Module 7: Real-World Applications of Data Engineering
Case studies on scalable architectures Integrating data engineering tools into
Module 6: Ensuring Data Reliability and Quality
Data validation, error handling, and recovery strategies Best practices for
Module 5: Building Scalable Data Pipelines
Principles of building robust and scalable pipelines Optimizing performance and
Module 4: Data Transformation and Processing
Batch processing fundamentals Real-time stream processing principles Data processing tools
Module 3: Data Storage Solutions
Understanding different storage paradigms: Relational vs. Non-relational databases File systems,
Module 2: Data Ingestion and Collection
Techniques for ingesting data from multiple sources Working with APIs,
Module 1: Introduction to Data Engineering
Overview of Data Engineering concepts Data lifecycle and key challenges
