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Build Batch Data Pipelines on Google Cloud

Build Batch Data Pipelines on Google Cloud

magic_button Data Modelling Data Lake Modernization Data Fusion Data Engineer
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9 hours 15 minutes Intermediate

In this intermediate course, you will learn to design, build, and optimize robust batch data pipelines on Google Cloud. Moving beyond fundamental data handling, you will explore large-scale data transformations and efficient workflow orchestration, essential for timely business intelligence and critical reporting.

Get hands-on practice using Dataflow for Apache Beam and Serverless for Apache Spark (Dataproc Serverless) for implementation, and tackle crucial considerations for data quality, monitoring, and alerting to ensure pipeline reliability and operational excellence. A basic knowledge of data warehousing, ETL/ELT, SQL, Python, and Google Cloud concepts is recommended.

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Course Info
Objectives
  • Determine whether batch data pipelines are the correct choice for your business use case.
  • Design and build scalable batch data pipelines for high-volume ingestion and transformation.
  • Implement data quality controls within batch pipelines to ensure data integrity.
  • Orchestrate, manage, and monitor batch data pipeline workflows, implementing error handling and observability using logging and monitoring tools.
Prerequisites

Basic proficiency with Data Warehousing and ETL/ELT concepts

Basic proficiency in SQL

Basic programming knowledge (Python recommended)

Familiarity with gcloud CLI and the Google Cloud console

Familiarity with core Google Cloud concepts and services

Audience
Data Engineers Data Analysts
Available languages
English, español (Latinoamérica), 日本語, français, português (Brasil), italiano ve 한국어
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