Manage Information and Data

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 organisation?

● Essential MDM capabilities

● Common MDM sources

● MDM use in improved customer service, personalized marketing, etc.

 Data Governance

● Why data governance matters

● 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

● Types of data security: 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