A Holistic Framework for Enterprise Data Management DAMA NCR

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1 A Holistic Framework for Enterprise Data Management DAMA NCR Deborah L. Brooks March 13, 2007

2 Agenda What is Enterprise Data Management? Why an EDM Framework? EDM High-Level Framework EDM Framework Components EDM Framework Activity View EDM Framework Artifact View Conclusion 1

3 It s a lot like an elephant What is Enterprise Data Management? (from the parable The Six Blind Men and the Elephant ) 2

4 What is Enterprise Data Management? It depends on what your perspective is: Chief Information Officer Data Strategist Data Architect Data Analyst Data Administrator Database Administrator Data Owner / Steward Data Sharing Stakeholder Data Quality Specialist 3

5 Why an EDM Framework? Data Management professionals need to take a holistic approach to Enterprise Data Management that encompasses all perspectives to: Ensure that data is managed as an enterprise asset Ensure the definition and development of data solutions (transactional, analytical, portal) that are: Robust Scalable High-Performance Interoperable Secure High-Quality 4

6 EDM High-Level Framework Data Strategy & & Planning Vision Strategy Portfolio/Investments Goals & Objectives Scope Resources (Staff, Budget, Technology) DM Activities & Artifacts Data Architecture & Data Architecture & Design Conceptual Data Model Logical Data Model Physical Data Model Information Flows/Interfaces Business Rules Data Transformation Rules Data Engineering & Data Engineering & Operations Database Impl. & Maintenance Data Conversion Backup & Recovery Archiving & Retention Logging & Audit Performance & Availability Data Access & Data Access & Exchange Data Security & Privacy Data Quality Data Harmonization Data Registration Data Integration Data Presentation Data Governance Governance Framework/Oversight Ownership & Stewardship Policy & Procedures SLAs & Metrics Education & Training Outreach DM Foundation Name Metadata Metadata Definition & Semantics Management Domain Data Standards Modeling Metadata Documentation Structure Quality Lineage Security & Privacy Rules Stakeholders/COI Data Sharing Owner & Steward Implementation Operations Data Tools & & Technologies Repository Conversion Profiling & Cleansing Modeling DBMS Integration Registry Utilities Portal Business Intelligence Data Mining Decision Analytics 5

7 Data Strategy & Planning EDM Framework Components Activities Vision Definition Strategy Planning Investment Planning Goals & Objectives Setting Scope Definition Resource Planning Transition Planning Artifacts Vision Statement Data Management Strategy Investment Management Plan Goals & Objectives Scope Resource Plan Transition Plan 6

8 Data Architecture & Design EDM Framework Components Activities Data Requirements Definition Data Analysis Data Modeling Database Design Information Flow / Interface Definition Rule Definition Artifacts Data Requirements Conceptual Data Model Logical Data Model Physical Data Model / Database Design Data Interface / Service Specification Data Conversion Specification Business Rules 7

9 EDM Framework Components Data Engineering & Operations Activities Database Implementation & Maintenance Data Conversion Backup & Recovery Artifacts Production Database Data Management Plan Disaster Recovery Plan Archiving & Retention Logging & Audit Performance Tuning 8

10 Data Access & Exchange EDM Framework Components Activities Data Security Data Profiling Data Harmonization Data Integration Data Registration DB Connection Configuration Artifacts Data Access Privileges Privacy Impact Assessment Data Quality Assessment Data Registry Database Connections 9

11 Data Governance EDM Framework Components Activities Governance Establishment & Oversight Ownership & Stewardship Policy & Procedure Definition Service Level Agreements (SLA) & Metric Definition Education & Training Artifacts Governance Framework Policy & Procedures Service Level Agreements (SLA) & Metrics Classes & Seminars Communications Outreach 10

12 EDM Framework Components Metadata Name Definition & Semantics Domain Structure Lineage Rules Quality Security & Privacy Stakeholders / Community of Interest (COI) Owner & Steward Implementation Operations 11

13 Data Standards Modeling Metadata Documentation Data Access Data Exchange EDM Framework Components 12

14 EDM Framework Components Data Tools & Technologies Repository Modeling Registry Conversion DBMS & Utilities Profiling & Cleansing Data Integration Database Access Business Intelligence Data / Text Mining Decision Analytics Statistical Analysis 13

15 EDM Framework Activity View DM Activities Data Strategy & & Planning Data Architecture & Data Architecture & Design Design Data Conceptual Requirements Data Model Definition Data Logical Analysis Data Model Data Physical Modeling Data Model Database Information Design Flows/Interfaces Info. Business Flow/Interface Rules Definition Rule Data Definition Transformation Rules Vision Vision Definition Scope Definition Goals & Objectives Transition Planning Strategy Strategy Development Goals & Scope Objectives Setting Investment Portfolio/Investments Planning Resource Resources Planning (Staff, Budget, Technology) Data Engineering & Data Engineering & Operations Operations Database Database Impl. Impl. & Maintenance Maintenance Data Data Conversion Conversion Backup Backup & Recovery Recovery Archiving & Retention Logging & Audit Performance Performance Tuning & Availability Data Access & Data Access & Exchange Exchange Data Data Security Security & Privacy Data Data Profiling Quality Data Data Harmonization Harmonization Data Registration Integration Data Integration Registration Data DB Connection Presentation Configuration Data Governance Governance Framework/Oversight Establishment & Oversight Ownership & Stewardship Policy & Procedures Definition SLAs & MetricsDefinition Education & Training Outreach DM Foundation Metadata Management Data Standards Name Definition & Semantics Domain Modeling Metadata Documentation Structure Quality Lineage Security & Privacy Rules Stakeholders/COI Data Access Sharing Data Exchange Owner & Steward Implementation Operations Data Tools & & Technologies Repository Modeling DBMS Conversion & Utilities Profiling Data & Cleansing Integration Profiling DBMS & Cleansing Integration Database Access Registry Conversion Utilities Portal Data/Text Mining Business Intelligence Data Statistical Mining Analysis Decision Analytics 14

16 EDM Framework Artifact View Data Strategy & & Planning Vision Vision Statement Goals Goals & Objectives & Objectives Transition Plan Data Strategy Management Strategy Scope Scope Portfolio/Investments Management Plan Resources (Staff, Plan Budget, Technology) DM Artifacts Data Architecture & Data Engineering & Data Architecture & Data Engineering & Design Operations Design Operations Data Requirements Production Database Conceptual Data Model Database Impl. & Maintenance Conceptual Data Model Logical Data Model Data Data Conversion Management Plan Logical Data Model Physical Data Model Backup Disaster & Recovery Recovery Plan Physical Data Model/DB Design Information Flows/Interfaces Archiving & Retention Data Interface/Service Specification Business Rules Logging & Audit Data Conversion Specification Data Transformation Rules Performance & Availability Business Rules Data Access & Exchange Data Access Privileges Privacy Impact Assessment Data Quality Assessment Data Registry Database Connections Data Governance Governance Governance Framework/Oversight Ownership & Policy Stewardship & Procedures Policy & Procedures SLAs & Metrics Education Classes & Seminars Training Outreach Communications DM Foundation Metadata Management Data Standards Name Definition & Semantics Domain Modeling Metadata Documentation Structure Quality Lineage Security & Privacy Rules Stakeholders/COI Data Access Sharing Data Exchange Owner/Steward & Implementation Operations Data Tools & & Technologies Repository Modeling DBMS Conversion & Utilities Profiling Data & Cleansing Integration Profiling DBMS & Cleansing Integration Database Access Registry Conversion Utilities Portal Data/Text Mining Business Intelligence Data Statistical Mining Analysis Decision Analytics 15

17 Conclusion The scope of Enterprise Data Management is both broad and deep, requiring a holistic, disciplined approach to ensure the definition and development of robust, scalable, highperformance, interoperable, secure and high-quality data solutions and the management of data as an enterprise asset. Metadata, Data Standards and Data Tools and Technologies form the underlying foundation for all Data Management Activities and Artifacts. 16

18 Conclusion Don t be one of the 6 blind men. There are many perspectives other than your own that comprise Enterprise Data Management, so remember to take a holistic view when working on a data-related initiative. 17

19 Questions Deborah L. Brooks The MITRE Corporation

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