After taking this course, you will be able to describe two different approaches to converting raw data into analytics-ready data. One approach is the Extract, Transform, Load (ETL) process. The other contrasting approach is the Extract, Load, and Transform (ELT) process. ETL processes apply to data warehouses and data marts. ELT processes apply to data lakes, where the data is transformed on demand by the requesting/calling application.
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Informações sobre o curso
Computer and IT literacy.
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Describe and contrast Extract, Transform, Load (ETL) processes and Extract, Load, Transform (ELT) processes.
Explain batch vs concurrent modes of execution.
Implement an ETL pipelinethrough shell scripting.
Describe data pipeline components, processes, tools, and technologies.
Habilidades que você terá
- Extraction, Transformation And Loading (ETL)
- Apache Kafka
- Apache Airflow
- Data Pipelines
Computer and IT literacy.
Sua empresa se beneficiaria do treinamento dos funcionários em habilidades sob demanda?
Experimente o Coursera for Businessoferecido por
Programa - O que você aprenderá com este curso
Data Processing Techniques
ETL & Data Pipelines: Tools and Techniques
Building Data Pipelines using Airflow
Building Streaming Pipelines using Kafka
Avaliações
- 5 stars65,35%
- 4 stars22,22%
- 3 stars5,22%
- 2 stars4,57%
- 1 star2,61%
Principais avaliações do ETL AND DATA PIPELINES WITH SHELL, AIRFLOW AND KAFKA
Love the labs, but do not like the robotic lectures.
Thanks to all the instructor's efforts, one of the best DATA engineering courses, contains hands-on Experience with essential data tools.
Nice intro to ETL and Data Pipelines. Beginner level easy to follow hands on Airflow and Kafka.
It's great introduction for airflow and kafka but still an introduction it is shallow doesn't offer much but at the end you will understand what you need to continue further in both technologies.
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