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Data Management Fundamentals

5 Day Training

Dates: Available on Request
Locations: Johannesburg, South Africa
Platform: Available In-Class / Online

Price: Available on Request

Course Introduction

Effective data management is crucial for organizations to ensure data accuracy, consistency, and accessibility, as well as comply with legal and regulatory requirements. It helps organizations make informed decisions, improves operational efficiency, and enhances customer satisfaction.

 

This 5-day Data Management Fundamentals course covers all Information Management disciplines defined in the DAMA Body of Knowledge (DMBoK). This course provides a solid foundation across the entire Information Management spectrum. Attendees will gain a firm grounding in core Information Management concepts and learn their practical application through real examples of Information Architecture.

Course Objectives

This Data Management Fundamentals course aims to equip you with the knowledge, methods, and techniques needed to analyse, mature, and implement information management solutions within your organization. Topics covered include:

  • Data Lifecycle Management

  • Data Integration

  • Data Governance

  • Risk, Security, and Regulatory Compliance

  • Data Quality Management

  • Business Intelligence and Data Warehousing

  • The Essential Role of Data Modelling

  • Master and Reference Data Management

  • Metadata Management

 

Learning Outcomes By the end of the course, attendees will:

  • Understand and apply Information Management disciplines for various challenges

  • Explore an Information Management framework and its alignment with other architecture frameworks

  • Learn key concepts such as lifecycle management, normalization, dimensional modelling, and data virtualization

  • Grasp the importance of Master Data Management and Data Governance and how to apply them effectively

  • Learn different MDM architectures and their suitability for various needs

  • Develop practical techniques for information management challenges

  • Understand best practices for managing Enterprise Information needs

  • Apply techniques in information architecture planning through practical examples

Who should attend?

  • Information Managers

  • Information Architects

  • Data Architects

  • Enterprise Architects

  • MDM Managers

  • Data Governance Managers

  • Data Quality Managers

  • Information Quality Practitioners

  • Business Analysts

  • Executives

  • Technology Leaders

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Training Methodology

Our diverse instructional approaches ensure effective learning:

– Lectures & Presentations: Engage with expert-driven, stimulating content.
– Course Material: Access well-crafted supporting resources.
– Group Work: Collaborate on discussions and case studies for practical insights.
– Workshops & Role-Play: Participate in immersive, scenario-based activities.
– Practical Application: Focus on applying theoretical knowledge in real situations.
– Post-Training Support: Receive extensive support after training for skill implementation.

Training Outline

  1. Introduction to the DMBoK

    • Purpose and audience of the DMBoK

    • Changes in DMBoK 2.0 and its relationship with other frameworks (TOGAF / COBIT)

    • Overview of DAMA CDMP

  2. Data Governance

    • Importance of Data Governance

    • Typical Data Governance (DG) reference model

    • DG roles & responsibilities, the role of the Data Governance Office (DGO), and its relationship with the PMO

    • Getting started with Data Governance

  3. Data Quality Management

    • Dimensions of Data Quality

    • Policies, procedures, metrics, technology, and resources for ensuring Data Quality

    • Data Quality reference model

    • Tools to support Data Quality management

  4. Master & Reference Data Management

    • Differences between Reference and Master Data

    • Managing Master Data across the enterprise

    • MDM architectures and their suitability

    • MDM maturity assessment and business procedures

    • Incremental implementation of MDM

  5. Data Warehousing & BI Management

    • Provision of Business Intelligence (BI) and managing data for BI solutions and Data Warehouses

    • Types of BI, DW, and Analytics

  6. Data Modelling & Metadata Management

    • Metadata repositories and business user access

    • Development and use of data models

    • Maturity assessment and integration in the System Development Life Cycle (SDLC)

  7. Data Integration & Architecture Management

    • Business and technology issues addressed by Data Integration

    • Styles of Data Integration and their applicability

    • Approaches and guidelines for Data Integration

    • Consideration of P2P, ETL, CDC, Hub & Spoke, SOA, Data Virtualization

  8. Data Lifecycle Management

    • Planning for Data management across its lifecycle

    • Maturity assessment of Data Lifecycle Management

  9. Data Risk Management, Security & Privacy

    • Identifying threats and defences for data protection

    • Exploration of threat categories, defence mechanisms, and implications of security breaches

    • Risk identification and mitigation

  10. Regulatory Compliance

    • Policies and assurance processes for compliance

    • Adapting to changing legal and regulatory requirements

    • Approaches to regulatory compliance and understanding sanctions

  11. Data Management Tools & Repository

    • Categories of tools supporting Information Management disciplines

    • Selecting appropriate toolsets

    • Example policy for technology use to ensure consistency and interoperability

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