Apache Spark Essential Training: Big Data Engineering (2024)
Apache Spark Essential Training: Big Data Engineering (2024)
![Apache Spark Essential Training: Big Data Engineering (2024)]()
Data engineering is the foundation for building analytics and data science applications in the new Big Data world. Data engineering requires combining multiple big data technologies to construct data pipelines and networks to stream, process, and store data. This course focuses on building full-fledged solutions that combine Apache Spark with other big data tools to create end-to-end data pipelines. Instructor Kumaran Ponnambalam begins by defining data engineering, its functions, and its concepts. Next, Kumaran goes over how Spark capabilities such as parallel processing, execution plans, state management options, and machine learning work with extract, transform, load (ETL). He introduces you to batch processing use cases and processes, as well as real-time processing pipelines. After taking you through several useful best practices, Kumaran concludes with an end-to-end exercise project.
Homepage:
![Apache Spark Essential Training: Big Data Engineering (2024)]()
rapidgator.net:
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Released: 10/2024
Duration: 1h 4m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 146 MB
Level: Intermediate | Genre: eLearning | Language: English
Duration: 1h 4m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 146 MB
Level: Intermediate | Genre: eLearning | Language: English
Data engineering is the foundation for building analytics and data science applications in the new Big Data world. Data engineering requires combining multiple big data technologies to construct data pipelines and networks to stream, process, and store data. This course focuses on building full-fledged solutions that combine Apache Spark with other big data tools to create end-to-end data pipelines. Instructor Kumaran Ponnambalam begins by defining data engineering, its functions, and its concepts. Next, Kumaran goes over how Spark capabilities such as parallel processing, execution plans, state management options, and machine learning work with extract, transform, load (ETL). He introduces you to batch processing use cases and processes, as well as real-time processing pipelines. After taking you through several useful best practices, Kumaran concludes with an end-to-end exercise project.
Homepage:
https://www.linkedin.com/learning/apache-spark-essential-training-big-data-engineering-23165395?u=121350530Screenshots
rapidgator.net:
ddownload.com: