Data Engineering: Pipelines, ETL, Hadoop
Completed by Valerija Kijaskina
May 19, 2026
3 hours (approximately)
Valerija Kijaskina's account is verified. Coursera certifies their successful completion of Data Engineering: Pipelines, ETL, Hadoop
What you will learn
Analyse the architecture and components of data pipelines to understand their impact on data flow and processing efficiency.
Implement robust ETL processes, for scalability and maintainability.
Analyze big data challenges and introduce Hadoop ecosystem tools (HDFS, MapReduce, Hive, Pig, and Spark) for data processing tasks.
Skills you will gain
- Category: Apache Hive
- Category: Extract, Transform, Load
- Category: Data Warehousing
- Category: Scalability
- Category: Data-Driven Decision-Making
- Category: Data Architecture
- Category: Data Processing
- Category: Data Management
- Category: Dataflow
- Category: Big Data
- Category: Data Pipelines
- Category: Apache Spark
