CDMP Specialist Deep Dive: Data Governance ( specialistdatagovern | 35 hours )

​​​​​​The course is intended for business and IT professionals at all levels who have been charged with investigating or implementing Data Governance in their organizations, and who seek to gain an in-depth understanding of where Data Governance exists within the different disciplines of Data and Information Management. It also was developed as a preparation course for people wishing to take the CDMP Data Governance Specialist exam. 

The training presents methods and practices for addressing key Data Governance challenges and equipping organizations to address the challenges that increased regulatory scrutiny brings.

In this course the vital relationship between Data Governance and other core information disciplines – including Data Quality, Master Data Management, and Data Modeling – will be highlighted.

• Learn about the need for and application of Data Governance for different categories of challenges
• Understand the Data Governance implications of a variety of regulatory acts and how to prepare your organization for compliance
• Explore a Data Governance framework and understand how it aligns with other architecture frameworks
• Understand the core concept of information lifecycle management, the different stages, and why they are important
• Understand the critical roles Data Governance plays in the information disciplines of Master Data Management and Data Quality Management
• Understand the roles and activities of the data owner and data steward

Data Governance Overview, Definitions, and CDMP Exam Coverage

• Data Governance Exam Breakdown
  • Question Difficulty
• Why is Data Management Critical?
• Business Environmental Elements
• Data, Information and Knowledge
• Data Governance
  • Other Definitions of Data Governance
  • What is Data Governance?
• Assets
  • Data is an Asset
• Quiz 1
• Which Other Areas Does Data Governance Have a Role in?
• Data Quality Management
• Data Errors Over Time (Graphs)
• Juran Trilogy
• Data Quality Profiling – Assess Data Quality
  • Caution When Defining Data Quality Indicators
• Reference and Master Data Management
  • What Is… Master & Reference Data and Master Data Management
  • What Should Be Mastered?
  • Reinventing the Wheel?
  • MDM Implementation
  • Implementation: Operational Vs. Analytical MDM
  • Conclusions
• Data Modeling & Design
  • Data Modeling Enables Core Business Considerations
  • Data Modelling Facilitates – What is the Data We Need to Run Our Business?
    • Data Modelling Facilitates – Do We Agree What It Means?
    • Data Modelling Facilitates – Do We Know Where It Is?
    • Data Modelling Facilitates – Have Accountabilities with the Right Skills & Processes Been Allocated to Manage it?
    • Data Modelling Facilitates – Is it Fit for Purpose?
• Data Governance & Models – Metadata Extensions
• Linkages: Everything Relies on the Data
• Data Warehousing & Business Intelligence (& Big Data)
  • Classic Characteristics of a DW
  • Why Use a Data Warehouse?
  • Conceptual DW/BI and Big data Architecture
• Data Security Management
  • Data Security Guiding Principles
  • Assessment of Risk Exposure
• Metadata Management
  • Metadata Covers the 6 Interrogatives of Data
  • Types of Meta-Data
  • Data Stewardship Metadata
  • Metadata & Data Governance
  • Types & Typical Sources of Metadata
• Data Architecture & Lifecycle Management
• Process & Data Model Relationship
  • Process and Data are Related
• The Information Lifecycle
  • Information Lifecycle Activities – PLAN
  • Information Lifecycle Activities – ARCHIVE & RETRIEVE
  • Information Lifecycle Activities – PURGE
• Data Storage & Operations
  • Factors Affecting Availability Vs. Performance
  • Document, Records & Content Management
  • Key Terms
  •  Generally Accepted Recordkeeping Principles GARP
    • Document/Record Management Lifecycle
    • Document Control Schemes
  • Data Integration & Interoperability
  • Data Replication
  • Data Governance
    • Data Governance as a Program
    • 3 Motivations & Behaviors for Data Governance
    • Information in Context
    • Drivers for Data Governance
  • Quiz 2
  • Review of Today’s Topics

Data Governance Program, Scope, and Maturity Assessment

• Models & Data Governance (DG)

• • DG Framework (Common Themes in DG Models & Frameworks)
• Scope – 5 Considerations in Setting Data Governance Scope
• Exercise 1: Is Data Treated as a Corporate Asset? 
• Exercise 2: Drivers for Data Governance/Information Management for Your Company
• Baseline: Maturity Assessment
  • Maturity Assessments
  • Example: Data Governance Maturity Assessment
  • Exercise 3: 5 DG Maturity Levels Comparison to Your Company
• Data Governance Strategy & Implementation – Typical data Governance Implementation Approach
• Quiz 3
• Principles and Minimum Standards
  • Example: Data Management Principles
• Data is an Enterprise Asset
• Minimum Data Standards & Metrics
  • Data Management Measures (Example with 2 Principles)
• Example Governance Workflow (RACI)
  • Example Governance Workflow (Processes)
• Process Detail (Example)
• Reinventing the Wheel?
• Portfolio Vs. Per Project
• Data Management Organizations (DMBOK)
  • Data Governance Office
  • Data Governance Organization
  • Typical DG Roles and Responsibilities
• Example Governance (RACI)
• Example: Data Governance Steering Committee
• Example: Data Governance Council
• Example Data Governance Structure
• Data Stewardship
  • Data Stewards (DMBOK)
• Data Owner – Data Roles
  • Data Owner – Main Activities
  • Skills & Skill Levels Required for Roles
  • Example Skill – Data Governance
• Steward – Data Roles
  • Data Steward – Role Activities
  • Data Steward
  • Skills & Skill Levels Required for Roles
• Data Custodian – Data Roles
  • Data Custodian / System Owner
  • Data Custodian
• Data Governance Levels
• Data Management Roles
• Quiz 4
• Review of Today’s Topics

 Data Governance Skills, Competencies, and Activities

• Components of a Data Capabilities & Competencies Framework – Overview
• Behaviors & Attitudes
• General Competencies
• Role Families & Roles
  • Role Families & Roles – Architecture & Design Role Family / Data Management Roles
  • Skills & Skill Levels Required for Roles – Enterprise Information Architect
  • Critical Success Factors – Skills & Competencies for Data Management
  • Skills & Skill Levels Required for Roles – Data Owner
• Guiding Principles
  • Data Governance Enables Core Business Considerations
  • Data Governance Enables: What is the Data That We Need to Run Our Business?
  • Data Governance Enables: Do We Agree What It Means?
  • Data Governance Enables: Do We Know Where it is?
  • Data Governance Enables: Have Accountabilities with the Right Skills & Processes Been Allocated to Manage it?
  • Data Governance Enables: Is it Fit for Purpose?
• Activities
• Data Strategy & DMBOK2 – Define the Data Governance Strategy
  • Data Strategy in Context
• Organizational Strategy
• Quiz 5
• Diagnosing Organizational Readiness
• Barriers to Managing Information as a Business Asset
• Stakeholder Management
  • Benefits of Stakeholder management
  • Stakeholders: Who are Your Stakeholders?
  • Difference Between Stakeholder & Shareholder
  • Stakeholder Management
• Organizational Models for DG
  • DG Organization Model / Rationale
• Operating Models for DG
  • Operating Model – Centralized
  • Operating Model – Decentralized
  • Operating Model – federated
  • Operating Model – Hybrid
  • Operating Model – Self Organizing Teams
• Considerations
• Data Value Standards (Some Examples)
• BCBS 239 & Data Management
  • Mapping from DG Principle to BCBS 239 Principles
• Quiz 6
• Data Management Tool Genres (Illustrative)
  • A Data Governance Tool?
• 10 DG Worst Practices
• Enterprise Information Architecture
• Importance of Reference Data
• Focus on Important Stuff for Data Governance
• Evangelism & Outreach
• Data Governance Summary 1
  • Data Governance Summary 2
  • Data Governance Summary 3
• Data Handling Ethics
  • Data Ethics
  • Ethical Issues Raised By IT
  • Ethical Risks in a Sampling Project
• Quiz 7