Transferring Data with ETL

Master ETL processes, explore data extraction from MySQL, PostgreSQL, and MongoDB, and learn about scheduling and automating ETL pipelines using tools like Apache Airflow and Python.
4.3
57 Lessons
10h
Updated this week
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ETL stands for extract, transform, and load. It’s a collection of processes that combine data from various sources and load them into data warehouses or other data repositories. ETL is crucial for providing data used for business intelligence and analytics. In this course, you’ll experiment with extracting data from various database solutions such as MySQL, PostgreSQL, and MongoDB. You’ll use query and scripting languages like SQL, Python, and Apache Spark to process data and load it to data repositories or cloud solutions like Google’s GCP. Finally, you’ll learn how to schedule your ETL pipelines using cronjobs or automate and monitor them using open-source tools like Apache Airflow and Python’s pandas library. After completing this course, you’ll have a strong grasp of various methods, tools, and techniques for transferring data from a source to its destination using ETL pipelines.
ETL stands for extract, transform, and load. It’s a collection of processes that combine data from various sources and load them...Show More

WHAT YOU'LL LEARN

An understanding of the extract, transform, and load steps in an ETL pipeline
Hands-on experience implementing and orchestrating the ETL pipelines
Understanding of databases, data warehousing, data processing, and data ingestion
Hands-on experience with ETL tools such as Python, SQL, Apache Spark, and Apache Airflow
An understanding of the extract, transform, and load steps in an ETL pipeline

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Author NameTransferring Data with ETL
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