Data pipelines are essential for managing and transforming large volumes of data efficiently. In the "Building Batch Data Pipelines on Google Cloud" course, offered by Google Cloud, you will explore various paradigms such as Extra-Load, Extract-Load-Transform, and Extract-Transform-Load for batch data processing. This comprehensive course delves into the different methods of data loading and when to utilize each one, enabling you to make informed decisions when building batch data pipelines.
Throughout the course, you will gain practical insights into running Hadoop on Dataproc, leveraging Cloud Storage, and optimizing Dataproc jobs. Additionally, you will learn to build data processing pipelines using Dataflow and manage data pipelines with Data Fusion and Cloud Composer. The hands-on experience provided by Qwiklabs allows you to develop expertise in building data pipeline components on Google Cloud.
This course is designed to provide a comprehensive understanding of building batch data pipelines on Google Cloud, empowering you to effectively manage and transform data at scale.
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This course covers a comprehensive range of topics including data loading paradigms, running Hadoop on Dataproc, building data processing pipelines using Dataflow, and managing data pipelines with Data Fusion and Cloud Composer. Gain practical insights and hands-on experience in building batch data pipelines on Google Cloud.
Course Introduction provides an overview of the modules and sets the stage for the comprehensive learning journey ahead.
Gain insights into the paradigms of Extra-Load, Extract-Load-Transform, and Extract-Transform-Load for batch data processing. Understand the different methods of data loading and when to use EL, ELT, or ETL. Explore the quality considerations and shortcomings of these methods.
Understand the Hadoop ecosystem and learn to run Hadoop on Dataproc, leveraging Cloud Storage, and optimizing Dataproc jobs. Gain practical experience in executing Spark on Dataproc through hands-on labs provided by Qwiklabs.
Get introduced to Dataflow and understand why customers value it. Learn to build Dataflow pipelines in code, design pipelines, and transform data using PTransforms. Gain hands-on experience through labs covering various aspects of Dataflow.
Explore Cloud Data Fusion and its components, including the Cloud Data Fusion UI. Learn to build and execute pipeline graphs in Cloud Data Fusion. Additionally, get introduced to Cloud Composer and understand its components, workflow scheduling, and monitoring and logging capabilities.
Course Summary provides a concise recap of the key learnings and takeaways from the entire course, reinforcing the knowledge gained throughout the modules.
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