SlideShare ist ein Scribd-Unternehmen logo
1 von 16
Downloaden Sie, um offline zu lesen
Creating Enterprise Standards with
CA ERwin® Data Modeling
Terry Hanks – CA Presales Consultant
Abstract


• As data volumes increase, and organizations are faced with data
  integration challenges associated with mergers and acquisitions,
  master data management, business intelligence, and/or data
  governance initiatives, the need to create consistent, reusable
  standards is more critical than ever before. Standards help increase
  efficiency and quality by promoting reuse across the organization.




  PAGE 2
Speaker Bio

• Terry Hanks is a CA Technologies Presales Consultant for the CA
  Erwin Modeling Family of products. He has worked with the
  Modeling Product line for 5 years.
• Prior to joining CA Technologies, Terry worked in the Health care IT
  industry.




  PAGE 3
Agenda

• Why Use Enterprise Data Standards
• Implementing Standards with CA ERwin Modeling
     – Leveraging Naming Standards and Domains
     – User Defined Properties (UDP’s)
     – Defining Data Type Standards
     – Using Model Templates
     – Sharing Standards using CA ERwin Model Manager
     – Reporting to Stakeholders using Crystal Reports
• Live Demo
• Q&A


 PAGE 4
Why use Enterprise Standards?

• Business decisions are based on data – bad data or design
  results in bad business decisions
• Benefits of using data standards:
    – Increased Efficiency
    – Increased Data Quality
    – Promotes Reuse and Communication across the organization.




  PAGE 5
Who uses Enterprise Standards?

• Many types of initiatives can benefit from Enterprise Standards
             Data Warehousing
             Master Data Management (MDM)
             Mergers and Acquisitions
             Data Integration
             Application Development
             Data Quality
             Data Governance




 PAGE 6
Using Naming Standards

 • What is a Naming Standard?
     – A glossary of words and abbreviations that can be used in model object
       names
 • Why use the Naming Standards Editor?
     – Develop model naming standards
     – Check model names for accuracy
     – Name model objects in models derived from other models
     – Reuse of standards across the enterprise




 PAGE 7
Using Domains

 • What is a Domain?
     – A set of values and rules assigned to a data element
          • Example: Data types, Validation rules
     – Used to quickly assign properties to columns
 • Why use Domains?
     – Speeds Design process
     – Easy to maintain
     – Use across entire model




 PAGE 8
Using User Defined Properties (UDPs)


• What is a UDP ?
   – Provides the ability to define custom model object properties
• Why use UDPs?
   – Further documentation of model objects
   – Clarification for users or viewers of models
   – Standardize usage across models
• Examples of Common UDPs
   – Data Stewards, Status, Document attachments, etc.




 PAGE 9
Using Datatype Standards


 • What is a Datatype Standards file?
     – Includes user-defined datatypes and mapping information that is needed to
       convert logical & physical datatypes.
 • Why use a Datatype Standards file?
     – Converting models from Logical to Physical
     – Converting models from one Physical DBMS to another
     – Deriving multiple models from one source
     – Introducing new data types




 PAGE 10
Using Model Templates with Standards

• What is a Model Template?
   – A starting point for new models containing reusable objects such as:
           • Domains
           • Naming standards
           • Formatting options
           • Etc.
• Why use a Model Template?
   – Provides Standardization and Reuse
   – Speeds up development/altering of models/databases




 PAGE 11
Sharing Standards Using CA ERwin Model Manager

 • What is CA ERwin Model Manager?
     – Central location for storing standards, such as:
           • Naming Standards
           • Datatype Standards
           • Model Templates
     – Collaboration for use, reuse, and audit
 • Why use CA ERwin Model Manager?
     – Reuse of core data assets
     – Efficiencies for team collaboration
     – Access to other models for sharing objects via Complete Compare




 PAGE 12
Reporting to Stakeholders


• Sharing information in customizable formats
• CA ERwin Data Modeler provides multiple reporting options
     – HTML
     – PDF
     – Text
     – RTF
     – Crystal Reports
     – OBDC queries
• In addition, these reports may be filtered by Subject Areas or
  Stored Displays


 PAGE 13
Demo


• CA ERwin Data Modeler Enterprise Standards Demo




PAGE 14
Visit www.ERwin.com




 PAGE 15
Questions?




 PAGE 16

Weitere ähnliche Inhalte

Andere mochten auch

CA ERwin Data Modeler End User Presentation
CA ERwin Data Modeler End User PresentationCA ERwin Data Modeler End User Presentation
CA ERwin Data Modeler End User PresentationCA RMDM Latam
 
Importance of data model
Importance of data modelImportance of data model
Importance of data modelyhen06
 
Ca e rwin state of the union 09082010
Ca e rwin state of the union 09082010Ca e rwin state of the union 09082010
Ca e rwin state of the union 09082010ERwin Modeling
 
All data models in dbms
All data models in dbmsAll data models in dbms
All data models in dbmsNaresh Kumar
 
Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010ERwin Modeling
 
Sybase PowerDesigner Vs Erwin
Sybase PowerDesigner Vs ErwinSybase PowerDesigner Vs Erwin
Sybase PowerDesigner Vs ErwinSybase Türkiye
 
Ernesto_Arce_ERwin_Data_Modeling
Ernesto_Arce_ERwin_Data_ModelingErnesto_Arce_ERwin_Data_Modeling
Ernesto_Arce_ERwin_Data_ModelingErnesto Arce Jr.
 
Data modeling for the business 09282010
Data modeling for the business  09282010Data modeling for the business  09282010
Data modeling for the business 09282010ERwin Modeling
 
Integrating data process a roundtrip modeling using e rwin data modeler_erwin...
Integrating data process a roundtrip modeling using e rwin data modeler_erwin...Integrating data process a roundtrip modeling using e rwin data modeler_erwin...
Integrating data process a roundtrip modeling using e rwin data modeler_erwin...ERwin Modeling
 
Using ca e rwin modeling to asure data 09162010
Using ca e rwin modeling to asure data 09162010Using ca e rwin modeling to asure data 09162010
Using ca e rwin modeling to asure data 09162010ERwin Modeling
 
Cust experience a practical guide 09152010
Cust experience a practical guide 09152010Cust experience a practical guide 09152010
Cust experience a practical guide 09152010ERwin Modeling
 
Sneak peak ca e rwin data modeler r8 preview09222010
Sneak peak ca e rwin data modeler r8 preview09222010Sneak peak ca e rwin data modeler r8 preview09222010
Sneak peak ca e rwin data modeler r8 preview09222010ERwin Modeling
 
Data Modeling PPT
Data Modeling PPTData Modeling PPT
Data Modeling PPTTrinath
 

Andere mochten auch (20)

Lançamento ERwin 08/02
Lançamento ERwin 08/02Lançamento ERwin 08/02
Lançamento ERwin 08/02
 
CA ERwin Data Modeler End User Presentation
CA ERwin Data Modeler End User PresentationCA ERwin Data Modeler End User Presentation
CA ERwin Data Modeler End User Presentation
 
rm006sn (2)
rm006sn (2)rm006sn (2)
rm006sn (2)
 
Importance of data model
Importance of data modelImportance of data model
Importance of data model
 
Ca e rwin state of the union 09082010
Ca e rwin state of the union 09082010Ca e rwin state of the union 09082010
Ca e rwin state of the union 09082010
 
All data models in dbms
All data models in dbmsAll data models in dbms
All data models in dbms
 
Nagendra Resume
Nagendra ResumeNagendra Resume
Nagendra Resume
 
Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010Mastering your data with ca e rwin dm 09082010
Mastering your data with ca e rwin dm 09082010
 
Sybase PowerDesigner Vs Erwin
Sybase PowerDesigner Vs ErwinSybase PowerDesigner Vs Erwin
Sybase PowerDesigner Vs Erwin
 
Ernesto_Arce_ERwin_Data_Modeling
Ernesto_Arce_ERwin_Data_ModelingErnesto_Arce_ERwin_Data_Modeling
Ernesto_Arce_ERwin_Data_Modeling
 
Data modeling for the business 09282010
Data modeling for the business  09282010Data modeling for the business  09282010
Data modeling for the business 09282010
 
Integrating data process a roundtrip modeling using e rwin data modeler_erwin...
Integrating data process a roundtrip modeling using e rwin data modeler_erwin...Integrating data process a roundtrip modeling using e rwin data modeler_erwin...
Integrating data process a roundtrip modeling using e rwin data modeler_erwin...
 
Using ca e rwin modeling to asure data 09162010
Using ca e rwin modeling to asure data 09162010Using ca e rwin modeling to asure data 09162010
Using ca e rwin modeling to asure data 09162010
 
Cust experience a practical guide 09152010
Cust experience a practical guide 09152010Cust experience a practical guide 09152010
Cust experience a practical guide 09152010
 
Sneak peak ca e rwin data modeler r8 preview09222010
Sneak peak ca e rwin data modeler r8 preview09222010Sneak peak ca e rwin data modeler r8 preview09222010
Sneak peak ca e rwin data modeler r8 preview09222010
 
Rm006sn ca world2010
Rm006sn ca world2010Rm006sn ca world2010
Rm006sn ca world2010
 
Different data models
Different data modelsDifferent data models
Different data models
 
Dbms models
Dbms modelsDbms models
Dbms models
 
Data models
Data modelsData models
Data models
 
Data Modeling PPT
Data Modeling PPTData Modeling PPT
Data Modeling PPT
 

Ähnlich wie Creating enterprise standards 09302010

Webinar: Initiating a Customer MDM/Data Governance Program
Webinar: Initiating a Customer MDM/Data Governance ProgramWebinar: Initiating a Customer MDM/Data Governance Program
Webinar: Initiating a Customer MDM/Data Governance ProgramDATAVERSITY
 
Akili Data Integration using PPDM
Akili Data Integration using PPDMAkili Data Integration using PPDM
Akili Data Integration using PPDMrnaramore
 
Data Management Workshop - ETOT 2016
Data Management Workshop - ETOT 2016Data Management Workshop - ETOT 2016
Data Management Workshop - ETOT 2016DataGenic Ltd
 
Microsoft master data services mds overview
Microsoft master data services mds overviewMicrosoft master data services mds overview
Microsoft master data services mds overviewEugene Zozulya
 
Marlabs Capabilities Overview: DWBI, Analytics and Big Data Services
Marlabs Capabilities Overview: DWBI, Analytics and Big Data ServicesMarlabs Capabilities Overview: DWBI, Analytics and Big Data Services
Marlabs Capabilities Overview: DWBI, Analytics and Big Data ServicesMarlabs
 
Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...
Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...
Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...IDERA Software
 
Pr dc 2015 sql server is cheaper than open source
Pr dc 2015 sql server is cheaper than open sourcePr dc 2015 sql server is cheaper than open source
Pr dc 2015 sql server is cheaper than open sourceTerry Bunio
 
Model Confidence for Master Data with David Loshin
Model Confidence for Master Data with David LoshinModel Confidence for Master Data with David Loshin
Model Confidence for Master Data with David LoshinEmbarcadero Technologies
 
Architect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh ArchitectureArchitect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh ArchitectureDatabricks
 
MDM & BI Strategy For Large Enterprises
MDM & BI Strategy For Large EnterprisesMDM & BI Strategy For Large Enterprises
MDM & BI Strategy For Large EnterprisesMark Schoeppel
 
Foundation of Business Intelligence for Business Firms .ppt
Foundation of Business Intelligence for Business Firms .pptFoundation of Business Intelligence for Business Firms .ppt
Foundation of Business Intelligence for Business Firms .pptRoshni814224
 
The Shifting Landscape of Data Integration
The Shifting Landscape of Data IntegrationThe Shifting Landscape of Data Integration
The Shifting Landscape of Data IntegrationDATAVERSITY
 
Akili Oil & Gas Data Practice - PPDM
Akili Oil & Gas Data Practice - PPDMAkili Oil & Gas Data Practice - PPDM
Akili Oil & Gas Data Practice - PPDMrnaramore
 
SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!
SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!
SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!Richard Robinson
 
Strategically manage data quality in an erp rollout
Strategically manage data quality in an erp rolloutStrategically manage data quality in an erp rollout
Strategically manage data quality in an erp rolloutVerdantis Inc.
 
Strategically Manage Data Quality in an ERP Rollout
Strategically Manage Data Quality in an ERP RolloutStrategically Manage Data Quality in an ERP Rollout
Strategically Manage Data Quality in an ERP RolloutVipul Aroh
 
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...Agile Testing Alliance
 
DevOps Spain 2019. Olivier Perard-Oracle
DevOps Spain 2019. Olivier Perard-OracleDevOps Spain 2019. Olivier Perard-Oracle
DevOps Spain 2019. Olivier Perard-OracleatSistemas
 
Achieving a Single View of Business – Critical Data with Master Data Management
Achieving a Single View of Business – Critical Data with Master Data ManagementAchieving a Single View of Business – Critical Data with Master Data Management
Achieving a Single View of Business – Critical Data with Master Data ManagementDATAVERSITY
 

Ähnlich wie Creating enterprise standards 09302010 (20)

Webinar: Initiating a Customer MDM/Data Governance Program
Webinar: Initiating a Customer MDM/Data Governance ProgramWebinar: Initiating a Customer MDM/Data Governance Program
Webinar: Initiating a Customer MDM/Data Governance Program
 
Akili Data Integration using PPDM
Akili Data Integration using PPDMAkili Data Integration using PPDM
Akili Data Integration using PPDM
 
Data Management Workshop - ETOT 2016
Data Management Workshop - ETOT 2016Data Management Workshop - ETOT 2016
Data Management Workshop - ETOT 2016
 
Microsoft master data services mds overview
Microsoft master data services mds overviewMicrosoft master data services mds overview
Microsoft master data services mds overview
 
Marlabs Capabilities Overview: DWBI, Analytics and Big Data Services
Marlabs Capabilities Overview: DWBI, Analytics and Big Data ServicesMarlabs Capabilities Overview: DWBI, Analytics and Big Data Services
Marlabs Capabilities Overview: DWBI, Analytics and Big Data Services
 
Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...
Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...
Geek Sync | Avoid the Seven Mistakes Data Modelers Make in Aiding Data Govern...
 
Pr dc 2015 sql server is cheaper than open source
Pr dc 2015 sql server is cheaper than open sourcePr dc 2015 sql server is cheaper than open source
Pr dc 2015 sql server is cheaper than open source
 
Model Confidence for Master Data with David Loshin
Model Confidence for Master Data with David LoshinModel Confidence for Master Data with David Loshin
Model Confidence for Master Data with David Loshin
 
Architect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh ArchitectureArchitect’s Open-Source Guide for a Data Mesh Architecture
Architect’s Open-Source Guide for a Data Mesh Architecture
 
MDM & BI Strategy For Large Enterprises
MDM & BI Strategy For Large EnterprisesMDM & BI Strategy For Large Enterprises
MDM & BI Strategy For Large Enterprises
 
Foundation of Business Intelligence for Business Firms .ppt
Foundation of Business Intelligence for Business Firms .pptFoundation of Business Intelligence for Business Firms .ppt
Foundation of Business Intelligence for Business Firms .ppt
 
The Shifting Landscape of Data Integration
The Shifting Landscape of Data IntegrationThe Shifting Landscape of Data Integration
The Shifting Landscape of Data Integration
 
Akili Oil & Gas Data Practice - PPDM
Akili Oil & Gas Data Practice - PPDMAkili Oil & Gas Data Practice - PPDM
Akili Oil & Gas Data Practice - PPDM
 
SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!
SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!
SCRIMPS-STD: Test Automation Design Principles - and asking the right questions!
 
Strategically manage data quality in an erp rollout
Strategically manage data quality in an erp rolloutStrategically manage data quality in an erp rollout
Strategically manage data quality in an erp rollout
 
Strategically Manage Data Quality in an ERP Rollout
Strategically Manage Data Quality in an ERP RolloutStrategically Manage Data Quality in an ERP Rollout
Strategically Manage Data Quality in an ERP Rollout
 
Cloud Strategy
Cloud StrategyCloud Strategy
Cloud Strategy
 
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
ATAGTR2017 Performance Testing and Non-Functional Testing Strategy for Big Da...
 
DevOps Spain 2019. Olivier Perard-Oracle
DevOps Spain 2019. Olivier Perard-OracleDevOps Spain 2019. Olivier Perard-Oracle
DevOps Spain 2019. Olivier Perard-Oracle
 
Achieving a Single View of Business – Critical Data with Master Data Management
Achieving a Single View of Business – Critical Data with Master Data ManagementAchieving a Single View of Business – Critical Data with Master Data Management
Achieving a Single View of Business – Critical Data with Master Data Management
 

Mehr von ERwin Modeling

Zen of metadata 09212010
Zen of metadata 09212010Zen of metadata 09212010
Zen of metadata 09212010ERwin Modeling
 
Staying relevant in todays changing dm environment 09282010
Staying relevant in todays changing dm environment 09282010Staying relevant in todays changing dm environment 09282010
Staying relevant in todays changing dm environment 09282010ERwin Modeling
 
Monetizing data management 09162010
Monetizing data management 09162010Monetizing data management 09162010
Monetizing data management 09162010ERwin Modeling
 
Effective capture of metadata using ca e rwin data modeler 09232010
Effective capture of metadata using ca e rwin data modeler 09232010Effective capture of metadata using ca e rwin data modeler 09232010
Effective capture of metadata using ca e rwin data modeler 09232010ERwin Modeling
 
Deciding to go cloud 09212010
Deciding to go cloud  09212010Deciding to go cloud  09212010
Deciding to go cloud 09212010ERwin Modeling
 
Ca e rwin modeling global user communities_09232010 - webcast
Ca e rwin modeling global user communities_09232010 - webcastCa e rwin modeling global user communities_09232010 - webcast
Ca e rwin modeling global user communities_09232010 - webcastERwin Modeling
 
10 things to avoid in data model 09242010
10 things to avoid in data model 0924201010 things to avoid in data model 09242010
10 things to avoid in data model 09242010ERwin Modeling
 
5 physical data modeling blunders 09092010
5 physical data modeling blunders 090920105 physical data modeling blunders 09092010
5 physical data modeling blunders 09092010ERwin Modeling
 
Optimizing the design of your data warehouse 09222010
Optimizing the design of your data warehouse 09222010Optimizing the design of your data warehouse 09222010
Optimizing the design of your data warehouse 09222010ERwin Modeling
 

Mehr von ERwin Modeling (9)

Zen of metadata 09212010
Zen of metadata 09212010Zen of metadata 09212010
Zen of metadata 09212010
 
Staying relevant in todays changing dm environment 09282010
Staying relevant in todays changing dm environment 09282010Staying relevant in todays changing dm environment 09282010
Staying relevant in todays changing dm environment 09282010
 
Monetizing data management 09162010
Monetizing data management 09162010Monetizing data management 09162010
Monetizing data management 09162010
 
Effective capture of metadata using ca e rwin data modeler 09232010
Effective capture of metadata using ca e rwin data modeler 09232010Effective capture of metadata using ca e rwin data modeler 09232010
Effective capture of metadata using ca e rwin data modeler 09232010
 
Deciding to go cloud 09212010
Deciding to go cloud  09212010Deciding to go cloud  09212010
Deciding to go cloud 09212010
 
Ca e rwin modeling global user communities_09232010 - webcast
Ca e rwin modeling global user communities_09232010 - webcastCa e rwin modeling global user communities_09232010 - webcast
Ca e rwin modeling global user communities_09232010 - webcast
 
10 things to avoid in data model 09242010
10 things to avoid in data model 0924201010 things to avoid in data model 09242010
10 things to avoid in data model 09242010
 
5 physical data modeling blunders 09092010
5 physical data modeling blunders 090920105 physical data modeling blunders 09092010
5 physical data modeling blunders 09092010
 
Optimizing the design of your data warehouse 09222010
Optimizing the design of your data warehouse 09222010Optimizing the design of your data warehouse 09222010
Optimizing the design of your data warehouse 09222010
 

Kürzlich hochgeladen

[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdfSandro Moreira
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FMESafe Software
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native ApplicationsWSO2
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyKhushali Kathiriya
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWERMadyBayot
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Zilliz
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityWSO2
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxRustici Software
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...apidays
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Victor Rentea
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century educationjfdjdjcjdnsjd
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontologyjohnbeverley2021
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...apidays
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MIND CTI
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...Zilliz
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesrafiqahmad00786416
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProduct Anonymous
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelDeepika Singh
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Bhuvaneswari Subramani
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc
 

Kürzlich hochgeladen (20)

[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)Introduction to Multilingual Retrieval Augmented Generation (RAG)
Introduction to Multilingual Retrieval Augmented Generation (RAG)
 
Platformless Horizons for Digital Adaptability
Platformless Horizons for Digital AdaptabilityPlatformless Horizons for Digital Adaptability
Platformless Horizons for Digital Adaptability
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
Six Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal OntologySix Myths about Ontologies: The Basics of Formal Ontology
Six Myths about Ontologies: The Basics of Formal Ontology
 
Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...Apidays New York 2024 - The value of a flexible API Management solution for O...
Apidays New York 2024 - The value of a flexible API Management solution for O...
 
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
ICT role in 21st century education and its challenges
ICT role in 21st century education and its challengesICT role in 21st century education and its challenges
ICT role in 21st century education and its challenges
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot ModelMcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Mcleodganj Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​Elevate Developer Efficiency & build GenAI Application with Amazon Q​
Elevate Developer Efficiency & build GenAI Application with Amazon Q​
 
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data DiscoveryTrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
TrustArc Webinar - Unlock the Power of AI-Driven Data Discovery
 

Creating enterprise standards 09302010

  • 1. Creating Enterprise Standards with CA ERwin® Data Modeling Terry Hanks – CA Presales Consultant
  • 2. Abstract • As data volumes increase, and organizations are faced with data integration challenges associated with mergers and acquisitions, master data management, business intelligence, and/or data governance initiatives, the need to create consistent, reusable standards is more critical than ever before. Standards help increase efficiency and quality by promoting reuse across the organization. PAGE 2
  • 3. Speaker Bio • Terry Hanks is a CA Technologies Presales Consultant for the CA Erwin Modeling Family of products. He has worked with the Modeling Product line for 5 years. • Prior to joining CA Technologies, Terry worked in the Health care IT industry. PAGE 3
  • 4. Agenda • Why Use Enterprise Data Standards • Implementing Standards with CA ERwin Modeling – Leveraging Naming Standards and Domains – User Defined Properties (UDP’s) – Defining Data Type Standards – Using Model Templates – Sharing Standards using CA ERwin Model Manager – Reporting to Stakeholders using Crystal Reports • Live Demo • Q&A PAGE 4
  • 5. Why use Enterprise Standards? • Business decisions are based on data – bad data or design results in bad business decisions • Benefits of using data standards: – Increased Efficiency – Increased Data Quality – Promotes Reuse and Communication across the organization. PAGE 5
  • 6. Who uses Enterprise Standards? • Many types of initiatives can benefit from Enterprise Standards  Data Warehousing  Master Data Management (MDM)  Mergers and Acquisitions  Data Integration  Application Development  Data Quality  Data Governance PAGE 6
  • 7. Using Naming Standards • What is a Naming Standard? – A glossary of words and abbreviations that can be used in model object names • Why use the Naming Standards Editor? – Develop model naming standards – Check model names for accuracy – Name model objects in models derived from other models – Reuse of standards across the enterprise PAGE 7
  • 8. Using Domains • What is a Domain? – A set of values and rules assigned to a data element • Example: Data types, Validation rules – Used to quickly assign properties to columns • Why use Domains? – Speeds Design process – Easy to maintain – Use across entire model PAGE 8
  • 9. Using User Defined Properties (UDPs) • What is a UDP ? – Provides the ability to define custom model object properties • Why use UDPs? – Further documentation of model objects – Clarification for users or viewers of models – Standardize usage across models • Examples of Common UDPs – Data Stewards, Status, Document attachments, etc. PAGE 9
  • 10. Using Datatype Standards • What is a Datatype Standards file? – Includes user-defined datatypes and mapping information that is needed to convert logical & physical datatypes. • Why use a Datatype Standards file? – Converting models from Logical to Physical – Converting models from one Physical DBMS to another – Deriving multiple models from one source – Introducing new data types PAGE 10
  • 11. Using Model Templates with Standards • What is a Model Template? – A starting point for new models containing reusable objects such as: • Domains • Naming standards • Formatting options • Etc. • Why use a Model Template? – Provides Standardization and Reuse – Speeds up development/altering of models/databases PAGE 11
  • 12. Sharing Standards Using CA ERwin Model Manager • What is CA ERwin Model Manager? – Central location for storing standards, such as: • Naming Standards • Datatype Standards • Model Templates – Collaboration for use, reuse, and audit • Why use CA ERwin Model Manager? – Reuse of core data assets – Efficiencies for team collaboration – Access to other models for sharing objects via Complete Compare PAGE 12
  • 13. Reporting to Stakeholders • Sharing information in customizable formats • CA ERwin Data Modeler provides multiple reporting options – HTML – PDF – Text – RTF – Crystal Reports – OBDC queries • In addition, these reports may be filtered by Subject Areas or Stored Displays PAGE 13
  • 14. Demo • CA ERwin Data Modeler Enterprise Standards Demo PAGE 14