Post on 14-Jul-2015
transcript
Data architecture is foundational to an information-based operational environment. It is your data architecture that organizes your data assets so they can be leveraged in your business strategy to create real business value. Even though this is important, not all data architectures are used effectively. This webinar describes the use of data architecture as a basic analysis method. Various uses of data architecture to inform, clarify, understand, and resolve aspects of a variety of business problems will be demonstrated. As opposed to showing how to architect data, your presenter Dr. Peter Aiken, will show how to use data architecting to solve business problems. The goal is for you to be able to envision a number of uses for data architectures that will raise the perceived utility of this analysis method in the eyes of the business.
Welcome: Data Architecture Requirements
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Copyright 2015 by Data Blueprint
Program F
Program E
Program DProgram G
Program H
Program I
Applicationdomain 2Application
domain 3
Date: March 9, 2015 Time: 2:00 PM ET Presented by: Peter Aiken, PhD
Two Most Commonly Asked Questions
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1. Will I get copies of the slides after the event?
2. Is this being recorded so I can view it afterwards?
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Peter Aiken, Ph.D.
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• 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 - 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’s
Most Important Asset.
The Case for theChief Data OfficerRecasting the C-Suite to LeverageYour Most Valuable Asset
Peter Aiken andMichael Gorman
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 √ √ √ √
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Copyright 2015 by Data Blueprint
• Today, data is the most powerful, yet underutilized and poorly managed organizational asset
• Data is your – Sole – Non-depleteable – 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
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 Architecture Requirements
8
Copyright 2015 by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
9Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• 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
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Data Platform/Architecture
Data Governance Data Quality
Data Operations
Data Management Strategy
Technologies
Capabilities
Maintain fit-for-purpose data, efficiently and effectively
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Manage data coherently
Manage data assets professionally
Data architecture implementation
Data lifecycle implementation
Organizational support
DMM℠ Structure of 5 Integrated DM Practice Areas
The DAMA Guide to the Data Management Body of Knowledge
13Copyright 2015 by Data Blueprint
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
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Copyright 2015 by Data Blueprint
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
What is the CDMP?
15Copyright 2015 by Data Blueprint
• Certified Data Management Professional
• DAMA International and ICCP • Membership in a distinct
group made up of your fellow professionals
• Recognition for your specialized knowledge in a choice of 17 specialty areas
• Series of 3 exams • For more information, please
visit: – http://www.dama.org/i4a/pages/
index.cfm?pageid=3399 – http://iccp.org/certification/
designations/cdmp
Data Architecture Requirements
16Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
17Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
18
Copyright 2015 by Data Blueprint
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.
Architecture
Architectures: here, whether you like it or not
19Copyright 2015 by Data Blueprint
deviantart.com
• All organizations have architectures – Some are better
understood and documented (and therefore more useful to the organization) than others
Architecture Representation
20Copyright 2015 by Data Blueprint
• 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
Understanding
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• 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
• 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
22Copyright 2015 by Data Blueprint
• 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
Data Architecture Requirements
24Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
25Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture – A Useful Definition
26Copyright 2015 by Data Blueprint
• Common vocabulary expressing integrated requirements ensuring that data assets are stored, arranged, managed, and used in systems in support of organizational strategy [Aiken 2010]
How one inventory item proliferates data throughout an organization's data architecture
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555 Subassemblies & subcomponents
17,659 Repair parts or Consumables
System 1:18,214 Total items
75 Attributes/ item1,366,050 Total attributes
System 2 47 Total items
15+ Attributes/item720 Total attributes
System 3 16,594 Total items 73 Attributes/item
1,211,362 Total attributes
System 4 8,535 Total items
16 Attributes/item136,560 Total attributes
System 5 15,959 Total items
22 Attributes/item351,098 Total attributes
Total for the five systems show above:59,350 Items
179 Unique attributes3,065,790 values
Business Value: Agency units are carrying $1.5 billion worth of expired inventory
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• Generates unnecessary costs & negative impacts on operations, including: – Resources are focused on non-value added tasks of maintaining obsolete inventory, which
creates distractions to the agency’s main mission
• Storage – Physical/real estate needed to house items
• Handling – Includes transportation and human resources
dedicated to moving, maintaining, counting and securing outdated inventory
• Opportunity – Inventory could be returned to manufacturer or
sold to free up financial assets for more needed and critical supplies
• Systemic – Cost of inventorying information and maintaing
paper or electronic records which should be used to support mission-critical acquisitions and distribution
• Maintenance – Repairing of expired items
Data Architecture – A More Useful Definition
30Copyright 2015 by Data Blueprint
• 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?
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/
Database Architecture Focus
32Copyright 2015 by Data Blueprint
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
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• 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
Why is Data Architecture Important?
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• 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
healthcare.gov
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• 55 Contractors! • "Anyone who has written a
line of code or built a system from the ground-up cannot be surprised or even mildly concerned that Healthcare.gov did not work out of the gate," Standish Group International Chairman Jim Johnson said in a recent podcast.
• "The real news would have been if it actually did work. The very fact that most of it did work at all is a success in itself."
• Software programmed to access data using traditional data management technologies
• Data components incorporated "big data technologies"http://www.slate.com/articles/technology/bitwise/2013/10/problems_with_healthcare_gov_cronyism_bad_management_and_too_many_cooks.html
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
• 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
Lack of coherent data architecture is a hidden expense
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PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA
MONETIZINGDATA MANAGEMENT
Unlocking the Value in Your Organization’s
Most Important Asset.
Data Architecting for Business Value
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Copyright 2015 by Data Blueprint
Inspired by: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2
• 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
Levels of Abstraction, Completeness and Utility
47Copyright 2015 by Data Blueprint
• 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
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
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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.
Wisdom & knowledge are often used synonymously
Data
Data
Data Data
How do data structures support organizational strategy?
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• Two answers – Achieving efficiency and effectiveness goals – Providing organizational dexterity for rapid implementation
Computers
Human resources
Communication facilities
Software
Managementresponsibilities
Policies,directives,and rules
Data
What Questions Can Data Architectures Address?
55Copyright 2015 by Data Blueprint
• 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?
! ! ! !
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
Data Architecture Requirements
57Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
58Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Leverage
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Less ROT
Technologies
Process
People
• 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
Architecture Evolution
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Conceptual Logical Physical
Validated
Not UnValidated
Every change can be mapped to a transformation in this framework!
Application-Centric Development
Original articulation from Doug Bagley @ Walmart
Data/Information
Network/Infrastructure
Systems/Applications
Goals/Objectives
Strategy
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• In support of strategy, organizations develop 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: – 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
Systems/Applications
Network/Infrastructure
Data/Information
Goals/Objectives
Strategy
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• 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 supporting organizational data use
• 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 needs and compliment organizational process flows
– Maximum data/information reuse
Engineering
Architecture
Engineering/Architecting Relationship
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• 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
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!
Architectural Work Product
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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.
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 the governmental pay and personnel scenario
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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
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DSS Strategic Data Model
Taxpayer view
Client view
Governance view
Program Delivery view
Vendor view
Taxpayer viewPayments Taxpayers
SocialServicePrograms
TaxpayerBenefits
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Client viewPayments
Clients ClientBenefits
LocalWellfareAgencies
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Governance viewPayments
SocialServicePrograms
GovernmentalResources
Governance Governments
State Boardof SocialServices
PolicyApproval
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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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Data Architecture Requirements
77Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
78Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Challenge
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Package Implementation Example • "Green screen" legacy system to be replaced with Windows Icons
Mice Pointers (WIMP) interface; and • Major changes to operational processes
– 1 screen to 23 screens
• Management didn't think workforce could adjust to simultaneous changes – Question: "How big a change will it be to replace all instances of person_identifier
with social_security_number?"
• Answer: – (from "big" consultants) "Not a very big change." ($5 million budget)
Home Page
Business Process Name
Business Process Component
Business Process Component Step
PeopleSoft Process Metadata
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Home Page Name
(relates to one or more)
Business Process Name
(relates to one or more)
Business Process Component Name
(relates to one or more)
Business Process Component Step Name
Home Page Name Business Process Name Business Process Component Name Business Process Component Step Name
Peoplesoft Metadata Structureprocesses(39)
homepages(7)
menugroups(8)
components(180)
stepnames(822)
menunames(86)
panels(1421)
menuitems(1149)
menubars(31)
fields(7073)
records(2706)
parents(264)
reports(347)
children(647)
(41) (8)
(182)
(847)
(949)
(86)
(281)
(1259)(1916)
(5873)(264)
(647)(708)(647)
(25906)
(347)
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Peop
leso
ft M
etad
ata
Stru
ctur
e
Quantity
System Component
Time to make change
Labor Hours
1,400 Panels 15 minutes 350
1,500 Tables 15 minutes 375
984Business process component steps
15 minutes 246
Total 971
X $200/hour $194,200
X 5 upgrades $1,000,000
Business Value - Better Decisions
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Data Architecture Requirements
84Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
85Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
A National Cancer Institute
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• This cancer center is a leader in shaping the fight against cancer
• Over 500 researchers and staff tend to over 12,000 patients annually
• This requires robust information management and analytical services
• The problem: It takes 1 month to run a report on an incident, i.e. a patient’s hospital visit that shows all touch points
Other Departments
SQLSQLSAS
Cancer Registry
Claims Database
File Export
Physician Invoices
Patient (Hospital)
Patient (Physician)
Patient (Registry)
Billing Data (Hospital)
Billing Data (Physician)
Diagnoses (Hospital)
Diagnoses (Physician)
Diagnoses (Registry)
Physicians (Hospital)
Physicians (Physician)
Access
SQL
SQL
SAS
SQL
Excel
Excel
Hospital Claims
Text Files FTP FTP
Text Files
FTP or Email
WordWordWord
Current State Assessment
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Other Departments
SSIS
Cancer Registry
Hospital Claims
Staging
SSIS
Physician Invoices
Patient Demographics
Billing Data (Hospital)
Billing Data (Physician)
Diagnoses (Hospital)
Diagnoses (Physician)
Diagnoses (Registry)
Physicians (Hospital)
Physicians (Physician)
SSIS SSIS Consolidated/ Sandbox
SSISSSAS
Patient (Consolidated)
RPT
Physicians (Consolidated)
Diagnoses (Consolidated)
SSRS
SharePoint
Excel
One-off reports
Reusable reports
Conceptual Target Architecture
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0
25
50
75
100
Current Improved
Manipulation AnalysisReversing The Measures
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• Currently: – Analysts spend 80% of their time manipulating data and 20% of their time
analyzing data – Hidden productivity bottlenecks
• After rearchitecting: – Analysts spend less time manipulating data and more of their time analyzing data – Significant improvements in knowledge worker productivity
A 20% improvement results in a doubling of productivity!
Results: It is not always about money
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• Solution: – Integrate multiple databases into
one to create holistic view of data
– Automation of manual process
• Results: – Data is passed safely and
effectively – Eliminate inconsistencies,
redundancies, and corruption – Ability to cross-analyze – Significantly reduced turnaround
time for matching patients with potential donor -> increased potential to make life-saving connection in a manner that is faster, safer and more reliable
– Increased safe matches from 3 out of 10 to 6 out of 10
Data Architecture Requirements
91Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
92Copyright
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• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Improving Data Quality during System Migration
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• Challenge – Millions of NSN/SKUs
maintained in a catalog – Key and other data stored in
clear text/comment fields – Original suggestion was manual
approach to text extraction – Left the data structuring problem unsolved
• Solution – Proprietary, improvable text extraction process – Converted non-tabular data into tabular data – Saved a minimum of $5 million
– Literally person centuries of work
Unmatched Items Ignorable Items Items Matched
Week # (% Total) (% Total) (% Total)
1 31.47% 1.34% N/A
2 21.22% 6.97% N/A
3 20.66% 7.49% N/A
4 32.48% 11.99% 55.53%
… … … …
14 9.02% 22.62% 68.36%
15 9.06% 22.62% 68.33%
16 9.53% 22.62% 67.85%
17 9.5% 22.62% 67.88%
18 7.46% 22.62% 69.92%
Copyright 2014 by Data Blueprint
Architecture Derived: Diminishing Returns Determination
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Time needed to review all NSNs once over the life of the project:NSNs 2,000,000Average time to review & cleanse (in minutes) 5Total Time (in minutes) 10,000,000
Time available per resource over a one year period of time:Work weeks in a year 48Work days in a week 5Work hours in a day 7.5Work minutes in a day 450Total Work minutes/year 108,000
Person years required to cleanse each NSN once prior to migration:Minutes needed 10,000,000Minutes available person/year 108,000Total Person-Years 92.6
Resource Cost to cleanse NSN's prior to migration:Avg Salary for SME year (not including overhead) $60,000.00Projected Years Required to Cleanse/Total DLA Person Year Saved
93Total Cost to Cleanse/Total DLA Savings to Cleanse NSN's: $5.5 million
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Quantitative Benefits
Data Architecture Requirements
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• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• Take Aways, References & Q&A
Data Architecture Requirements
97Copyright
2015by Data Blueprint
• Context: Data Management/DAMA/DM BoK/CDMP?
• What is Data/Information Architecture?
• Why is Data/Information Architecture Important?
• Data Engineering/Leverage
• Example: Software Package Implementation
• Example: Donation Center Processing
• Example: Text Mining/Analytics
• 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
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• 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
Upcoming Events
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EDW 2015
Developing Data Strategy and Roadmap March 29, 2015 @ 5:00 PM ET
Addressing Data Challenges with the (DMM) Data Management Maturity March 30, 2015 @ 2:00 PM ET/11:00 AM PT
April Webinar: Data Governance Strategies April 14, 2015 @ 2:00 PM ET/11:00 AM PT
Sign up here: • www.datablueprint.com/webinar-schedule • www.Dataversity.net Brought to you by:
PETER AIKEN WITH JUANITA BILLINGSFOREWORD BY JOHN BOTTEGA
MONETIZINGDATA MANAGEMENT
Unlocking the Value in Your Organization’s
Most Important Asset.