DataEd Webinar: Unlocking Business Value Through Data Modeling and Data Architecture (Part 2 of 2)

Welcome: Data Modeling & Data Architecting for Business Value pt. 2

Date: February 12, 2013Time: 2:00 PM ETPresented by: Peter Aiken, PhD

When asked why they are architec0ng data, many in the prac0ce answer: "Because that is what must be done." However, a be>er approach to this ques0on is to speak in terms that are understood in the execu0ve suite – business results! All of our organiza0ons are faced with various organiza0onal challenges that require analysis. Building new systems is just one example. This webinar describes the use of data architec0ng as a basic analysis method (one of many that good analysts should keep in their “toolbox"). I will demonstrate various uses of data architec0ng to inform, clarify, understand, and resolve aspects of a variety of business problems. As opposed to showing how to architect data, I will show how to use data architec0ng 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 u0lity of this analysis method in the eyes of the business.

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Meet Your Presenter: Dr. Peter Aiken

• Internationally recognized thought-leader in the data management field - 30 years of experience– Recipient of multiple international

awards– Founder, Data Blueprint

(http://datablueprint.com)• 7 books and dozens of articles• Experienced w/ 500+ data

management practices in 20 countries

• Multi-year immersions with organizations as diverse as the US DoD, Deutsche Bank, Nokia, Wells Fargo, the Commonwealth of Virginia and Walmart

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Upcoming Special Event

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Leading the Data Asset Management Team: CDO or Top Data Job?Join Peter Aiken, Ph.D. and Micheline Casey forthis interactive discussion on the role of Chief Data Officer (CDO) or Top Data Job (TDJ).

Attendees will be presented with big ideas and alternative ways not only for how to think about the role of CDO/TDJ but also how to plan and establish a CDO/TDJ position at their organizations. This webinar is intended to provide viewers with deep insights from two data management thought leaders.

March 19, 2013 @ 2:00 PM ET/11:00 AM PT

Brought to you by:

2/12/2013DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION

Peter Aiken: Data Modeling & Data Architecting for Business Value pt. 1

Data Modeling & Data Architecting

for Business Value pt. 2

TITLE Agenda1. What is Data Management/DAMA/DM

BoK/CDMP?2. Brief review of Part 13. What is Data/Information

Architecture?4. Why is Data/Information Architecture

Important?5. Data Engineering/Leverage6. Example: Software Package

Implementation7. Example: Donation Center

Processing8. Example: Text Mining/Analytics9. Take Aways, References & Q&A

PRODUCED BY DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060

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EDUCATION

Tweeting now: #dataed

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Five Integrated DM Practices

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Five Integrated DM Practices

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Manage data coherently.

Share data across boundaries.

Assign responsibilities for data.Engineer data delivery systems.

Maintain data availability.

Data Program Coordination

Organizational Data Integration

Data Stewardship Data Development

Data Support Operations

#dataed


• 5 Data Management Practices Areas / Data Management Basics

• Are necessary but insufficient prerequisites to organizational data leveraging applications (that is Self Actualizing Data or Advanced Data Practices)

Data Management Practices Hierarchy (after Maslow)

Basic Data Management Practices– Data Program Management– Organizational Data Integration– Data Stewardship– Data Development– Data Support Operations

http://3.bp.blogspot.com/-ptl-9mAieuQ/T-idBt1YFmI/AAAAAAAABgw/Ib-nVkMmMEQ/s1600/maslows_hierarchy_of_needs.png

Advanced Data Practices• Cloud• MDM• Mining• Analytics• Warehousing• Big

• 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 (more at dama.org)

– Organized around several environmental elements

• CDMP– 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

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DAMA DM BoK & CDMP

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Data Management Func-ons










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Data Modeling for Business Value (REVIEW)• 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

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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










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Data Architecture Management

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from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International

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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

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Levels of Abstraction, Completeness and Utility

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Architecture

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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 Representation

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• 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

• A specific definition – 'Understanding an architecture'

– Documented and articulated as a digital blueprint illustrating the commonalities and interconnections among the architectural components

– Ideally the understanding is shared by systems and humans


Understanding

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Typically Managed Architectures

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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

• 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 Architectures

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What do you use an information architecture for?

23 Illustration by murdock23 @ http://designfestival.com/information-architecture-as-part-of-the-web-design-process/

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Data Architecture – Better Definition

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*Source: Aiken 2010

• Common vocabulary expressing integrated requirements ensuring that data assets are stored, arranged, managed, and used in systems in support of organizational strategy* • All organizations have

information architectures• Some are better understood and

documented (and therefore more useful) than others


Vocabulary is Important-Tank, Tanks, Tankers, Tanked

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How one inventory item proliferates data throughout the chain

555 Subassemblies & subcomponents

17,659 Repair parts or Consumables

System 1:18,214 Total items75 Attributes/ item

1,366,050 Total attributes

System 247 Total items

15+ Attributes/item720 Total attributes

System 316,594 Total items73 Attributes/item1,211,362 Total

System 48,535 Total items16 Attributes/item

136,560 Total attributes

System 515,959 Total items22 Attributes/item

351,098 Total attributes

Total for the five systems show above:59,350 Items

179 Unique attributes3,065,790 values

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Business Value

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• Agency units are carrying $1.5 billion worth of expired inventory – Generates unnecessary costs and negative

impacts on operations, including:• Mission Readiness

• Storage

• Handling

• Opportunity

• Systemic

• Maintenance










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Why Architectural Models?

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• 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!

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Architecture Examples: Bad

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Poor Quality Foundation


What they think they are purchasing!

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Polling Question #1

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Do you believe that your organization has a solid data architectural foundation on which to build their IT projects?

a) Yesb) No

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Polling Question #2

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Do you believe that your organization is capable of building a solid data architectural foundation on which to build their IT projects?

a) Yesb) No

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Context Diagrams Show System Boundaries

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Too Much Detail

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Web Developers Understand IAhttp://www.jeffkerndesign.com

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Web Developers Understand IAhttp://www.jeffkerndesign.com

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#dataed

Database Architecture Focus

Program F

Program E

Program DProgram G

Program H

Program I

Applicationdomain 2Application

domain 3

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#dataed

Data Architecture Focus has poten-ally greater Business Value


Data Data

Data

Information

Fact Meaning

Request

A Model Specifying Relationships Among Important Terms

[Built on definition by Dan Appleton 1983]

Intelligence

Use

1. Each FACT combines with one or more MEANINGS. 2. Each specific FACT and MEANING combination is referred to as a DATUM. 3. An INFORMATION is one or more DATA that are returned in response to a

specific REQUEST 4. INFORMATION REUSE is enabled when one FACT is combined with more than

one MEANING.5. INTELLIGENCE is INFORMATION associated with its USES.

Wisdom & knowledge are often used synonymously

Data

Data

Data Data

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How are data structures expressed as architectures?

• Details are organized into larger components

• Larger components are organized into models

• Models are organized into architectures

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A B

C D

A B

? D

A

D

C

B


Architectures Comprise a Network of Networks

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How are Data Models Expressed as Architectures?• 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?

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#dataed


How do data structures support organizational strategy?

• 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?

– In all likelihood your organization is spending between 20-40% of its IT budget compensating for poor data structure integration

– They cannot be helpful as long as their structure is unknown

• Two answers– Achieving efficiency and

effectiveness goals– Providing organizational dexterity for

rapid implementation45

Computers

Human resources

Communication facilities

Software

Managementresponsibilities

Policies,directives,and rules

Data

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What Questions Can Architectures Address?

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• How and why do the 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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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

#dataed

Data Architectures produce and are made up of information models that are developed in response to organizational needs

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Polling Question #3

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• Our organization is using enterprise data modeling to achieve integration– a) Yes– b) No

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Polling Question #4

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• Our organization should be using enterprise data modeling to achieve integration– Yes– No










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Data Leverage

• Data Leverage permits organizations to better manage their most powerful yet under-utilized, poorly managed, durable asset - data– within the system and – with organizational data exchange partners.

• Leverage is obtained by implementation of data-centric technologies, processes, and human skill sets.

• Leverage is increased by elimination of data ROT (redundant, obsolete, or trivial)

• Treating data more asset-like simultaneously 1. lowers organizational IT costs and 2. increases organizational knowledge worker productivity

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Less ROT

Technologies

Process

People

Architecture Evolution


Conceptual Logical Physical

Validated

Not Validated

Strategy

Goals/Objectives

Systems/Applications

Network/Infrastructure

Data/Information

- IA-2 datablueprint.com 2/14/2013 © Copyright this and previous years by Data Blueprint - all rights reserved!

• In support of strategy, the organization develops specific goals/objectives

• The goals/objectives drive the development of specific systems/applications

• Development of systems/applications leads to network/infrastructure requirements

• Data/information are typically considered after the systems/applications and network/infrastructure have been articulated

• Problems with this approach:– This ensures that data is formed

around the application and not the organizational information requirements

– Process are narrowly formed around applications

– Very little data reuse is possible

Application-Centric Development

Original articulation from Doug Bagley @ Walmart

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Strategy

Goals/Objectives

Data/Information

Network/Infrastructure

Systems/Applications


• In support of strategy, the organization develops specific goals/objectives

• The goals/objectives drive the development of specific data/information assets with an eye to organization-wide usage

• Network/infrastructure components are developed to support organization-wide use of data

• Development of systems/applications is derived from the data/network architecture

• Advantages of this approach:– Data/information assets are

developed from an organization-wide perspective

– Systems support organizational data/information needs and compliment organizational process flows

– Data/information reuse is maximized

Data-Centric Development Flow

Original articulation from Doug Bagley @ Walmart

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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


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.

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Engineering Standards


Hierarchical System Functional Decomposition

SystemProcess

Process2

Process1

Process3

Subprocess1.1

Subprocess1.2

Subprocess1.3

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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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Polling Question #5• My organization uses the following

approaches to achieve organizational integration A)Organizational data modelingB)Creates point to point interconnectivityC)Distributed systems implementationD)My organization is not

following a programmatic approach to integration

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EDUCATION


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Challenge

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."63


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


Business Process Component Name


Business Process Component Step Name


Example Query Outputs65


processes(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)

Peoplesoft Metadata Structure

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• Home Page Name• Business Process Name• Business Process Component Name• Business Process Component Step Name


Business Value - Better Decisions

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Quantity System Component

Time to make change

Labor Hours

1,400 Panels 15 minutes 3501,500 Tables 15 minutes 375984 Business

process component steps

15 minutes 246

Total 971

X $200/hour $194,200

X 5 upgrades $1,000,000










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• This Virginia 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


A National Cancer Institute

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Other Departments

SQLSQL

Current State Assessment

7

SAS

Cancer Registry

ClaimsDatabase

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 orEmail

WordWordWord


Other Departments

Conceptual Target Architecture

10

SSIS

Cancer Registry

Hospital Claims

Staging

SSIS

Physician Invoices

PatientDemographics

Billing Data(Hospital)

Billing Data(Physician)

Diagnoses(Hospital)

Diagnoses(Physician)

Diagnoses(Registry)

Physicians(Hospital)

Physicians(Physician)

SSIS

SSIS

Consolidated/Sandbox

SSIS SSA

S

Patient(Consolidated)

RPT

Physicians(Consolidated)

Diagnoses(Consolidated)

SSRS

SharePoint

Excel

Email

One-off reports

Reusable reports

0

25

50

75

100

Current Improved


Business Value - Improving Productivity

• Currently:– Analysts spend 80% of their time manipulating data and 20% of their time

analyzing data– Used to take 1 month to produce key reports

• After rearchitecting:– Analysts spend 20% of their time manipulating data and 80% of their time

analyzing data– Two days to produce key reports

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Manipulation Analysis


Rough Estimates on Improvements to Modeling Analyses

• Modelers/analysts are expensive knowledge workers

• 80% of their time is spent searching for information

• 20% of their time is spent acting on the retrieved information

• An improvement of 25% (from 80% search to 60%) could yield a doubling of modeler/analyst productivity - a 10 to one payoff

• A 75% improvement (from 80% search to 20%) could yield a 5 X improvement ...

• ... and a similar multiplier implying the opportunity for 10X (OOM) improvements in systems development time

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0%

20%

40%

60%

80%

100%

80% 60% 40% 20%Searching Analysis

12

3










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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

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USS Midway & Pancakes


What is this?

• It is tall• It has a clutch• It was built in 1942• It is still in regular use!


Text Mining/Analytics Example

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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/A2 21.22% 6.97% N/A3 20.66% 7.49% N/A4 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 9.50% 22.62% 67.88%18 7.46% 22.62% 69.92%


The Business Value of Diminishing Returns

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Time needed to review all NSNs once over the life of the project: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: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: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: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 - datablueprint.com 2/14/2013 © Copyright this and previous years by Data Blueprint - all rights reserved!

Business Value - Quantitative Benefits

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EDUCATION


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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 (or strategies)– 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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Upcoming Events

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March Webinar:Building the Case for the Top Data JobMarch 12, 2013 @ 2:00 PM ET/11:00 AM PT

April Webinar:Unlock Business Value through Data GovernanceApril 9, 2013 @ 2:00 PM ET/11:00 AM PT

Sign up here:• www.datablueprint.com/webinar-schedule • www.Dataversity.net

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Upcoming Special Event

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Leading the Data Asset Management Team: CDO or Top Data Job?Join Peter Aiken, Ph.D. and Micheline Casey forthis interactive discussion on the role of Chief Data Officer (CDO) or Top Data Job (TDJ).

Attendees will be presented with big ideas and alternative ways not only for how to think about the role of CDO/TDJ but also how to plan and establish a CDO/TDJ position at their organizations. This webinar is intended to provide viewers with deep insights from two data management thought leaders.

March 19, 2013 @ 2:00 PM ET/11:00 AM PT

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DataEd Webinar: Unlocking Business Value Through Data Modeling and Data Architecture (Part 2 of 2)

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Transcript of DataEd Webinar: Unlocking Business Value Through Data Modeling and Data Architecture (Part 2 of 2)