Data Engineering

  1. Advanced Data Engineering Topics
    1. Real-Time Analytics Architecture
      1. Lambda Architecture
        1. Batch Layer Processing
          1. Speed Layer Processing
            1. Serving Layer Integration
            2. Kappa Architecture
              1. Stream-Only Processing
                1. Event Sourcing Patterns
                  1. Simplified Architecture Benefits
                  2. Real-Time Analytics Use Cases
                    1. Fraud Detection Systems
                      1. Recommendation Engines
                        1. IoT Data Processing
                          1. Financial Trading Systems
                        2. Machine Learning Operations
                          1. MLOps Principles
                            1. Model Development Lifecycle
                              1. Continuous Integration for ML
                                1. Model Versioning
                                  1. Automated Testing for ML
                                  2. Feature Engineering Infrastructure
                                    1. Feature Store Architecture
                                      1. Feature Pipeline Development
                                        1. Feature Versioning and Lineage
                                          1. Feature Serving Systems
                                          2. Model Deployment Patterns
                                            1. Batch Prediction Pipelines
                                              1. Real-Time Model Serving
                                                1. A/B Testing for Models
                                                  1. Model Performance Monitoring
                                                  2. Model Lifecycle Management
                                                    1. Model Training Automation
                                                      1. Model Validation Frameworks
                                                        1. Model Retraining Strategies
                                                          1. Model Retirement Processes
                                                        2. Serverless Data Processing
                                                          1. Serverless Architecture Principles
                                                            1. Event-Driven Processing
                                                              1. Auto-Scaling Capabilities
                                                                1. Pay-Per-Use Pricing
                                                                  1. Reduced Operational Overhead
                                                                  2. Serverless Data Processing Patterns
                                                                    1. Function-as-a-Service for ETL
                                                                      1. Event-Triggered Data Processing
                                                                        1. Serverless Data Pipelines
                                                                        2. Cost Optimization Strategies
                                                                          1. Function Execution Optimization
                                                                            1. Cold Start Minimization
                                                                              1. Resource Right-Sizing
                                                                                1. Usage Pattern Analysis
                                                                              2. Graph Data Processing
                                                                                1. Graph Data Models
                                                                                  1. Property Graph Model
                                                                                    1. RDF Triple Store Model
                                                                                      1. Graph Schema Design
                                                                                      2. Graph Query Languages
                                                                                        1. Cypher Query Language
                                                                                          1. SPARQL for RDF
                                                                                            1. Gremlin Traversal Language
                                                                                            2. Graph Processing Frameworks
                                                                                              1. Apache Spark GraphX
                                                                                                1. Neo4j Graph Database
                                                                                                  1. Amazon Neptune
                                                                                                    1. Graph Analytics Algorithms
                                                                                                    2. Graph Use Cases
                                                                                                      1. Social Network Analysis
                                                                                                        1. Fraud Detection Networks
                                                                                                          1. Knowledge Graphs
                                                                                                            1. Supply Chain Optimization

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                                                                                                        12. Data Governance, Quality, and Security

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                                                                                                        1. Introduction to Data Engineering