Course Code: datamgtbspk
Duration: 28 hours
Course Outline:

1. Devises and implements master data management processes:

  • Topic: Master Data Management (MDM) Processes
  1. Introduction to MDM and its importance
  2. MDM process design principles
  3. Data governance frameworks (e.g., DAMA-DMBOK)
  4. MDM implementation methodologies (e.g., Gartner's MDM Framework)
  5. MDM tools and technologies (e.g., Informatica MDM, SAP MDG)

2. Derives data management structures and metadata:

  • Topic: Data Management Structures and Metadata
  1. Data modeling concepts and techniques
  2. Entity-Relationship (ER) modeling
  3. Data schemas and schema design
  4. Metadata management frameworks (e.g., ISO/IEC 11179)
  5. Data integration and ETL (Extract, Transform, Load) tools (e.g., Talend, Informatica PowerCenter)

3. Plans effective data storage, sharing, and publishing: 

  • Topic: Data Storage, Sharing, and Publishing
  1. Data storage options: relational databases, data lakes, cloud storage
  2. Data sharing mechanisms: APIs, data services, data catalogs
  3. Data publishing and reporting frameworks (e.g., Tableau, Power BI)
  4. Data privacy and security considerations
  5. Data governance frameworks (e.g., COBIT, GDPR)

4. Independently validates external information: 

  • Topic: External Data Validation
  1. Data validation techniques and best practices
  2. Data quality assessment frameworks (e.g., DAMA DQAF)
  3. Data source evaluation and reliability assessment
  4. Data profiling and cleansing tools (e.g., Trifacta, Talend Data Quality)

5. Assesses issues preventing maximum use of information assets: 

  • Topic: Data Utilization Assessment
  1. Data audit and assessment methodologies
  2. Data quality issue identification and resolution
  3. Data governance frameworks (e.g., DMBOK)
  4. Data integration and interoperability challenges
  5. Data management maturity models (e.g., CMMI-DM)

6. Provides expert advice and guidance on data assets: 

  • Topic: Data Management Best Practices and Expertise
  1. Emerging trends in data management
  2. Data strategy development frameworks
  3. Data-driven decision-making frameworks
  4. Data management certifications (e.g., CDMP, CDP)
  5. Case studies and real-world examples