Course Description:

The Data Management course is designed to provide students with a comprehensive understanding of data management principles, techniques, and best practices. The course covers the fundamentals of data management, explores different data storage and retrieval methods, and teaches students how to effectively organize, store, and maintain data. Students will learn about data modeling, database design, data integration, data quality, and data governance. The course also covers emerging trends in data management, such as big data and cloud-based data management.

Course Objectives:

1. Understand the importance of data management in organizations.
2. Learn about different data storage and retrieval methods, including databases and data warehouses.
3. Develop skills in data modeling and database design.
4. Understand the process of data integration and data quality management.
5. Learn about data governance and data security best practices.
6. Explore emerging trends in data management, such as big data and cloud-based data management.
7. Apply data management principles to real-world scenarios and effectively communicate data management strategies.

Course Outline:

Module 1: Introduction to Data Management

– Overview of data management and its importance
– Understanding the role of data management in organizations

Module 2: Data Modeling and Database Design

– Entity-Relationship (ER) modeling
– Relational database design
– Normalization techniques
– Indexing and query optimization

Module 3: Data Storage and Retrieval Methods

– Relational databases (e.g., SQL databases)
– NoSQL databases (e.g., document databases, key-value stores)
– Data warehouses and OLAP (Online Analytical Processing)

Module 4: Data Integration and ETL (Extract, Transform, Load)

– Techniques for integrating data from multiple sources
– Data transformation and cleansing
– ETL tools and processes

Module 5: Data Quality Management

– Understanding data quality dimensions
– Data profiling and data cleansing techniques
– Data quality assessment and monitoring

Module 6: Data Governance and Data Security

– Data governance frameworks and best practices
– Data privacy and compliance
– Data security and access control

Module 7: Big Data Management

– Introduction to big data and its challenges
– Hadoop and MapReduce
– Distributed file systems (e.g., HDFS)
– NoSQL databases for big data (e.g., Apache Cassandra, MongoDB)

Module 8: Cloud-Based Data Management

– Cloud computing and its impact on data management
– Cloud-based databases and data storage options
– Data integration and migration in the cloud

Module 9: Data Management for Business Intelligence

– Data warehousing and data mart design
– Online Analytical Processing (OLAP) and data cubes
– Data visualization and reporting

Module 10: Real-World Applications and Projects

– Applying data management principles to real-world scenarios and projects
– Hands-on projects and simulations to reinforce learning