GCP Data Engineer Pro: Creating a Pipeline of Services

Google Cloud 2024    |    Intermediate
  • 13 videos | 1h 11m 59s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 1 users Rating 5.0 of 1 users (1)
Just as landmarks guide you on a journey, the services covered in this course will serve as pivotal markers, steering you through the construction and optimization of robust data pipelines in the expansive landscape of Google Cloud. In this course, you'll uncover the essentials of data pipelines for analysis, learn about Google Cloud's data storage services, and automate data ingestion with Cloud Datastream and Pub/Sub. You'll delve into Hadoop and Hadoop Distributed File System (HDFS), compare Apache Kafka with Google services, and explore use cases for Cloud Data Fusion, Dataproc, Dataflow, and Beam. You'll also analyze BigQuery's role in data analysis and contrast it with MapReduce and Apache Spark, culminating in integrating Google Vertex AI for enhanced data analytics. This course is one of a collection that prepares learners for the Google Professional Data Engineer exam.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Identify the key elements in a data pipeline that will lead to useful analysis of data
    Outline the unstructured, structured, and semi-structured data storage services available on google cloud platform
    Provide an overview of the use of cloud datastream and pub/sub to automate ingestion of data into a pipeline
    Identify how hadoop and hadoop distributed file system (hdfs) fit into a data pipeline
    Compare and contrast apache kafka with google database and messaging services
    Outline the use case for implementing services such as cloud data fusion and cloud dataproc
  • Outline the use case for implementing services such as cloud dataflow or beam to process data
    Compare and contrast apache beam with google batch and stream processing services
    Outline the use case for implementing services such bigquery for supporting analysis
    Compare and contrast mapreduce and apache spark with google bigquery
    Outline how google vertex ai integrates into a data pipeline
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 7s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 7m 37s
    After completing this video, you will be able to identify the key elements in a data pipeline that will lead to useful analysis of data. FREE ACCESS
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    3.  Google Data Storage Services
    8m 11s
    Upon completion of this video, you will be able to outline the unstructured, structured, and semi-structured data storage services available on Google Cloud Platform. FREE ACCESS
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    4.  Google Data Ingestion Services
    5m 55s
    After completing this video, you will be able to provide an overview of the use of Cloud Datastream and Pub/Sub to automate ingestion of data into a pipeline. FREE ACCESS
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    5.  Hadoop and Hadoop Distributed File System (HDFS)
    7m 51s
    Upon completion of this video, you will be able to identify how Hadoop and Hadoop Distributed File System (HDFS) fit into a data pipeline. FREE ACCESS
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    6.  Apache Kafka
    6m 49s
    After completing this video, you will be able to compare and contrast Apache Kafka with Google database and messaging services. FREE ACCESS
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    7.  Google Batch Data Processing
    5m 7s
    Upon completion of this video, you will be able to outline the use case for implementing services such as Cloud Data Fusion and Cloud Dataproc. FREE ACCESS
  • Locked
    8.  Google Streaming Data Processing
    6m 54s
    After completing this video, you will be able to outline the use case for implementing services such as Cloud Dataflow or Beam to process data. FREE ACCESS
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    9.  Apache Beam
    4m 36s
    Upon completion of this video, you will be able to compare and contrast Apache Beam with Google batch and stream processing services. FREE ACCESS
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    10.  Google BigQuery
    6m 41s
    After completing this video, you will be able to outline the use case for implementing services such BigQuery for supporting analysis. FREE ACCESS
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    11.  MapReduce and Apache Spark
    4m 39s
    Upon completion of this video, you will be able to compare and contrast MapReduce and Apache Spark with Google BigQuery. FREE ACCESS
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    12.  Google Vertex AI
    5m 41s
    After completing this video, you will be able to outline how Google Vertex AI integrates into a data pipeline. FREE ACCESS
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    13.  Course Summary
    52s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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