Big Data Modeling and Management Systems Course Syllabus
Full curriculum breakdown — modules, lessons, estimated time, and outcomes.
Overview (80-120 words) describing structure and time commitment.
Module 1: Introduction to Big Data and Data Models
Estimated time: 1 hour
- Overview of big data challenges and terminology
- Understanding data ingestion and scalability
- Introduction to data modeling in large-scale systems
- Role of data models in modern data platforms
Module 2: Foundational Data Modeling
Estimated time: 2 hours
- Structure of relational databases
- Working with semi-structured data formats (CSV, JSON)
- Schema design principles
- Data organization for scalability
Module 3: Advanced Modeling Approaches
Estimated time: 2 hours
- Introduction to vector space models
- Graph-based data structures
- Using Lucene for text data modeling
- Network data visualization with Gephi
Module 4: Streaming Data and Real-Time Systems
Estimated time: 1.5 hours
- Modeling and processing streaming data
- Techniques for real-time data handling
- Introduction to data lakes and flexible storage
Module 5: Big Data Management Technologies
Estimated time: 1.5 hours
- Comparison of traditional DBMS vs. big data platforms
- Hands-on with Vertica and AsterixDB
- Exploration of Impala, Neo4j, Redis, and SparkSQL
Module 6: Final Project
Estimated time: 1 hour
- Design a data management system for an online gaming platform
- Apply data modeling concepts across structured and semi-structured formats
- Integrate streaming and storage solutions
Prerequisites
- Familiarity with basic database concepts
- Basic understanding of data structures
- Some prior exposure to SQL or data querying helpful
What You'll Be Able to Do After
- Design scalable data systems for big data environments
- Apply relational, semi-structured, and graph data models
- Use modern big data platforms like AsterixDB and Neo4j
- Model and manage real-time and streaming data workflows
- Build data architectures for real-world applications such as online gaming