Data Management

Course Outline

Introduction to Data Management

• Fundamental concepts: data models, data independence (physical and logical), the query optimizer
• Information storage and retrieval
• Data management cycle
• Data management process

Database Management Systems

• Types of DBMS: relational, hierarchical
• DBMS architecture
• Application of DBMS in different sectors
• Data Abstraction
• ER Model

Developing Data Management Strategy

• Identifying key business objectives
• Creating data processes for collecting, storing, preparing data
• Identifying the right tools and technologies

Data Integration

• Data warehousing
• Data migration
• Data integration techniques: manual integration, application-based integration, virtual integration
• Data integration in data mining

Master Data Management

• What are MDM and its benefits to the organization?
• Essential MDM capabilities
• Common MDM sources
• MDM use in improved customer service, personalized marketing, etc.

Data Governance

• Goals of data governance
• Breaking data silos
• Components of the data governance framework
• Data stewardship

Challenges and risks to Data management

• Combating flawed data
• Lack of data insight
• Balancing data management and transparency
• Keeping up-to-date with regulatory compliances
• Handling versatile data with varied standard

Data security and regulatory compliance

• Data encryption
• Tokenization
• Access control, Authentication, backups, and recovery
• Data erasure
• Data masking
• Main elements of data security
• Data regulatory compliance

Innovation in Data Management

• Cloud data governance
• Case study: world’s first self-driving database

Data Management Best Practices and latest trends

• Artificial intelligence automates data
• Augmented data management
• Data post
• Data Fabric