The Data Management course provides a comprehensive understanding of the principles and practices involved in effectively managing and organizing data. The course covers various aspects of data management, including data storage, data integration, data quality, and data governance. Students will learn how to design and implement data management strategies, leverage database systems, and ensure the integrity and security of data.
- Basic understanding of databases and SQL
- Familiarity with data modeling concepts
- Some programming skills (preferred but not mandatory)
- Curiosity and interest in data management practices
The course adopts a combination of theoretical lectures, hands-on exercises, and practical labs to provide a comprehensive learning experience. The lectures cover the fundamental concepts and methodologies of data management. The hands-on exercises allow students to apply the learned techniques in real-world scenarios, while the labs provide opportunities to work on data management projects. The course encourages critical thinking, problem-solving skills, and an understanding of data governance principles.
Introduction to Data Management
Overview of data management principles and practices
Importance of data quality and data governance
Ethical considerations in data management
Data Modeling and Design
Entity-relationship (ER) modeling and normalization
Conceptual, logical, and physical data models
Design considerations for relational databases
Database Systems and Technologies
Relational database management systems (RDBMS)
NoSQL databases and their use cases
Introduction to cloud-based databases
Data Integration and ETL Processes
Data integration techniques (e.g., extract, transform, load)
Data migration and synchronization
ETL tools and frameworks
Data Quality and Master Data Management
Data quality assessment and improvement strategies
Data profiling and cleansing techniques
Master data management concepts and practices
Data Security and Privacy
Data security principles and best practices
Access control and user authentication
Compliance with data privacy regulations
Data Governance and Metadata Management
Data governance frameworks and practices
Establishing data governance policies and procedures
Metadata management and data lineage
Big Data Management
Introduction to big data and its challenges
Hadoop ecosystem and distributed file systems
Data management techniques for big data analytics
Upon completing the course, students will:
- Understand the fundamental principles, practices, and methodologies of data management.
- Be proficient in data modeling, database systems, and SQL query languages.
- Gain hands-on experience with database management systems and data integration tools.
- Develop skills in ensuring data quality, data security, and data privacy.
- Understand the principles of data governance and metadata management.
- Apply data management techniques to handle structured and unstructured data effectively.
The course includes hands-on labs and projects to reinforce the theoretical concepts and provide practical experience. The labs may include:
- Designing and implementing a relational database schema for a given scenario.
- Writing SQL queries to retrieve and manipulate data from a database.
- Building an ETL pipeline to integrate and transform data from multiple sources.
- Performing data profiling and cleansing tasks on real-world datasets.
- Implementing data security measures (e.g., user authentication, access control) in a database system.
- Designing a data governance framework and establishing data governance policies.