Course and Data Management Introduction

• Data Management Maturity Self-evaluation exercise
• Data is or not the new Oil?
• Introduction to DAMA DMBOK2 Framework (DAMA Wheel, Environmental Factors Exagon and Context Diagram)
• Other Data Management Framework
• Reasons why Data is an asset with singular characteristics

Data Governance, Data Ethics and Data Roles and Responsabilities

• What is Data Governance and Why it is important
• Data Governance Bodies and Committees
• Design and Implement Data Governance Activities
• Typical Data Management Roles and Responsibilities
• Building a Data Management Organization
• What does Data Handling Ethics means? Principles and Risks

Data Architecture and Modeling

• What is the role of Data Domain in Enteprise Architecture?
• Zachman Framework
• What is a Data Model and why it is important
• Data Model Components, learning to read and understand a Data Model
• Different schemes and levels of detail of a Data Model

Data Storage and Operations, Content and Document Management

• Data Storage and Operation definitions and principles
• Types of Database Environments
• Database Administrators
• Different types of database organizations and Data Processing Managing Unstructured Data, Document and Contents
• Records Management and Regulatory requirements

Data Security, Integration and Interoperaibility

• Data Security Goals and Business Drivers
• Secure Data at Rest and Network Security Data Security Risks Data Integration, how data are consolidated within applications
• Data Interoperability principles, techniques and method ETL vs ELT, preparing Data Warehouse or Data Lakes

Data Warehouse , Business Intelligence , Big Data and Data Science

• What is Data Warehouse, different approaches and techniques answering different business needs
• Developing Business Intelligence to enable data driven decisions
• What is Data Science and why do we need it
• Big Data Architecture and difference between Data Warehousing
• Classic reasons of failure of Big Data Initiatives

Data Quality

• What is Data Quality and why it is important for business
• Data Quality risks and how to face them
• Developing Data Quality Metrics and Indicators
• Monitor And Control Data Quality
• Manage Data Quality Rules, Data Quality Improvement Lifecycle and Data Quality Issues

Metadata, Master and Reference Data Management

• What is Metadata, Reference Data, Master Data
• The key role of a Metadata Repository, opportunities and business use
• Metadata Architecture
• Categories of Reference Data and Master Data
• System of Records, Trusted Source and Golden Records