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

IBM 기술 네트워크의 ETL and Data Pipelines with Shell, Airflow and Kafka 학습자 리뷰 및 피드백

4.5
별점
114개의 평가

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

DS

2022년 6월 13일

Excellent introduction to this topics. Labs contain all you need to know how to start using this type of technologies. Highly recommended.

MA

2022년 6월 9일

Thanks to all the instructor's efforts, one of the best DATA engineering courses, contains hands-on Experience with essential data tools.

필터링 기준:

ETL and Data Pipelines with Shell, Airflow and Kafka의 34개 리뷰 중 26~34

교육 기관: otto z

2022년 6월 22일

교육 기관: Mbaye B

2022년 5월 14일

교육 기관: Krishnakumar K

2022년 4월 12일

교육 기관: Yao G A

2022년 2월 25일

교육 기관: Santiago Z A

2022년 9월 15일

교육 기관: Roberta B

2022년 4월 3일

교육 기관: Tal M

2022년 7월 17일

교육 기관: Benjamin A A

2022년 8월 20일

교육 기관: BO W

2022년 7월 8일