Module #1 Introduction to Data Pipelines Overview of data pipelines, their importance, and benefits
Module #2 Data Pipeline Fundamentals Key concepts, components, and architecture of data pipelines
Module #3 Data Ingestion Methods Overview of data ingestion methods, including batch, streaming, and event-driven approaches
Module #4 Data Sources and Targets Introduction to common data sources and targets, including databases, files, and APIs
Module #5 Data Pipeline Design Principles Best practices for designing scalable, reliable, and maintainable data pipelines
Module #6 Pipeline Architecture Patterns Common pipeline architecture patterns, including Extract-Transform-Load (ETL) and Extract-Load-Transform (ELT)
Module #7 Data Quality and Data Profiling Importance of data quality and data profiling in data pipeline design
Module #8 Data Transformation and Enrichment Techniques for data transformation, enrichment, and data standardization
Module #9 Data Storage and Warehousing Overview of data storage and warehousing options, including relational databases and data lakes
Module #10 Data Visualization and Reporting Introduction to data visualization and reporting tools and techniques
Module #11 Big Data and NoSQL Technologies Introduction to big data and NoSQL technologies, including Hadoop, Spark, and MongoDB
Module #12 Cloud-Based Data Pipelines Designing and implementing data pipelines on cloud-based infrastructure, including AWS, Azure, and GCP
Module #13 Data Pipeline Security and Governance Importance of security and governance in data pipeline design and implementation
Module #14 Monitoring and Logging Monitoring and logging techniques for data pipelines, including metrics and logging frameworks
Module #15 Error Handling and Debugging Techniques for error handling and debugging in data pipelines
Module #16 Data Pipeline Automation and Orchestration Introduction to automation and orchestration tools, including Apache Airflow and Zapier
Module #17 Real-Time Data Pipelines Designing and implementing real-time data pipelines for streaming data
Module #18 Data Pipeline Optimization and Tuning Techniques for optimizing and tuning data pipeline performance
Module #19 Data Pipeline Migration and Upgrades Best practices for migrating and upgrading data pipelines
Module #20 Case Studies and Real-World Examples Real-world examples and case studies of data pipeline design and implementation
Module #21 Data Pipeline Tools and Technologies Overview of popular data pipeline tools and technologies, including Fivetran, Stitch, and Talend
Module #22 Data Pipeline Best Practices and Anti-Patterns Best practices and common pitfalls to avoid in data pipeline design and implementation
Module #23 Data Governance and Compliance Importance of data governance and compliance in data pipeline design and implementation
Module #24 Data Quality and Data Validation Techniques for data quality and data validation in data pipelines
Module #25 Data Lineage and Provenance Importance of data lineage and provenance in data pipeline design and implementation
Module #26 Data Pipeline Scalability and Performance Techniques for designing scalable and high-performance data pipelines
Module #27 Data Pipeline Cost Optimization Best practices for optimizing data pipeline costs and ROI
Module #28 Data Pipeline ROI and Metrics Measuring the ROI and metrics of data pipelines
Module #29 Data Pipeline Team Management and Collaboration Best practices for managing and collaborating on data pipeline teams
Module #30 Course Wrap-Up & Conclusion Planning next steps in Data Pipeline Design and Implementation career
