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EDUCATION
Welcome!
Date: March 13, 2012Time: 2:00 PM ETPresenter: Dr. Peter AikenTwitter: #dataed
1
Practical Data Modeling
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EDUCATION
Meet Your Presenter: Dr. Peter Aiken
2
• 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://www.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
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2/14/2012DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060 EDUCATION
Practical Data Modeling
Dr. Peter Aiken: Practical Data Modeling
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EDUCATION
Practical Data ModelingThis presentation provides you with an understanding of the data modeling and data development components of data management. Participants will understand how the analysis, design, implementation, deployment, and maintenance of data solutions should be approached in order to maximize the full value of the enterprise data resources and activities. Architecting in quality is imperative at this level and complements a subset of project activities within the system development lifecycle (SDLC) focused on defining data requirements, designing data solution components, and implementing these components. Participants will understand the difficulties organizations experience when interacting with data development efforts and how to best incorporate these efforts into specific data projects.
4
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
5
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EDUCATION
The DAMA Guide to the Data Management Body of Knowledge
6
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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EDUCATION
The DAMA Guide to the Data Management Body of Knowledge
7
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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EDUCATION
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
8
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EDUCATION
Data Management
9
#dataed
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EDUCATION
Data Management
10
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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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
11
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EDUCATION
Summary: Data Development
12
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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EDUCATION
Data Development Definition
13
• Analysis, design, implementation, deployment, and maintenance of data solutions to maximize the value of the data resources to the enterprise
• Subset of SDLC – defining and implementing data solution components– Primarily databases and data structures but includes screens,
reports, interfaces – Now is recognized to include data virtualization, portals, XML
delivery, etc.• Example:
data definition language(DDL)
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EDUCATION
Data Modeling Definition
14
• Modeling = Analysis and design method used to– Define and analyze data requirements– Design data structures that support these
requirements
• Model = set of data specifications and related diagrams that reflect requirements and designs– Representation of something in our
environment– Employs standardized text/symbols to
represent data attributes (grouped into data elements) and the relationships among them
– Integrated collection of specifications and related diagrams that represent data requirements and design
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
15
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EDUCATION
Data Modeling• Modeling = complex process involving
interaction between people and with technology that don’t compromise the integrity or security of the data
• Good data models accurately express and effectively communicate data requirements and quality solution design
• Modeling approach (guided by 2 formulas):– Purpose + audience = deliverables– Deliverables + resources + time = approach
16
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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Data Models Facilitate
2. Communicationo Data model is a bridge to understanding data between people
with different levels and types of experience. o Helps understand business area, existing application, or impact
of modifying an existing structureo May also facilitate training new business and/or technical staff
3. Scopeo Data model can help explain the data concept and scope of
purchased application packages
17
1. Formalizationo Data model documents a single,
precise definition of data requirements and data-related business rules
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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EDUCATION
Data Models: Same But Different• Models that include the same data may differ by• Scope: Express a perspective about data in
terms of:– Function: business view vs. application view– Realm: process, department, division, enterprise or
industry– Time: current state, short-term future, long-term future
• Focus:– Conceptual view: Basic and critical concepts– Logical view: Detailed but independent of context– Physical view: Optimized for a specific technology/use
18
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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Data Model Uses
19
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
• Use data models to specify the data required for information needs
• Data flows through business processes packaged in information products
• Data contained in these products must meet business requirements
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EDUCATION
Data Models Used to Support Strategy
20
• Flexible, adaptable data structures• Cleaner, less complex code• Ensure strategy effectiveness measurement• Build in future capabilities• Form/assess merger and acquisitions strategies
Adapted from Introduction to Data Modeling by Clive Finkelstein in Information Engineering Strategic Systems Development 1992
Employee Employee
Sales Manager Manager
Staff Line
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EDUCATION
Data Models and Business Rules
21
Person Job Class
Employee Posi:on
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.
Moo
nligh:
ng
Job Sharing
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data
management components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
22
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EDUCATION
Data Management Functions
23
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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EDUCATION
Data Modeling and Design Quality Management
24
• Implement development/test database changes• Create and maintain test data• Migrate and convert data• Build and test information products• Build and test data access services• Validate information requirements• Prepare for data deployment
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
Analysis
Design
Build
Test
Maintain
#dataed
• Data modeling is used to articulate data architecture components
• Data architectures are comprised of components – usually expressed as models
• Styles of data modeling exist – this is a challenge– IE or information engineering– IDEF1X used by DoD– ORM or object role modeling– UML or unified modeling language
• Data models are useful– In stand-alone mode– As components of a larger information architecture
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Data Modeling and Data Architecture
25
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!" !" !" !"
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26
Data Architectures produce and are made up of models that are developed in response to organizational needs
Organizational Needs
become instantiated and integrated into an Data/Information
Architecture
!"#$%&'($")*+,-.&)/.012%.&."-,3
authorizes and articulates sa
tisfy
spe
cific
org
aniz
atio
nal n
eeds
#dataed
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EDUCATION
• 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 answers1. Achieving efficiency and effectiveness goals2. Providing organizational dexterity for rapid implementation
How do Data Models Support Organizational Strategy?
27
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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?
28
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
29
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The Data Model Pyramid
Source: Steve Hoberman & George McGeachie, Key Features Needed in a Data Modeling Tool; http://www.tdan.com/view-articles/15768
30
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Disposition Data Map
31
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Data Map of DISPOSITION• At least one but possibly more system USERS enter the DISPOSITION facts into the system.• An ADMISSION is associated with one and only one DISCHARGE.• An ADMISSION is associated with zero or more FACILITIES.• An ADMISSION is associated with zero or more PROVIDERS.• An ADMISSION is associated with one or more ENCOUNTERS.• An ENCOUNTER may be recorded by a system USER.• An ENCOUNTER may be associated with a PROVIDER.• An ENCOUNTER may be associated with one or more DIAGNOSES.
ADMISSION Contains information about patient admission history related to one or more inpatient episodes
DIAGNOSIS Contains the International Disease Classification (IDC) of code representation and/or description of a patient's health related to an inpatient code
DISCHARGE A table of codes describing disposition types available for an inpatient at a FACILITY
ENCOUNTER Tracking information related to inpatient episodes
FACILITY File containing a list of all facilities in regional health care system
PROVIDER Full name of a member of the FACILITY team providing services to the patient
USER Any user with access to create, read, update, and delete DISPOSITION data
32
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Attributes & Definitions
33
Entity: BED Data Asset Type: Principal Data EntityPurpose: This is a substructure within the
Room substructure of the Facility Location. It contains information about beds within rooms.
Source: Maintenance Manual for File and Table Data (Software Version 3.0, Release 3.1)
Attributes: Bed.Description Bed.Status Bed.Sex.To.Be.Assigned Bed.Reserve.ReasonAssociations: >0-+ RoomStatus: Validated
BEDBed.Id #Bed.Descrip:onBed.StatusBed.Sex.To.Be.AssignedBed.Reserve.Reason
Attributes arranged into an entity named "bed" – the attribute Bed.Id is the means used to identify a unique occurrence of bed
Attributes displayed in a manner encouraging their reuse as perhaps in a CASE-tool or metadata repository – A purpose statement describing why the organization is maintaining information about these "business things" – Sources of information about it –(A partial) List of the attributes or characteristics of the entity – Associations with other data items; this is read as ROOM contains zero or more BEDS
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ANSI-SPARK 3-Layer Schema
34
1. Conceptual - Allows independent customized user views:
– Each should be able to access the same data, but have a different customized view of the data.
2. Logical - This hides the physical storage details from users:
– Users should not have to deal with physical database storage details. They should be allowed to work with the data itself, without concern for how it is physically stored.
3. Physical - The database administrator should be able to change the database storage structures without affecting the users’ views:
– Changes to the structure of an organization's data will be required. The internal structure of the database should be unaffected by changes to the physical aspects of the storage.
For example, a changeover to a new DBMS technology. The database administrator should be able to change the conceptual or global structure of the database without affecting the users.
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Data Modeling is used throughout the Systems Development Lifecycle
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
Analysis
Design
Build
Test
Maintain#dataed
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
36
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Data Modeling & Development Building Blocks
3745
Illustration from The DAMA Guide to the Data Management Body of Knowledge p. 37 © 2009 by DAMA International#dataed
üü ü üü ü ü
üü ü üü ü ü
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Summary: Data Development
38
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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Goals and Principles
39
1. Identify and define data requirements.
2. Design data structures and other solutions to these requirements.
3. Implement and maintain solution components that meet these requirements.
4. Ensure solution conformance to data architecture and standards as appropriate.
5. Ensure the integrity, security, usability, and maintainability of structured data assets.
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
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Data Modeling/Development Activities1. Data modeling, analysis and solution
design1) Analyze information requirements2) Develop and maintain conceptual models3) Develop and maintain logical models4) Develop and maintain physical models
2. Detailed data design1) Design physical databases2) Design information products3) Design data access services4) Design data integration services
40
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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Data Modeling/Development Activities, cont’d3. Data model and design quality management
1) Develop data modeling and design standards2) Review data model and database design quality3) Manage data model versioning and integration
4. Data implementation1) Implement development/test database changes1) Create and maintain test data2) Migrate and convert data3) Build and test information products4) Build and test data access services5) Validate information requirements6) Prepare for data deployment
41
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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EDUCATION
Primary Deliverables• Data Requirements and
Business Rules• Conceptual Data Models• Logical Data Models and
Specifications• Physical Data Models and
Specifications• Meta-data (Business and
Technical)• Data Modeling and DB design
Standards• Data Model and DB Design
Reviews• Data Integration Services• Data Access Services
• Version Controlled Data Models
• Test Data• Development and Test
Databases• Information Products• Migrated and Converted Data
42
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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Primary Deliverables become Reference Material
43
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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Data Modeling/Dev. Roles & Responsibilities
44
Suppliers:• Data Stewards and SMEs• IT Steering committee• Data Governance Council• Data Architects and Analysts• Software Developers• Data Producers• Information Consumers
Participants:• Data Stewards and SMEs• Data Architects and Analysts• Database Administrators• Data Model Administrators• Software Developers• Project Managers• DM Executives and other IT Management
Consumers:• Data Producers• Knowledge Workers• Managers and Executives• Customers• Data Professionals• Other IT Professionals
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
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Data Modeling/Development Technology
45
Testing ToolsData Profiling Tools
Data Modeling ToolsOffice Productivity Tools
Model Management ToolsSoftware Development Tools
Database Management SystemsConfiguration Management Tools
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International#dataed
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
46
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Guiding Principles1. Data development activities are
an integral part of the software development lifecycle (SDLC).
2. Data modeling is an essential technique for effective data management and system design.
47
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
3. Conceptual and logical data modeling express business and application requirements, while physical data modeling represents solution design.
4. Data modeling and database design balances tradeoffs and needs.
5. Data professionals should collaborate with other project team members to design information products and data access and integration interfaces.
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Guiding Principles, cont’d6. Data modeling and database
design should follow documented standards
7. Design reviews should review all data models and designs, in order to ensure they meet business requirements and follow design standards.
48
from The DAMA Guide to the Data Management Body of Knowledge © 2009 by DAMA International
6. Data models represent valuable knowledge resources (metadata). Carefully manage and control them through library, configuration, and change management to ensure data model quality and availability.
7. DBAs and other data professionals play important roles in the construction, testing, and deployment of databases and related application systems.
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EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
49
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7 Mistakes You Can’t Afford to Make Enterprise Data Modeling
Source: Karen Lopez, InfoAdvisors; @datachick
1. Forgetting that an enterprise architecture is a living framework• Traceability is key to realizing the benefits of an
enterprise data management program: Any team member should be able to trace a business concept from the logical model to the physical model to the physical implementation of that concept
2. Keeping data models invisible• In order to deliver business value, a data
management effort must be accessible, understandable and shareable.
• Models need to be available in an easily searchable manner.
50
Source: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2
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EDUCATION
7 Mistakes You Can’t Afford to Make3. Assuming that business users can’t understand or
review models• Business users need to be able to access and digest data
models so they can make informed business decisions• It is key to give them data model viewing and reporting
capabilities• Remember: business users who see models regularly are
more likely to support the allocation of resources to future efforts
4. Thinking that data models are only about databases• Both logical and physical models support more than just
databases• Allowing team members to import/export metadata
contributes to a model-driven design environment and establishes integration of model metadata with other platforms
51
Source: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2
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EDUCATION
7 Mistakes You Can’t Afford to Make, cont’d5. Throwing models “over the wall”
• A modeler is the mediator between business requirements and physical implementations
• He/She should be involved in how requirements are captured as well as implemented
6. Forgetting about the sizzle• One of the main benefits of effective enterprise data
management is better communication• Models should be interesting and the successful data
modeler must never underestimate the value of sizzle• Presentations of models must be clear and
understandable• Adding color and diagramming objects customizes
models and allows for a more engaging and enjoyable user review process
52
Source: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2
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EDUCATION
7 Mistakes You Can’t Afford to Make, cont’d7. Thinking of them as “your” models
• Most critical mistake is treating data models as if the modeler personally owns them
• Models belong to the business and are tended to by the modelers. This means:• Share them openly• Provide access to those who want it• Keep extra printouts available• Offer training on how to read them• Make every effort to make them clear and understandable
53
Source: Karen Lopez http://www.information-management.com/newsletters/enterprise_architecture_data_model_ERP_BI-10020246-1.html?pg=2
Treating models as technical specifications that are understood only by developers and DBAs will not provide the benefits of an enterprise architecture #dataed
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PRODUCED BY
DATA BLUEPRINT 10124-C W. BROAD ST, GLEN ALLEN, VA 23060CLASSIFICATION DATE SLIDE
2/14/2012© Copyright this and previous years by Data Blueprint - all rights reserved!
EDUCATION
Outline1. Data Management Overview2. What is Data Modeling? What is Data
Development?3. Why are they important and how do they
compare?4. Where do they fit in as data management
components?5. Data Modeling/Development Frameworks6. Data/Information Architecture Building
Blocks7. Guiding Principles & Best Practices8. Improving Data Modeling and Data
Development within Your Organization: 7 Mistakes You Cannot Afford to Make
9. Take Aways, References & Q&A
54
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EDUCATION
References
55
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EDUCATION
References
56
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EDUCATION
References
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Questions?
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