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ETL and Data Pipelines with Shell, Airflow and Kafka(으)로 돌아가기

IBM의 ETL and Data Pipelines with Shell, Airflow and Kafka 학습자 리뷰 및 피드백

35개의 평가
8개의 리뷰

강좌 소개

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. Both ETL and ELT extract data from source systems, move the data through the data pipeline, and store the data in destination systems. During this course, you will experience how ELT and ETL processing differ and identify use cases for both. You will identify methods and tools used for extracting the data, merging extracted data either logically or physically, and for importing data into data repositories. You will also define transformations to apply to source data to make the data credible, contextual, and accessible to data users. You will be able to outline some of the multiple methods for loading data into the destination system, verifying data quality, monitoring load failures, and the use of recovery mechanisms in case of failure. Finally, you will complete a shareable final project that enables you to demonstrate the skills you acquired in each module....

최상위 리뷰

필터링 기준:

ETL and Data Pipelines with Shell, Airflow and Kafka의 8개 리뷰 중 1~8

교육 기관: Nataliya S

2021년 10월 12일

Thanks to IBM and Coursera for the great "ETL and Data Pipelines with Shell, Airflow and Kafka" course, that I passed with Grade Achieved: 100%. It's the third course, that I've passed, as a part of "IBM Data Engineering Specialization". I was so carried away by the course that I literally sat up until 2 am almost every day. In this course I could apply my knowledge of Python, Pandas, SQL, Bash commands to build ETL Batch and Stream pipelines.

교육 기관: Evgeny D

2021년 9월 29일

I​t's one of the most challenging courses I've been enrolled!

교육 기관: Dmitry K

2021년 9월 17일

Buggy practice. Not possible to complete without fixing airflow start script yourself. Nobody monitor or fixing issues here

교육 기관: RLee

2022년 1월 13일

The final project to connect Airflow as a pipeline management tool to Kafka server is a very useful hands-on project. More details or explanations on the syntax of Python calling Kafka producer and consumer, which are in the files of and, would be more valuable rather than just providing these two files to run on its own.

교육 기관: Ilya K

2022년 1월 13일

Perfect environment to make experiments! Very easy and powerful in use.

교육 기관: Natale F

2021년 12월 15일

Interesting course with enough labs.

교육 기관: Hugo A O O

2021년 12월 6일

i really liked the labs


2022년 1월 17일

Love the labs, but do not like the robotic lectures.