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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À propos de ce cours
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.
Compétences que vous acquerrez
- Extraction, Transformation And Loading (ETL)
- Apache Kafka
- Apache Airflow
- Data Pipelines
Computer and IT literacy.
Votre entreprise pourrait-elle bénéficier de la formation des employés à des compétences recherchées ?
Essayez Coursera pour les affairesOffert par
Programme de cours : ce que vous apprendrez dans ce cours
Data Processing Techniques
ETL & Data Pipelines: Tools and Techniques
Building Data Pipelines using Airflow
Building Streaming Pipelines using Kafka
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- 5 stars65,58 %
- 4 stars22,07 %
- 3 stars5,19 %
- 2 stars4,54 %
- 1 star2,59 %
Meilleurs avis pour ETL AND DATA PIPELINES WITH SHELL, AIRFLOW AND KAFKA
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.
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.
Excellent introduction to this topics. Labs contain all you need to know how to start using this type of technologies. Highly recommended.
Very useful high-level overview with practical examples of the major technologies that drive modern data pipelines.
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