Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Course Outline
INTRODUCTION TO DAMA
- Definition of data management and its critical importance.
- Overview of the distinct disciplines within data management.
- DAMA and the DMBoK 2.0, including their relationship with other frameworks such as TOGAF and COBIT.
- Overview of available professional certifications, with a focus on the DAMA CDMP.
DATA GOVERNANCE
- Definition of Data Governance, its importance, and a typical reference model.
- Primary data governance roles: owner, steward, and custodian.
- The role of the Data Governance Office (DGO) and its interaction with the PMO.
- Distinctions between Data Governance and IT Governance, and the relevance of these differences.
- Overview of data management implications related to selected regulatory frameworks.
- Key steps organizations should take to prepare for compliance with current and future regulations.
- Strategies for initiating, sustaining, and expanding data governance efforts.
DATA LIFECYCLE MANAGEMENT
- Proactive planning for managing data throughout its lifecycle.
- Differences between the data lifecycle and the Systems Development Lifecycle (SDLC).
- Integration of data governance touchpoints across the data lifecycle.
METADATA MANAGEMENT
- Definition of metadata and its importance.
- Types, uses, and sources of metadata.
- The connection between metadata and business glossaries.
- How metadata serves as the essential link for data governance and adherence to metadata standards.
DG MINI PROJECT
- Launching the Data Governance Program: critical early steps and developing a realistic business case for DG aligned with business objectives.
DOCUMENT RECORDS & CONTENT MANAGEMENT
- The importance of document and records management.
- Distinctions between taxonomy and ontology.
- Legal and regulatory factors impacting records and content management.
DATA MODELING BASICS
- Types of data models, their applications, and interrelationships.
- Development and utilization of data models, ranging from enterprise-level to conceptual, logical, physical, and dimensional models.
- Maturity assessment for evaluating how models are used within the enterprise and integrated into the System Development Life Cycle (SDLC).
- Data modeling in the context of big data.
- Why data modeling is critical to data governance, accompanied by a business process case study.
DATA QUALITY MANAGEMENT
- The various facets of data quality and why validity is often mistaken for quality.
- Policies, procedures, metrics, technology, and resources required to ensure data quality.
- A data quality reference model and its practical application.
- The interconnectedness of data quality management and data governance, illustrated with case studies.
DATA OPERATIONS MANAGEMENT
- Core roles and key considerations for data operations.
- Best practices for effective data operations.
DATA RISK & SECURITY
- Identifying threats and implementing defenses to prevent unauthorized access, use, or loss of data, with a specific focus on personal data abuse.
- Identifying risks to data and its usage beyond just security concerns.
- Data management considerations for various regulations, such as GDPR and BCBS239.
- The role of data governance in managing data security.
MASTER & REFERENCE DATA MANAGEMENT
- Differences between reference data and master data.
- Identification and management of master data across the enterprise.
- Four generic MDM architectures and their suitability for different scenarios.
- Strategies for incrementally implementing MDM to align with business priorities.
- Case study: Statoil (Equinor).
DATA WAREHOUSING, BUSINESS INTELLIGENCE & DATA ANALYTICS
- Definition of data warehousing and business intelligence, and their necessity.
- Major data warehouse architectures, including Inmon and Kimball approaches.
- Introduction to dimensional data modeling.
- Reasons why master data management may fail without adequate data governance.
- Data analytics, machine learning, and data visualization.
DATA INTEGRATION & INTEROPERABILITY
- Business and technological issues that data integration aims to resolve.
- Differences between data integration and data interoperability.
- Various styles of data integration and interoperability, their applicability, and implications.
- Approaches and guidelines for providing data integration and access.
35 Hours
Testimonials (7)
Very engaging
Samieg - Vodacom
Course - Certified Data Management Professional (CDMP)
it was very interactive and although I was not exposed to some modules before, Gaurav made it easy to understand. Good Participation in the team
UVASH - Vodacom
Course - Certified Data Management Professional (CDMP)
The training covered all the areas that were required. Very Insightful.
Carol - Vodacom
Course - Certified Data Management Professional (CDMP)
Material was covered according to the weight of the exam's marks. gave a better understanding of this course. Quizes helped a lot
Saika - Vodacom
Course - Certified Data Management Professional (CDMP)
Quizzes to test our knowledge and white board work kept us engaged.
Paula Dunsby - Vodacom
Course - Certified Data Management Professional (CDMP)
The instructor was very simple and clear on the point of the course
Mohamed - Dubai Government Human Resources Department - DGHR
Course - Certified Data Management Professional (CDMP)
Practical knowledge of the trainer
