Data-Ed Online: Building A Solid Foundation-Data/Information Architecture

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

EDUCATIONDATA SLIDE2/14/2012

© Copyright this and previous years by Data Blueprint - all rights reserved!

Welcome!

Date: February 14, 2012Time: 2:00 PM ETPresenter: Dr. Peter Aiken

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Building a Solid Foundation: Data/Information Architecture

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Meet Your Presenter: Dr. Peter Aiken

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• Internationally recognized thought-leader in the data management field with more than 30 years of experience

• Recipient of the 2010 International Stevens Award

• Founding Director of Data Blueprint (http://datablueprint.com)

• Associate Professor of Information Systems at Virginia Commonwealth University (http://vcu.edu)

• President of DAMA International (http://dama.org)

• DoD Computer Scientist, Reverse Engineering Program Manager/Office of the Chief Information Officer

• Visiting Scientist, Software Engineering Institute/Carnegie Mellon University

• 7 books and dozens of articles• Experienced w/ 500+ data management practices in 20 countries

2/14/2012DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION

Building a Solid Foundation:

Data/Information Architecture

Dr. Peter Aiken: Building a Solid Foundation – Data/Information

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Building a Solid Foundation: Data/Information Architecture

All organizations have data architectures. The question is: How effectively do they use them? This presentation provides a clear and concise understanding of what is meant by the term data architecture and the requirement that data and information architectures must be simultaneously managed. More importantly, organizations must understand what it means to use data architecture to support the implementation of organizational strategy. Participants will understand the requirements for an iterative, incremental approach to data architecture reengineering, the complimentary role of the Zachman Framework, and the ability to articulate the business value of data architecture projects and components.

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Outline1. Data Management Overview2. What is Data/Information Architecture?3. Why is Data/Information Architecture

Important?4. Data/Information Architecture

Frameworks5. Data/Information Architecture Building

Blocks6. Guiding Principles & Best Practices7. Considerations for Improving Data

Architecture Utility within your Organization

8. Take Aways, References & Q&A

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The DAMA Guide to the Data Management Body of Knowledge

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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

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The DAMA Guide to the Data Management Body of Knowledge

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Environmental Elements

Amazon:http://www.amazon.com/DAMA-Guide-Management-Knowledge-DAMA-DMBOK/dp/0977140083Or enter the terms "dama dm bok" at the Amazon search engine

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What is the 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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Data Management

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Data Management

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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

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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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Niccolò Machiavelli (1469-1527)

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He who doesn’t lay his foundations before hand, may by great abilities do so afterward, although with great trouble to the architect and danger to the building.

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Polling Question #1 Most organizations do not formally manage any type of

architectures. I have surveyed 500 different organizations around the world and found that not all of them have architectures in place. What do you think is the percentage of organizations worldwide with data architectures?

a) 80%b) 60%c) 40%d) Less than 10%

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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

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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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Information Architectures

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•… are plans, guiding the transformation of strategic organizational information needs into specific information systems development projects

– Source: Internet

• "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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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

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Vocabulary is Important-Tank, Tanks, Tankers, Tanked

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Architecture Examples: Good

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Architecture Examples: Bad

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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

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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Polling Question #2 The average organization contains information about

customers in more than one place. What do you think is the average number of places internally in which organizations keep customer information?

a) 2b) 9c) 17d) 20

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Who is Joan Smith?

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Data/Information Architectures Must be Managed Together

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1. Each FACT combines with one or more MEANINGS. – Each specific FACT and MEANING combination is referred to as a DATUM.

2. An INFORMATION is one or more DATA that are returned in response to a specific REQUEST

3. INTELLIGENCE is INFORMATION associated with its USES.– INFORMATION REUSE is enabled when one FACT is combined with more than one MEANING.

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Data Architecture Frameworks

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• TOGAF– The open group architectural framework

• ANSI/IEEE 1471-2000 Standard– Defines specific design artifacts

• FEA– Federal Enterprise Architecture/OMB

• MODAF– UK Ministry of Defence

• AGATE– France DGA Architecture Framework

• Industry Models– IBM/Teradata/Financial Transactions

Inc.• DODAF

– US DoD Architecture Framework• Zachman Framework

• A system of ideas for guiding analyses

• A means of organizing project data

• Data integration priorities decision making framework

• A means of assessing progress

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Names

Names

*Horizontal integration lines are shown for example purposes only and are not a complete set. Composite, integrative rela-tionships connecting every cell horizontally potentially exist.Names

Names

™

C o m p o s i t e I n t e g r a t i o n s

Alignment

Transformations

C o m p o s i t e I n t e g r a t i o n s

Alignment

Transformations

C o m p o s i t e I n t e g r a t i o n s C o m p o s i t e I n t e g r a t i o n s

Alignment

Transformations

Alignment

Transformations

A l i g n m e n t

A l i g n m e n t

Where Why

Operations

Instances

TheEnterprise

TheEnterprise

Enterprise

Perspective

Executive

Perspective

Business Mgmt

Perspective

Architect

Perspective

Engineer

Perspective

Technician

Perspective

Scope

Contexts

Business

Concepts

System

Logic

Technology

Physics

Tool

Components

e.g. e.g. e.g. e.g. e.g. e.g.



e.g. e.g. e.g. e.g. e.g. e.g.e.g.: primitive e.g.: composite model:

model:

Forecast Sales

Plan Production

Sell Products

Take Orders

Train Employees

Assign Territories

Develop Markets

Maintain Facilities

Repair Products

Record Transctns

Material Supply Ntwk

Product Dist. Ntwk

Voice Comm. Ntwk

Data Comm. Ntwk

Manu. Process Ntwk

Parts Dist. Ntwk

Personnel Dist. Ntwk

etc., etc.

General Mgmt

Product Mgmt

Engineering Design

Manu. Engineering

Accounting

Finance

Transportation

Distribution

Marketing

Sales

Product Cycle

Market Cycle

Planning Cycle

Order Cycle

Employee Cycle

Maint. Cycle

Production Cycle

Sales Cycle

Economic Cycle

Accounting Cycle

Products

Product Types

Parts Bins

Customers

Territories

Orders

Employees

Vehicles

Accounts

New Markets

Revenue Growth

Expns Reduction

Cust Convenience

Customer Satis.

Regulatory Comp.

New Capital

Social Contribution

Increased Yield

Increased Qualitye.g. e.g. e.g. e.g. e.g. e.g.

Process

Instantiations

Distribution

Instantiations

Responsibility

Instantiations

Timing

Instantiations

Inventory

Instantiations

Motivation

Instantiations

List: Timing Types

Business IntervalBusiness Moment

List: Responsibility Types

Business RoleBusiness Work Product

List: Distribution Types

Business LocationBusiness Connection

List: Process Types

Business TransformBusiness Input/Output

System TransformSystem Input /Output

System LocationSystem Connection

System RoleSystem Work Product

System IntervalSystem Moment

Technology TransformTechnology Input /Output

Technology LocationTechnology Connection

Technology RoleTechnology Work Product

Technology IntervalTechnology Moment

Tool TransformTool Input /Output

Tool LocationTool Connection

Tool RoleTool Work Product

Tool IntervalTool Moment

List: Inventory Types

Business EntityBusiness Relationship

System EntitySystem Relationship

Technology EntityTechnology Relationship

Tool EntityTool Relationship

List: Motivation Types

Business EndBusiness Means

System EndSystem Means

Technology EndTechnology Means

Tool EndTool Means

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Data Architectures are Developed in Response to Organizational Needs

Organizational Needs

become instantiated and integrated into an Data/Information

Architecture

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Data Architecture Management Building Blocks

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√√ √ √√ √ √


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Data Architecture Management Overview

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Data Architecture Mgmt Goals and Principles

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1) To plan with vision and foresight to provide high quality data

2) To identify and define common data requirements

3) To design and implement structures and plans to meet the current and long-term data requirements of the enterprise


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Polling Question #3

What percentage of your data handles most of your information needs?

a) 80%b) 50%c) 20%d) 5%

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Data Architecture Mgmt Activities1) Understand enterprise information needs

2) Develop and maintain the enterprise data model

3) Analyze and align with other business models

4) Define and maintain

– Data technology architecture

– Data integration architecture

– Data Warehouse/BI architecture

– Enterprise taxonomies and namespaces

– Metadata architecture

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Data Architecture Mgmt Primary Deliverables• Enterprise Data Model

• Information Value Chain Analysis

• Data Technology Architecture

• Data Integration/MDM Architecture

• DW/BI Architecture

• Metadata Architecture

• Enterprise Taxonomies and Namespace

• Document Management Architecture

• Metadata

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Polling Question #4

Who is responsible for the data?

a) Everyoneb) CIOc) Data Producersd) Data Stewards

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Data Architecture Mgmt Roles and ResponsibilitiesManagers and Executives

Consumers• Data Stewards• Data Architects• Data Analysts• Database Administrators• Software Developers• Project Managers• Data Producers• Knowledge Workers

Suppliers• Executives • Data Stewards• Data Producers• Information Consumers

Participants• Data Stewards• SMEs• Data Architects• Data Analysts & Modelers • Other Enterprise Architects• DM Executives & Managers• CIO & other Executives• Database Administrators• Data Model Administrators

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Data Architecture Mgmt Technology• Data Modeling/CASE Tools

• Model Management Tool

• Metadata Repository

• XML Processors/Servers

• Data Discovery/Profiling Tools

• Office Productivity/Collaboration Tools

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Top 3 Things a Data Architecture Tool Needs to have in 20121. True business glossary

– Capturing the language of the business independent of data structure, independent of physical form, is the ideal way to properly identify, classify, and manage disparate information sources

2. Business process and other business models– These models define the context for information that we

manage. By aligning all information concepts with all uses of that same concept across all business units and all business use cases, we can ensure a consistent definition of that information regardless of which subset of the attributes we implement in a given application or technology

3. Web-based collaboration– This one is really about sharing the metadata with folks

that are not using a modeling tool but have a say in this knowledge set.

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Source: “Top 3 Things a Data Architecture Tool Needs to Have in 2012” by David Dichmann; http://blogs.sybase.com/dichmann/2012/01/top-3-things-a-data-architecture-tool-needs-to-have-in-2012/

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Guiding Principles & Best Practices1. Data architecture is an integrated set of

specification artifacts (master blueprints) used to define data requirements, guide data integration, control data assets, and align data investments with business strategy

2. Enterprise data architecture is part of the overall enterprise architecture, along with process architecture, business architecture, systems architecture, and technology architecture

3. Enterprise data architecture includes three major categories of specifications:

(1) The enterprise data model(2) Information value chain analysis(3) Data delivery architecture

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Guiding Principles & Best Practices, cont’d4. Enterprise data architecture is

about more than just data. It helps establish the semantics of an enterprise, using a common business vocabulary

5. An enterprise data model is an integrated subject-oriented data model defining the essential data used across an entire organization. Build an enterprise data model in layers: – Subject area overview– Conceptual views of entities and relationships for each subject area– More detailed, partially attributed views of these same subject areas

6. Information value chain analysis defines the critical relationships between data, processes, roles and organizations, and other enterprise elements

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7. Data delivery architecture defines the master blueprint for how data flows across databases and applications. This ensures data quality and integrity to support both transactional business processes and business intelligence reporting and analysis

8. Architectural frameworks like TOGAF and The Zachman Framework help organize collective thinking about architecture. This allows different people with different objectives and perspectives to work together to meet common interests.

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Guiding Principles & Best Practices, cont’d


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Data Architecture is non-trivial

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• The successful development of a organizational data architecture requires a degree of information system development:– More often spoken about

than sought after, and – More often sought after

than achieved. • Strategic planning

without the benefit of a data architecture is just a ritual rain dance.

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Largely Ineffective DM Investments

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• Approximately, 10% percent of organizations achieve parity and (potential positive returns) on their DM investments.

• Only 30% of DM investments achieve tangible returns at all.

• Seventy percent of organizations have very small or no tangible return on their DM investments.

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Data Architecture 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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References

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Websites

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References, cont’d

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References, cont’d

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Questions?

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It’s your turn! Use the chat feature to submit your questions to Peter now.

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Upcoming Events

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March Webinar:Practical Data ModelingMarch 13, 2012 @ 2:00 PM ET/11:00 AM PT

April Webinar:Data Operations Management: Turning your Challenges Into SuccessApril 10, 2012 @ 2:00 PM ET/11:00 AM PT

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

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Comparative Assessment Results

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Data Program Coordination

Organizational Data Integration

Data Stewardship

Data Development

Data Support Operations

0 1 2 3 4 5

Nokia Industry Competition All Respondents

Challenge

Challenge

Challenge

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Data-Centric Development Flow• 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

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Strategy

Goals/Objectives

Data/Information

Network/Infrastructure

Systems/Applications

Original articulation from Doug Bagley @ Walmart

Data-Ed Online: Building A Solid Foundation-Data/Information Architecture

Technology

Transcript of Data-Ed Online: Building A Solid Foundation-Data/Information Architecture