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.
Ofrecido Por


Acerca de este Curso
Computer and IT literacy.
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Prueba Coursera para negociosQué aprenderás
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 obtendrás
- Extraction, Transformation And Loading (ETL)
- Apache Kafka
- Apache Airflow
- Data Pipelines
Computer and IT literacy.
¿Podría tu empresa beneficiarse de la capacitación de los empleados en las habilidades más demandadas?
Prueba Coursera para negociosOfrecido por
Programa - Qué aprenderás en este curso
Data Processing Techniques
ETL & Data Pipelines: Tools and Techniques
Building Data Pipelines using Airflow
Building Streaming Pipelines using Kafka
Reseñas
- 5 stars65,78 %
- 4 stars21,71 %
- 3 stars5,26 %
- 2 stars4,60 %
- 1 star2,63 %
Principales reseñas sobre ETL AND DATA PIPELINES WITH SHELL, AIRFLOW AND KAFKA
It takes 1 hour to connect the lab and start the service.
Great Course, Assignments prepare really well and flexible
Succinctly presented. Labs really hammered the point home :)
Course Is Good but, if you can add some more practicles that will surely help understand better and help all learner grasp things very quickly.
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