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Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden

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Peter Aiken, Ph.D.
Data Architecture Strategies
Constructing your data garden
Peter Aiken, Ph.D.
• 30+ years in data manag...
Bryan Hogan, CDMP
• Data Consultant
• Certified Data
Management
Professional
• Experience in ….
– Organizational Data
Mana...
5Copyright 2017 by Data Blueprint Slide #
Data Architecture Requirements
• Context: Data Management/DAMA/DM BoK/CDMP?
• Wh...
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Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden

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Data architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong data architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.

The goal of this webinar is not to instruct you in being an outright data architect, but rather to enable you to envision a number of uses for data architectures that will maximize your organization’s competitive advantage.

With that being said, we will:

- Discuss data architecture’s guiding principles and best practices
- Demonstrate how to utilize data architecture to address a broad variety of organizational challenges and support your overall business strategy
- Illustrate how best to understand foundational data architecture concepts based on the DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK)

Data architecture is foundational to an information-based operational environment. Without proper structure and efficiency in organization, data assets cannot be utilized to their full potential, which in turn harms bottom-line business value. When designed well and used effectively, however, a strong data architecture can be referenced to inform, clarify, understand, and resolve aspects of a variety of business problems commonly encountered in organizations.

The goal of this webinar is not to instruct you in being an outright data architect, but rather to enable you to envision a number of uses for data architectures that will maximize your organization’s competitive advantage.

With that being said, we will:

- Discuss data architecture’s guiding principles and best practices
- Demonstrate how to utilize data architecture to address a broad variety of organizational challenges and support your overall business strategy
- Illustrate how best to understand foundational data architecture concepts based on the DAMA International Guide to Data Management Body of Knowledge (DAMA DMBOK)

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Data-Ed Slides: Data Architecture Strategies - Constructing Your Data Garden

  1. 1. Peter Aiken, Ph.D. Data Architecture Strategies Constructing your data garden 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 BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset. The Case for the Chief Data Officer Recasting the C-Suite to Leverage Your MostValuable Asset Peter Aiken and Michael Gorman 2Copyright 2017 by Data Blueprint Slide #
  2. 2. 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 3Copyright 2017 by Data Blueprint Slide # 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 √ √ √ √ We believe ... • 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 2017 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] Data Assets Win!
  3. 3. 5Copyright 2017 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 ArchitectureJargon 6Copyright 2017 by Data Blueprint Slide #
  4. 4. 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 
 greater
 risk
(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 2017 by Data Blueprint Slide # 7 Data$Management$ Strategy Data Management Goals Corporate Culture Data Management Funding Data Requirements Lifecycle Data Governance Governance Management Business Glossary Metadata Management Data Quality Data Quality Framework Data Quality Assurance Data Operations Standards and Procedures Data Sourcing Platform$&$ Architecture Architectural Framework Platforms & Integration Supporting$ Processes Measurement & Analysis Process Management Process Quality Assurance Risk Management Configuration Management Component Process$Areas DMM℠ Structure of 
 5 Integrated 
 DM Practice Areas Data architecture implementation Data 
 Governance Data 
 Management
 Strategy Data 
 Operations Platform
 Architecture Supporting
 Processes Maintain fit-for-purpose data, efficiently and effectively 8Copyright 2017 by Data Blueprint Slide # Manage data coherently Manage data assets professionally Data life cycle management Organizational support Data 
 Quality
  5. 5. The DAMA Guide to the Data Management Body of Knowledge 9Copyright 2017 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 Architecture • Things – (components) • The functions of the things – (individually) • How the things interact – (as a system, towards a goal) 10Copyright 2017 by Data Blueprint Slide #
  6. 6. Data Architecture Management • Definition – Defining the data needs of the enterprise and designing the master blueprints to meet those needs • Goals 1. To plan with vision and foresight to provide high-quality data 2. To identify and define common data requirements 3. To design conceptual structures and plans to meet the current and long-term data requirements of the enterprise 11Copyright 2017 by Data Blueprint Slide # from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International Data Architecture Management 12Copyright 2017 by Data Blueprint Slide # from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
  7. 7. 13Copyright 2017 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. 14Copyright 2017 by Data Blueprint Slide # Architecture
  8. 8. Architectures: here, whether you like it or not 15Copyright 2017 by Data Blueprint Slide # 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 • Architectures are sufficiently detailed to permit both business analysts and technical personnel to separately read the same model, and come away with a common understanding 16Copyright 2017 by Data Blueprint Slide #
  9. 9. 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 17Copyright 2017 by Data Blueprint Slide # 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 18Copyright 2017 by Data Blueprint Slide #
  10. 10. • 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 19Copyright 2017 by Data Blueprint Slide # • 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 20Copyright 2017 by Data Blueprint Slide # Information Architecture
  11. 11. 21Copyright 2017 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 Architecture – A Useful Definition 22Copyright 2017 by Data Blueprint Slide # • Common vocabulary expressing integrated requirements ensuring that data assets are stored, arranged, managed, and used in systems in support of organizational strategy [Aiken 2010]
  12. 12. Data Architecture – A More Useful Definition 23Copyright 2017 by Data Blueprint Slide # • 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 24Copyright 2017 by Data Blueprint Slide # Program F Program E Program D Program G Program H Program I Application domain 2Application domain 3
  13. 13. database architecture engineering effort DataData DataData Data Data Data Focus of a software architecture engineering effort Program A Program B Program C Program F Program E Program D Program G Program H Program I Application domain 1 Application domain 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 25Copyright 2017 by Data Blueprint Slide # 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 26Copyright 2017 by Data Blueprint Slide # Higher res image available?
  14. 14. 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. 27Copyright 2017 by Data Blueprint Slide # Job Sharing Running Query 28Copyright 2017 by Data Blueprint Slide #
  15. 15. Optimized Query 29Copyright 2017 by Data Blueprint Slide # Repeat 100s, thousands, millions of times ... 30Copyright 2017 by Data Blueprint Slide #
  16. 16. Death by 1000 Cuts 31Copyright 2017 by Data Blueprint Slide # 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 32Copyright 2017 by Data Blueprint Slide # PETER AIKEN WITH JUANITA BILLINGS FOREWORD BY JOHN BOTTEGA MONETIZING DATA MANAGEMENT Unlocking the Value in Your Organization’s Most Important Asset.
  17. 17. • 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 33Copyright 2017 by Data Blueprint Slide # Inspired by: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2 Good Architectural Foundation? 34Copyright 2017 by Data Blueprint Slide #
  18. 18. Poor Quality Foundation 35Copyright 2017 by Data Blueprint Slide # What they think they are purchasing! 36Copyright 2017 by Data Blueprint Slide #
  19. 19. Levels of Abstraction, Completeness and Utility 37Copyright 2017 by Data Blueprint Slide # • 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 38Copyright 2017 by Data Blueprint Slide #
  20. 20. What do you use an information architecture for? 39Copyright 2017 by Data Blueprint Slide # Illustration by murdock23 @ http://designfestival.com/information-architecture-as-part-of-the-web-design-process/ Web Developers Understand IA 40Copyright 2017 by Data Blueprint Slide # http://www.jeffkerndesign.com
  21. 21. Web Developers Understand IA 41Copyright 2017 by Data Blueprint Slide # http://www.jeffkerndesign.com How are data structures expressed as architectures? 42Copyright 2017 by Data Blueprint Slide # 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
  22. 22. How are Data Models Expressed as Architectures? 43Copyright 2017 by Data Blueprint Slide # 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. 44Copyright 2017 by Data Blueprint Slide # Wisdom & knowledge are 
 often used synonymously Data Data Data Data
  23. 23. How do data structures support organizational strategy? • Two answers – Achieving efficiency and effectiveness goals – Providing organizational dexterity for rapid implementation 45Copyright 2017 by Data Blueprint Slide # Computers Human resources Communication facilities Software Management responsibilities 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? 46Copyright 2017 by Data Blueprint Slide #
  24. 24. ! ! ! ! Data Architectures produce and are made up of information models 
 that are developed in response to organizational needs 47Copyright 2017 by Data Blueprint Slide # Organizational Needs become instantiated 
 and integrated into an Data/Information
 Architecture Informa(on)System) Requirements authorizes and 
 articulates satisfyspecificorganizationalneeds 48Copyright 2017 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
  25. 25. Data Leverage • Permits organizations to better manage their sole non-depletable, 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 49Copyright 2017 by Data Blueprint Slide # Less ROT Technologies Process People Architecture Evolution 50Copyright 2017 by Data Blueprint Slide # Conceptual Logical Physical Validated Not UnValidated Every change can be mapped to a transformation in this framework!
  26. 26. IT Project or Application-Centric Development Original articulation from Doug Bagley @ Walmart 51Copyright 2017 by Data Blueprint Slide # Data/ Information IT
 Projects 
 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 52Copyright 2017 by Data Blueprint Slide # IT
 Projects 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
  27. 27. 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 2017 by Data Blueprint Slide # 53 USS Midway & Pancakes What is this? 54Copyright 2017 by Data Blueprint Slide # • It is tall • It has a clutch • It was built in 1942 • It is still in regular use!
  28. 28. Engineering Standards 55Copyright 2017 by Data Blueprint Slide # Architectural Work Product Components 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. 56Copyright 2017 by Data Blueprint Slide #
  29. 29. System Process Process 2 Process 1 Process 3 Subprocess 1.1 Subprocess 1.2 Subprocess 1.3 Hierarchical System Functional Decomposition 57Copyright 2017 by Data Blueprint Slide # Level 1 Level 2 Level 3 Pay Employment Recruitment and Selection personnel Personnel Employee relations administration Employee compensation changes Salary planning Classification and pay Job evaluation Benefits administration Health insurance plans F lexible spending accounts Group life insurance Retirement plans Payroll Payroll administration Payroll processing Payroll interfaces Development N/A Training administration Career planning and skills inventory Work group activities Health and safety Accidents and workers compensation Health and safety programs A three-level decomposition of the model views from a governmental pay and personnel scenario 58Copyright 2017 by Data Blueprint Slide #
  30. 30. H ealth car e system 1 Patient administration 1.1 R egistration 1.2 Admission 1.3 Disposition 1.4 Transfer 1.5 M edical record 1.6 Administration 1.7 Patient billing 1.8 Patient affairs 1.9 Patient management 2 Patient appointments and scheduling 2.1 Create or maintain schedules 2.2 Appoint patients 2.3 R ecord patient encounter 2.4 I dentify patient 2.5 I dentify health care provider 3 Nursing 3.1 Patient care 3.2 Unit management 4 Laboratory 4.1 R esults reporting 4.2 Specimen processing 4.3 R esult entry processing 4.4 Laboratory management 4.5 Workload support 5 Pharmacy 5.1 Unit dose dispensing 5.2 Controlled Drug I nventory 5.3 Outpatient 6 R adiology 6.1 Scheduling 6.2 E xam processing 6.3 E xam reporting 6.4 Special interest and teaching 6.5 R adiology workload reporting 7 Clinical dietetics 7.1 E stablish parameters 7.2 R eceive diet orders 8 Order entry and results 8.1 R eporting 8.2 E nter and maintain orders 8.3 Obtain results 8.4 R eview patient information 8.5 Clinical desktop 9 System management 9.1 Logon and security management 9.2 Archive run M anagement 9.3 Communication software 9.4 M anagement 9.5 Site management 10 Facility quality assurance 10.1 Provider credentialing 10.2 M onitor and evaluation A relatively complex model view decomposition 59Copyright 2017 by Data Blueprint Slide # 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 60Copyright 2017 by Data Blueprint Slide #
  31. 31. Taxpayer view Payments Taxpayers Social Service Programs Taxpayer Benefits 61Copyright 2017 by Data Blueprint Slide # Client view 62Copyright 2017 by Data Blueprint Slide # Payments Clients Client Benefits Local Wellfare Agencies
  32. 32. Governance view 63Copyright 2017 by Data Blueprint Slide # Payments Social Service Programs Governmental Resources Governance Governments State Board of Social Services Policy Approval Social Service Programs Clients Service Delivery Partners Local Wellfare Agencies Program Delivery view 64Copyright 2017 by Data Blueprint Slide #
  33. 33. Payments Social Service Programs Clients Local Wellfare Agencies Goods and Services Vendors Vendor view 65Copyright 2017 by Data Blueprint Slide # Governmental Resources Governance Governments Payments Taxpayers State Board of Social Services Social Service Programs Clients Client Benefits Taxpayer Benefits Policy Approval Service Delivery Partners Local Wellfare Agencies Goods and Services Vendors DSS Strategic Level Data Model 66Copyright 2017 by Data Blueprint Slide # Payments Social Service Programs Governmental Resources Governance Governments State Board of Social Services Policy Approval Payments Clients Client Benefits Local Wellfare Agencies
  34. 34. 67Copyright 2017 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 • 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 68Copyright 2017 by Data Blueprint Slide #
  35. 35. Problem • Data needed to make key business decisions was not accessible across the Enterprise – Timeliness – Accuracy – Data Isolation 69Copyright 2017 by Data Blueprint Slide # 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 70Copyright 2017 by Data Blueprint Slide #
  36. 36. Solution • Vision and Purpose – Data Architecture • Business Glossary • Enterprise Conceptual Data Model 71Copyright 2017 by Data Blueprint Slide # Vision and Purpose 72Copyright 2017 by Data Blueprint Slide # TARGET STATE VISION COLLABORATION & WIP DOCUMENTS Talent Management Business Development Project Management CAPTURE DATA INTEGRATE DATA Talent Management Financial Management Business Development Project Management CREATEREPORTSANDPERFORMBI STORECORPORATEDATA MANAGE CONTENT Financial Management DATAGOVERNANCE • 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
  37. 37. Business Glossary 73Copyright 2017 by Data Blueprint Slide # Entity Description Domain Area Donor Funder Business Development Solicitations Need for Work Business Development Solicitations Proposal Response to Need for Work Business Development Pre-Positioning Intelligence Gathering Business Development Award/Sub-Award Funding Vehicle Business Development Terms Conditions Details about a Funding Vehicle Business Development Budget Amount of Money Available Business Development Work Plan Set of Activities to Complete Business Development PMP 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 Locations Location in which a Central Office resides Project Management Project Roles Project Management Project Artifacts Project Management Project Budget Project Management Project Work Plan Project Management Milestones Schedule of completed activities Project Management Monitoring Plan to measure Activities Project Management Evaluation Assessment of Activities Project Management Indicators Target of Outcome Project Management Outcomes Statement of what needs to be accomplished Project Management Acct Receivable Payments to NGO Financial Management Chart of Accounts Defined Accounts Financial Management Payroll Process to Pay Worker Financial Management Supplier Provider of Goods or Service Financial Management Contract Binding Agreement Financial Management Purchase Order Statement of Good or Service Financial Management Performance Level of Success Talent Management Benefits Talent Management Skills Talent Management Worker Person 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 EnterpriseConceptualDataModel • Linkages across Business Functions • How Data flows throughout Enterprise • Impact from Data Changes • Defines Common Vocabulary • Aligning the Data to support the Organizational Strategy 74Copyright 2017 by Data Blueprint Slide #
  38. 38. Business Value • Supports Organizational Strategy • Reduced IT Costs • Data Asset Knowledge and Reuse • Accurate and Timely Reporting 75Copyright 2017 by Data Blueprint Slide # 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 76Copyright 2017 by Data Blueprint Slide # Understanding Resized & moved "Understanding"
  39. 39. 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 77Copyright 2017 by Data Blueprint Slide # 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 78Copyright 2017 by Data Blueprint Slide #
  40. 40. • 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 79Copyright 2017 by Data Blueprint Slide # DATA 80Copyright 2017 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
  41. 41. 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? 81Copyright 2017 by Data Blueprint Slide # 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 82Copyright 2017 by Data Blueprint Slide #
  42. 42. 83Copyright 2017 by Data Blueprint Slide # Organizational
 Strategy Data Strategy IT Projects Organizational Operations Data Governance Data Strategy and Data Governance in Context Data asset support for 
 organizational strategy What the data assets do to support strategy How well the data strategy is working Operational feedback How data is delivered by IT How IT supports strategy Other aspects of organizational strategy Questions? 84Copyright 2017 by Data Blueprint Slide # + =
  43. 43. March Webinar: The Importance of MDM
 Eternal Management of the Data Mind March 14, 2017 @ 2:00 PM ET/11:00 AM PT April Webinar: Data Modeling Strategies
 Getting Your Data Ready for the Catwalk April 11, 2017 @ 2:00 PM ET/11:00 AM PT Sign up at: www.datablueprint.com/webinar-schedule Enterprise Data World 2017 (Atlanta): Implementing a Data-Centric Strategy & Roadmap: 
 Planning Not to Fail Importance of MDM
 April 3, 2017 @ 1:30 PM ET
 Using Data to Help Improve People's Everyday Lives
 April 5, 2017 @ 1:30 PM ET Upcoming Events 85 Copyright 2017 by Data Blueprint Slide # Brought to you by:

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