Description
Course Description:
– Introduction to Data Pipelines: Learn the fundamentals of data pipelines, including their purpose, components, and architecture for processing and transferring data from sources to destinations.
– Data Pipeline Design:Explore best practices for designing efficient and scalable data pipelines, covering topics such as data ingestion, transformation, and loading (ETL).
– Tools and Technologies: Gain hands-on experience with popular data pipeline tools and platforms like Apache Kafka, Apache Airflow, Apache Nifi, and AWS Glue.
– Data Integration and Transformation: Understand techniques for integrating disparate data sources, transforming data into useful formats, and managing data quality.
– Real-Time vs Batch Processing: Compare and contrast real-time (streaming) and batch processing approaches, and learn how to implement both types of pipelines effectively.
– Monitoring and Maintenance:Learn how to monitor data pipelines, handle errors and failures, and ensure data integrity and performance optimization.
– Security and Compliance:Address data security concerns, implement access controls, and ensure compliance with data governance and regulatory requirements.Course Duration:
– 6 Weeks (3 hours/week) or Intensive 3-Week Program (6 hours/day)Prerequisites:
– Basic knowledge of data concepts and databases
– Familiarity with programming or scripting languages (e.g., Python, SQL)Learning Resources:
– Online tutorials and documentation for pipeline tools
– Hands-on labs and real-world case studies
– Access to data pipeline platforms and servicesAssessment:
– Quizzes and hands-on assignments
– Final project demonstrating the design and implementation of a data pipeline
– Introduction to Data Pipelines: Learn the fundamentals of data pipelines, including their purpose, components, and architecture for processing and transferring data from sources to destinations.
– Data Pipeline Design:Explore best practices for designing efficient and scalable data pipelines, covering topics such as data ingestion, transformation, and loading (ETL).
– Tools and Technologies: Gain hands-on experience with popular data pipeline tools and platforms like Apache Kafka, Apache Airflow, Apache Nifi, and AWS Glue.
– Data Integration and Transformation: Understand techniques for integrating disparate data sources, transforming data into useful formats, and managing data quality.
– Real-Time vs Batch Processing: Compare and contrast real-time (streaming) and batch processing approaches, and learn how to implement both types of pipelines effectively.
– Monitoring and Maintenance:Learn how to monitor data pipelines, handle errors and failures, and ensure data integrity and performance optimization.
– Security and Compliance:Address data security concerns, implement access controls, and ensure compliance with data governance and regulatory requirements.Course Duration:
– 6 Weeks (3 hours/week) or Intensive 3-Week Program (6 hours/day)Prerequisites:
– Basic knowledge of data concepts and databases
– Familiarity with programming or scripting languages (e.g., Python, SQL)Learning Resources:
– Online tutorials and documentation for pipeline tools
– Hands-on labs and real-world case studies
– Access to data pipeline platforms and servicesAssessment:
– Quizzes and hands-on assignments
– Final project demonstrating the design and implementation of a data pipeline
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