VIFM Assessment Center

Course overview

The Certified Data Management Professional (CDMP) credential is awarded to those who qualify based on a combination of criteria including education, experience, and test-based examination of professional level knowledge. This credential is offered at the Mastery or Practitioner level. To maintain certified status and continued use of the credential, an annual recertification fee along with a 3-year cycle of continuing education and professional activity is required. The Data Management Association International (DAMA) authorizes the Certified Data Management Professional certification program and granting of the CDMP designation in partnership with the Institute for Certification of Computing Professionals (ICCP), which administers testing and re-certification. This document outlines the requirements for obtaining the CDMP.

Target audience

This course is designed for Data Professional Work Experience who has minimum of 2 years' experience in data management, for those who want to recertify, and professionals who are looking for continuing education in Data Management domain

Course objectives

Apply key concepts of Data Management in the organization
Implement data governance
Recommend data security
Manage data quality
Manage data for organizational change
Design data model

Target competencies

Data Management Essential Concepts

Data Management Framework

Data Handling

Data Governance

Data Architecture

Data Modeling and Design

Data Storage and Operation

Data Security

Data Integration and Interoperability

Document And Content Management

Data Warehouse and Business Intelligence

Metadata Management

Data Quality

Big Data and Data Science

Data Management Maturity

Data Management and Organization Chance Management

Course methodology

This course is an instructor led, participant will be required to complete exercises, case studies individually and in groups.

Course outline

INTRODUCTION

Business Drivers
Goals

ESSENTIAL CONCEPTS

Data and Information
Data as an Organizational Asset
Data Management Principles
Data Management Challenges
Data Management Strategy

DATA MANAGEMENT FRAMEWORKS

Strategic Alignment Model
The Amsterdam Information Model
The DAMA-DMBOK Framework
DMBOK Pyramid (Aiken)
DAMA Data Management

DATA HANDLING

Introduction
- Business Drivers
Essential Concepts
- Ethical Principles for Data
- Principles Behind Data Privacy Law
- Online Data in an Ethical Context
Risks of Unethical Data Handling
- Practices
- Establishing an Ethical Data Culture
- Data Ethics and Governance
- Works Cited / Recommended

DATA GOVERNANCE

Introduction to Data Governance
Activities
Tools and Techniques
Implementation Guidelines
Metrics
Works Cited

DATA ARCHITECTURE

Introduction to Data Architecture
Activities
Tools
Techniques
Implementation Guidelines
Data Architecture Governance
Works Cited

DATA MODELING AND DESIGN

Introduction to Data Modeling
Activities
Tools
Best Practices
Data Model Governance
Works Cited

DATA STORAGE AND OPERATIONS

Introduction to Data Modeling
Activities
Tools
Techniques
Implementation Guidelines
Data Storage Operation Governance
Works Cited

DATA SECURITY

Introduction to Data Security
Activities
Tools
Techniques
Implementation Guidelines
Data Security Governance
Works Cited

DATA INTEGRATION AND INTEROPERABILITY

Introduction to Data Integration
Data Integration Activities
Tools
Techniques
Implementation Guidelines
DDI Governance
Works Cited

DOCUMENT AND CONTENT MANAGEMENT

Introduction to DCM
Activities
Tools
Techniques
Implementation Guidelines
Document and Content Governance
Works Cited

REFERENCE AND MASTER DATA

Introduction to DCM
Activities
Tools
Techniques
Implementation Guidelines
Organization and Cultural Change
Reference and Master Data Governance
Works Cited

DATA WAREHOUSE AND BUSINESS INTELLIGENCE

Introduction to DW/BI
Activities
Tools
Techniques
Implementation Guidelines
DW/BI Governance
Works Cited

METADATA MANAGEMENT

Introduction to DW/BI
Activities
Tools
Techniques
Implementation Guidelines
Metadata Governance
Works Cited

DATA QUALITY

Introduction to DW/BI
Activities
Tools
Techniques
Implementation Guidelines
Data Quality and Data Governance
Works Cited

BIG DATA AND DATA SCIENCE

Introduction to Big Data and Data Science
Activities
Tools
Techniques
Implementation Guidelines
Big Data and Data Science Governance
Works Cited

DATA MANAGEMENT MATURITY ASSESSMENT

Introduction to DMMA
Activities
Tools
Techniques
Implementation Guidelines
Maturity Management Governance
Works Cited

DATA MANAGEMENT ORGANIZATION AND ROLE EXPECTATION

Introduction
Understand Existing Organization and Cultural Norms
Data Management Organizational Constructs
Critical Success Factor
Build the Data Management Organization
Interactions Between the DMO and Other Data-oriented Bodies
Data Management Role

DATA MANAGEMENT AND ORGANIZATION CHANCE MANAGEMENT

Introduction
Introduction
Laws of Change
Not Managing a Change: Managing a Transition
Kotter's Eight Errors of Change Management
Kotter's Eight Stage Process for Major Change
The Formula for Change
Diffusion of Innovations and Sustaining Change
Sustaining Change
Communicating Data Management Value
Works Cited / Recommended

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