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Building Batch Data Pipelines on Google Cloud Training Course |...

  • CMDBID 1080
  • Course Code GCPBDP
  • Duration 1 Days
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Overview

Building Batch Data Pipelines on Google Cloudis a practical training course for teams that need structured, instructor-led skills in Building Batch Data Pipelines, Google Cloud Introduction, This. CourseMonster has rewritten this summary to make the page clearer for learners, managers and search engines while preserving the key learning outcomes.

Data pipelines typically fall under one of the Extra-Load, Extract-Load-Transform or Extract-Transform-Load paradigms. This course describes which paradigm should be used and when for batch data. Furthermore, this course covers several technologies on Google Cloud for data transformation including BigQuery, executing Spark on Dataproc, pipeline graphs in Cloud Data Fusion and serverless data processing with Dataflow. Learners will get hands-on experience building data pipeline components on Google Cloud using Qwiklabs.

. Explore more Cloud traininghere

Useful links: Google Cloud training | Project Management training at CourseMonster | CourseMonster course page

CourseMonster SEO course note: Building Batch Data Pipelines on Google Cloud Training Course | CourseMonster has been positioned as a practical Google Cloud learning pathway for teams that need searchable, role-based training outcomes rather than a generic course description. The page now highlights Building, Batch, Data, Pipelines, Google, certification readiness, workplace application and visible next-step links so learners can compare this course with related CourseMonster programmes.The course is listed as 1 day(s), making it suitable for structured team scheduling.It is especially relevant for it professionals, system administrators, developers, analysts, architects and technical specialists responsible for implementing or supporting the technology covered in this course.

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Audience

IT professionals, system administrators, developers, analysts, architects and technical specialists responsible for implementing or supporting the technology covered in this course.

Skills Gained

By completing the Building Batch Data Pipelines on Google Cloud GCPBDP course participants will gain practical knowledge, configuration skills, implementation techniques and best practice understanding relevant to real enterprise environments.

Useful links: Google Cloud training | Project Management training at CourseMonster | CourseMonster course page

Additional workplace outcomes: Participants can explain where Building Batch Data Pipelines on Google Cloud Training Course | CourseMonster fits in a wider Google Cloud skills roadmap, identify related certifications or follow-on courses, and apply the concepts to real project, operations or service delivery scenarios.

Prerequisites

Participants should have basic familiarity with the technology area related to Building Batch Data Pipelines on Google Cloud GCPBDP. Some courses may recommend prior experience or foundational training.

Outline

Introduction to Building Batch Data Pipelines

This module reviews different methods of data loading: EL, ELT and ETL and when to use what

  • Module introduction
  • EL, ELT, ETL
  • Quality considerations
  • How to carry out operations in BigQuery
  • Shortcomings
  • ETL to solve data quality issues
  • QUIZ
  • Introduction to Building Batch Data Pipelines

Executing Spark on Dataproc

This module shows how to run Hadoop on Dataproc, how to leverage Cloud Storage, and how to optimize your Dataproc jobs.

  • Module introduction
  • The Hadoop ecosystem
  • Running Hadoop on Dataproc
  • Cloud Storage instead of HDFS
  • Optimizing Dataproc
  • Optimizing Dataproc storage
  • Optimizing Dataproc templates and autoscaling
  • Optimizing Dataproc monitoring
  • Lab Intro: Running Apache Spark jobs on Dataproc
  • LAB: Running Apache Spark jobs on Cloud Dataproc: This lab focuses on running Apache Spark jobs on Cloud Dataproc.
  • Summary
  • QUIZ

Serverless Data Processing with Dataflow

This module covers using Dataflow to build your data processing pipelines

  • Module introduction
  • Introduction to Dataflow
  • Why customers value Dataflow
  • Building Dataflow pipelines in code
  • Key considerations with designing pipelines
  • Transforming data with PTransforms
  • Lab Intro: Building a Simple Dataflow Pipeline
  • LAB: A Simple Dataflow Pipeline (Python) 2.5: In this lab, you learn how to write a simple Dataflow pipeline and run it both locally and on the cloud.
  • LAB: Serverless Data Analysis with Dataflow: A Simple Dataflow Pipeline (Java): In this lab you will open a Dataflow project, use pipeline filtering, and execute the pipeline locally and on the cloud using Java.
  • Aggregate with GroupByKey and Combine
  • Lab Intro: MapReduce in Beam
  • LAB: MapReduce in Beam (Python) 2.5: In this lab, you learn how to use pipeline options and carry out Map and Reduce operations in Dataflow.
  • LAB: Serverless Data Analysis with Beam: MapReduce in Beam (Java): In this lab you will identify Map and Reduce operations, execute the pipeline, use command line parameters.
  • Side inputs and windows of data
  • Lab Intro: Practicing Pipeline Side Inputs
  • LAB: Serverless Data Analysis with Dataflow: Side Inputs (Python): In this lab you will try out a BigQuery query, explore the pipeline code, and execute the pipeline using Python.
  • LAB: Serverless Data Analysis with Dataflow: Side Inputs (Java): In this lab you will try out a BigQuery query, explore the pipeline code, and execute the pipeline using Java.
  • Creating and re-using pipeline templates
  • Summary
  • QUIZ

Manage Data Pipelines with Cloud Data Fusion and Cloud Composer

This module shows how to manage data pipelines with Cloud Data Fusion and Cloud Composer.

  • Module introduction
  • Introduction to Cloud Data Fusion
  • Components of Cloud Data Fusion
  • Cloud Data Fusion UI
  • Build a pipeline
  • Explore data using wrangler
  • Lab Intro: Building and executing a pipeline graph in Cloud Data Fusion
  • LAB: Building and Executing a Pipeline Graph with Data Fusion 2.5: This tutorial shows you how to use the Wrangler and Data Pipeline features in Cloud Data Fusion to clean, transform, and process taxi trip data for further analysis.
  • Orchestrate work between Google Cloud services with Cloud Composer
  • Apache Airflow environment
  • DAGs and Operators
  • Workflow scheduling
  • Monitoring and Logging
  • Lab Intro: An Introduction to Cloud Composer
  • LAB: An Introduction to Cloud Composer 2.5: In this lab, you create a Cloud Composer environment using the GCP Console. You then use the Airflow web interface to run a workflow that verifies a data file, creates and runs an Apache Hadoop wordcount job on a Dataproc cluster, and deletes the cluster.
  • QUIZ

. Explore more Cloud traininghere

Useful links: Google Cloud training | Project Management training at CourseMonster | CourseMonster course page

Suggested learning path: After this course, compare related options via the links in the overview and the Google Cloud training category.

Certification

Exam and certification details

This course may support a vendor exam, digital badge or professional certification depending on the selected delivery option. Delegates should confirm exam inclusion, voucher availability, prerequisites, pass mark and version before booking.

Official vendor training information: Google Cloud training.

Is Building Batch Data Pipelines on Google Cloud GCPBDP right for me?

This course is for learners who want structured, expert-led training in professional development with practical workplace outcomes.

What will I learn on Building Batch Data Pipelines on Google Cloud GCPBDP?

You will build practical professional development skills, understand key concepts and apply the course outcomes in real workplace scenarios.

Does Building Batch Data Pipelines on Google Cloud GCPBDP include exam preparation?

Yes, this course supports certification or exam preparation where included in the selected delivery option.

What should I do after Building Batch Data Pipelines on Google Cloud GCPBDP?

Compare related CourseMonster courses and follow-on pathways to choose the best next step for your role or team.

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If you need training for 3 or more people, you should ask us about onsite training. Putting aside the obvious location benefit, content can be customised to better meet your business objectives and more can be covered than in a public classroom. Its a cost effective option. One on one training can be delivered too, at reasonable rates.

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