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.阅读更多.
此资源由附属合作伙伴提供。 如果您支付培训费用，我们可能会赚取佣金来支持该网站。
ETL and Data Pipelines with Shell, Airflow and Kafka 中涵盖的技术和工具与 数据工程师 招聘广告中的要求最为相似。
ETL and Data Pipelines with Shell, Airflow and Kafka is a part of 一 structured learning path.
13 Courses
15 Months
IBM Data Engineering Professional Certificate
