Data Engineering

  1. Data Pipeline Architecture and Orchestration
    1. Pipeline Design Patterns
      1. Data Ingestion Patterns
        1. Batch Ingestion Workflows
          1. Real-Time Ingestion Streams
            1. Hybrid Ingestion Approaches
              1. Change Data Capture Implementation
              2. Data Processing Patterns
                1. Linear Processing Pipelines
                  1. Fan-Out Processing Patterns
                    1. Fan-In Aggregation Patterns
                      1. Lambda Architecture
                        1. Kappa Architecture
                        2. Data Quality Patterns
                          1. Data Validation Rules
                            1. Data Profiling Integration
                              1. Anomaly Detection Workflows
                                1. Data Lineage Tracking
                              2. Pipeline Orchestration Concepts
                                1. Directed Acyclic Graphs
                                  1. Task Dependency Modeling
                                    1. Parallel Execution Paths
                                      1. Critical Path Analysis
                                      2. Scheduling Strategies
                                        1. Time-Based Scheduling
                                          1. Event-Driven Triggers
                                            1. Dependency-Based Execution
                                              1. Resource-Aware Scheduling
                                              2. Error Handling and Recovery
                                                1. Retry Mechanisms
                                                  1. Circuit Breaker Patterns
                                                    1. Dead Letter Queues
                                                      1. Rollback Strategies
                                                    2. Apache Airflow
                                                      1. DAG Development
                                                        1. Python-Based DAG Definition
                                                          1. Task Operators
                                                            1. Task Dependencies
                                                              1. Dynamic DAG Generation
                                                              2. Airflow Components
                                                                1. Scheduler Service
                                                                  1. Executor Types
                                                                    1. Web Server Interface
                                                                      1. Metadata Database
                                                                      2. Monitoring and Operations
                                                                        1. Task Instance Monitoring
                                                                          1. Log Management
                                                                            1. Alert Configuration
                                                                              1. Performance Metrics
                                                                            2. Alternative Orchestration Tools
                                                                              1. Prefect Framework
                                                                                1. Flow and Task Concepts
                                                                                  1. Functional API Design
                                                                                    1. Cloud Execution Options
                                                                                    2. Dagster Platform
                                                                                      1. Software-Defined Assets
                                                                                        1. Type System Integration
                                                                                          1. Data Quality Testing
                                                                                          2. Tool Selection Criteria
                                                                                            1. Ease of Development
                                                                                              1. Operational Requirements
                                                                                                1. Scalability Needs
                                                                                                  1. Community and Support

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                                                                                              8. Stream Processing and Real-Time Data

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                                                                                              10. Cloud Data Engineering Platforms