NGO Data Architecture Case Study
• Take Aways, References & Q&A
Data Leverage
• Permits organizations to better manage their sole non-depleteable, non-degrading, durable, strategic asset - data – within the organization, and – with organizational data exchange partners
• Leverage – Obtained by implementation of data-centric technologies, processes, and
human skill sets – Increased by elimination of data ROT (redundant, obsolete, or trivial)
• The bigger the organization, the greater potential leverage exists
• Treating data more asset-like simultaneously 1. lowers organizational IT costs and 2. increases organizational knowledge worker productivity
46Copyright 2016 by Data Blueprint Slide #
Less ROT
Technologies
Process
People
Architecture Evolution
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Conceptual Logical Physical
Validated
Not UnValidated
Every change can be mapped to a transformation in this framework!
IT Project or Application-Centric Development
Original articulation from Doug Bagley @ Walmart
48Copyright 2016 by Data Blueprint Slide #
Data/Information
ITProjects
Strategy
• In support of strategy, organizations implement IT projects
• Data/information are typically considered within the scope of IT projects
• Problems with this approach: – Ensures data is formed to the
applications and not around the organizational-wide information requirements
– Process are narrowly formed around applications
– Very little data reuse is possible
Data-Centric Development
Original articulation from Doug Bagley @ Walmart
49Copyright 2016 by Data Blueprint Slide #
ITProjects
Data/Information
Strategy
• In support of strategy, the organization develops specific, shared data-based goals/objectives
• These organizational data goals/objectives drive the development of specific IT projects with an eye to organization-wide usage
• Advantages of this approach: – Data/information assets are developed from an
organization-wide perspective
– Systems support organizational data needs and compliment organizational process flows
– Maximum data/information reuse
Engineering
Architecture
Engineering/Architecting Relationship• Architecting is used to
create and build systems too complex to be treated by engineering analysis alone
• Architects require technical details as the exception
• Engineers develop the technical designs
• Craftsman deliver components supervised by: – Building Contractor
– Manufacturer
Copyright 2016 by Data Blueprint Slide # 50
USS Midway & Pancakes
What is this?
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• It is tall • It has a clutch • It was built in 1942 • It is still in regular use!
Engineering Standards
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Architectural Work ProductComponents may be defined as:
• The intersection of common business functionality and the subsets of the organizational technology and data architectures used to implement that functionality
• Component definition is an important activity because CM2 component engineering is focused on an entire component as an analysis unit. A concrete example of a component might be
– The business processes, the technology and the data supporting organizational human resource benefits operations. This same component could be described simply as the "PeopleSoft™ version 7.5 benefits module implemented on Windows 95." illustrates the integration of the three primary PeopleSoft metadata structures describing the: business processes used to organization the work flow, menu navigation required to access system functionality, and data which when combined with meanings provided by the panels provided information to the knowledge workers.
53Copyright 2016 by Data Blueprint Slide #
SystemProcess
Process2
Process1
Process3
Subprocess1.1
Subprocess1.2
Subprocess1.3
Hierarchical System Functional Decomposition
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Level 1 Level 2 Level 3Pay Employment Recruitmentand Selectionpersonnel Personnel Employee relations
administration Employee compensation changesSalary planningClassification and payJob evaluationBenefits administrationHealth insurance plansF lexible spending accountsGroup life insurance
Retirement plansPayroll Payroll administration
Payroll processingPayroll interfaces
Development N/ATrainingadministration
Career planning and skillsinventoryWork group activities
Health andsafety
Accidents and workerscompensationHealth and safety programs
A three-level decomposition of the model views from a governmental pay and personnel scenario
55Copyright 2016 by Data Blueprint Slide #
H ealth car e system1 Patient administration 1.1 R egistration1.2 Admission1.3 Disposition1.4 Transfer1.5 M edical record1.6 Administration1.7 Patient bi l l ing1.8 Patient affairs1.9 Patient management2 Patient appointments
and sche d ul ing 2.1 Create or maintain
schedules2.2 Appoint patients2.3 R ecord patient encounter2.4 I dentify patient2.5 I dentify health care
provider3 Nursing 3.1 Patient care3.2 Unit management4 Laboratory 4.1 R esults reporting4.2 Specimen processing4.3 R esult entry processing4.4 Laboratory management4.5 Workload support5 Pharmacy 5.1 Unit dose dispensing5.2 Control led Drug
I nventory5.3 Outpatient
6 R adiology 6.1 Schedul ing6.2 E xam processing6.3 E xam reporting6.4 Special interest and
teaching6.5 R adiology workload
reporting7 C l inical dietetics 7.1 E stabl ish parameters7.2 R eceive diet orders8 Order entry and r e sults 8.1 R eporting8.2 E nter and maintain
orders8.3 Obtain results8.4 R eview patient
information8.5 C l inical desktop9 System management 9.1 Logon and security
management9.2 Archive run
M anagement9.3 Communication software9.4 M anagement9.5 Site management10 Faci l ity qual ity assurance 10.1 Provider credential ing10.2 M onitor and evaluation
A relatively complex model view decomposition
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DSS
"Governors"
Taxpayers Clients
Vendors Program Deliver
Data model is comprised of model views
DSS Strategic Data Model Taxpayer view
Client view
Governance view
Program Delivery view
Vendor view
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Taxpayer view
Payments Taxpayers
SocialServicePrograms
TaxpayerBenefits
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Client view
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Payments
Clients ClientBenefits
LocalWellfareAgencies
Governance view
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Payments
SocialServicePrograms
GovernmentalResources
Governance Governments
State Boardof SocialServices
PolicyApproval
SocialServicePrograms
Clients
ServiceDeliveryPartners
LocalWellfareAgencies
Program Delivery view
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Payments
SocialServicePrograms
Clients
LocalWellfareAgencies
GoodsandServices
Vendors
Vendor view
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GovernmentalResources
Governance Governments Payments Taxpayers
State Boardof SocialServices
SocialServicePrograms
Clients ClientBenefits
TaxpayerBenefits
PolicyApproval
ServiceDeliveryPartners
LocalWellfareAgencies
GoodsandServices
Vendors
DSS Strategic Level Data Model
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Payments
SocialServicePrograms
GovernmentalResources
Governance Governments
State Boardof SocialServices
PolicyApproval
Payments
Clients ClientBenefits
LocalWellfareAgencies
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Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• NGO Data Architecture Case Study
• Take Aways, References & Q&A
• Non-Governmental Organization (NGO) • Non-Profit • Industry
– Address Priority Health Concerns for Developing Countries • HIV & AIDS • Malaria • Etc…
– Provide Leadership Training – Health Information System Management
• Function – Project Management and Design for
Health Care Implementations
• Operates – Globally (30 + Countries)
Background
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Problem• Data needed to make key business decisions was not
accessible across the Enterprise
– Timeliness
– Accuracy
– Data Isolation
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Root Cause• No Enterprise-Wide understanding of its data assets
– Conceptual Data Model
• NGO does not have a common vocabulary
– Enterprise-Wide Taxonomy
• NGO lacks existing System and Data Architecture
– Vision
– Not Aligned with Business Model
– “Shiny Object Syndrome”
– Minimal Integration
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Solution• Vision and Purpose
– Data Architecture
• Business Glossary
• Enterprise Conceptual Data Model
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Vision and Purpose
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TARGET STATE VISIONCOLLABORATION & WIP DOCUMENTS
Talent Management
Business Development
Project Management
CAPTURE DATA
INTEGRATE DATA
Talent Management
Financial Management
Business Development
Project Management
CREATE REPORTS AND PERFORM BI
STORE CORPORATE DATA
MANAGE CONTENT
Financial Management
DATA GOVERNANCE
• 100,000 ft. View • Represents the processes,
procedures, and technologies that make up the Components
• Federated Data Architecture (FDA) • FDA supports the business
strategy • Set of entities (Projects)
that have a level of autonomy to support its goal while a unifying entity (Shared Services from Corporate) provides a framework and definition on how data is to managed and captured
Business Glossary
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Entity Description Domain AreaDonor Funder Business DevelopmentSolicitations Need for Work Business DevelopmentSolicitations Proposal Response to Need for Work Business DevelopmentPre-Positioning Intelligence Gathering Business DevelopmentAward/Sub-Award Funding Vehicle Business DevelopmentTerms Conditions Details about a Funding Vehicle Business DevelopmentBudget Amount of Money Available Business DevelopmentWork Plan Set of Activities to Complete Business DevelopmentPMP Monitoring Plan for Activities Business Development
Project
An NGO Project is defined as a self-contained set of interventions or activities with the following characteristics:a) an external client;b) purchase order, contract or agreement;c) expected deliverables, outcomes and results;d) a beginning and end date of implementation; e) an approved budget; and full and/or part time NGO staff Project Management
Geographic Area Project Management
Office LocationsLocation in which a Central Office resides Project Management
Project Roles Project ManagementProject Artifacts Project ManagementProject Budget Project ManagementProject Work Plan Project ManagementMilestones Schedule of completed activities Project ManagementMonitoring Plan to measure Activities Project ManagementEvaluation Assessment of Activities Project ManagementIndicators Target of Outcome Project Management
OutcomesStatement of what needs to be accomplished Project Management
Acct Receivable Payments to NGO Financial ManagementChart of Accounts Defined Accounts Financial ManagementPayroll Process to Pay Worker Financial ManagementSupplier Provider of Goods or Service Financial ManagementContract Binding Agreement Financial ManagementPurchase Order Statement of Good or Service Financial ManagementPerformance Level of Success Talent ManagementBenefits Talent ManagementSkills Talent Management
WorkerPerson who has been hired by NGO Talent Management
Candidate Potential hire of NGO Talent Management
• Start of Enterprise Taxonomy
• Defines Initial Entities for Conceptual Data Model
• Engages the Business Community to Validate Entities and provide meaningful business definitions
Ente
rpris
e C
once
ptua
l Dat
a M
odel • Linkages
across Business Functions
• How Data flows throughout Enterprise
• Impact from Data Changes
• Defines Common Vocabulary
• Aligning the Data to support the Organizational Strategy
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Business Value• Supports Organizational Strategy
• Reduced IT Costs
• Data Asset Knowledge and Reuse
• Accurate and Timely Reporting
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Supports Organizational Strategy• Defining a common vocabulary across the enterprise
increases cohesion between the Business and IT.
• Cohesion allows IT to effectively support the Organizational Strategy
• Understanding the business’s needs
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Understanding
Reduced IT Costs• Data Architecture guides IT on software implementations
– Mitigates “poor” software purchases
– Reduces cost of implementations
• Maintaining and Managing the Data Landscape
– A defined Data Architecture allows IT to manage and maintain the critical pieces of the Data Landscape
– Reduces cost of trying to manage and maintain everything
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Data Asset Knowledge and Reuse• Knowledge of how the Organization’s Data can be
leveraged
– Increased Organizational Learning
• Identified Key Integration Points
– Allows IT to focus on the critical Data Assets
– Increases Re-Use of Data Assets for future Integrations
• Identified Impact to Data Flows
– Allows IT to plan for future implementations
– Reduces impact to the Organizational existing Data Assets
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• Reduce Time Building Reports
– Faster Decision Making
– Single Source of Truth
• Less “Massaging” of Data
– Increased Productivity from Knowledge Workers
– Decreased Errors from compiling redundant data
Accurate and Timely Reporting
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DATA
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Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• NGO Data Architecture Case Study
• Take Aways, References & Q&A
Would you build a house without an architecture sketch?
Model is the sketch of the system to be built in a project.
Would you like to have an estimate how much your new house is going to cost?
Your model gives you a very good idea of how demanding the implementation work is going to be!
If you hired a set of constructors from all over the world to build your house, would you like them to have a common language?
Model is the common language for the project team.
Would you like to verify the proposals of the construction team before the work gets started?
Models can be reviewed before thousands of hours of implementation work will be done.
If it was a great house, would you like to build something rather similar again, in another place?
It is possible to implement the system to various platforms using the same model.
Would you drill into a wall of your house without a map of the plumbing and electric lines?
Models document the system built in a project. This makes life easier for the support and maintenance!
Why Architect Data?
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Take Aways• What is an information architecture?
– A structure of data-based information assets supporting implementation of organizational strategy
– Most organizations have data assets that are not supportive of strategies - i.e., information architectures that are not helpful
– The really important question is: how can organizations more effectively use their information architectures to support strategy implementation?
• What is meant by use of an information architecture? – Application of data assets towards organizational strategic objectives – Assessed by the maturity of organizational data management practices – Results in increased capabilities, dexterity, and self awareness – Accomplished through use of data-centric development practices (including
taxonomies, stewardship, and repository use)
• How does an organization achieve better use of its information architecture? – Continuous re-development; the starting point isn't the beginning – Information architecture components must typically be reengineered – Using an iterative, incremental approach, typically focusing on one component at a time
and applying formal transformations
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Questions?
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PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA
MONETIZINGDATA MANAGEMENT
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