GCP Data Engineer Pro: Building Robust Data Structures

Google Cloud 2024    |    Intermediate
  • 14 videos | 1h 23m 47s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 2 users Rating 5.0 of 2 users (2)
Just as architects draft blueprints to create resilient structures, you'll learn to design robust data storage solutions, ensuring your data's integrity and accessibility. This course lays the cornerstone for building a comprehensive understanding of Google Cloud Platform's (GCP) data services, equipping you with the skills to erect a formidable edifice of knowledge in the cloud computing landscape. In this course you will explore the world of GCP's data management, covering everything from storage architectures to data lake best practices. You'll learn to choose and manage storage services, design data models for warehouses, and normalize data. Next, you will discover how data access shapes warehouse architecture, explore GCP data lakes, and master cost control and access best practices. Finally, you will gain proficiency in data processing, monitoring on GCP, and constructing a data mesh with robust governance. 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 differences between a data warehouse, a data lake, and a data mesh
    Outline the process of defining a data warehouse that has the architecture, normalization, and data models needed to meet business needs
    Provide an overview of normalization and the choices that are made with regard to data in a data warehouse
    Correlate the relationship between data access patterns and a well planned data warehouse architecture
    Identify the steps and processes associated with configuring data discovery in the google cloud platform (gcp)
    Outline best practices that can reduce the costs for a gcp data lake
  • Recognize when to choose various methods of using identity and access management (iam) and access control lists (acls) to control access
    Identify the tools used to process data in a gcp data lake for different end goals
    List the tools and techniques used to monitor a gcp data lake
    Identify the tools used to build a gcp data mesh based on various business requirements
    Devise segmentation options that integrate with a federated governance plan to ensure the security of a data mesh end-to-end
    Compare and contrast the different processes used to bring data into a data warehouse
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 10s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 9m 44s
    After completing this video, you will be able to identify the differences between a data warehouse, a data lake, and a data mesh. FREE ACCESS
  • Locked
    3.  Designing the Data Model for a Data Warehouse
    10m 41s
    Upon completion of this video, you will be able to outline the process of defining a data warehouse that has the architecture, normalization, and data models needed to meet business needs. FREE ACCESS
  • Locked
    4.  Data Normalization in a Data Warehouse
    6m 51s
    After completing this video, you will be able to provide an overview of normalization and the choices that are made with regard to data in a data warehouse. FREE ACCESS
  • Locked
    5.  Data Access Defines Data Warehouse Architecture
    6m 50s
    Upon completion of this video, you will be able to correlate the relationship between data access patterns and a well planned data warehouse architecture. FREE ACCESS
  • Locked
    6.  Discovering Data for a Google Cloud Platform (GCP) Data Lake
    5m 53s
    After completing this video, you will be able to identify the steps and processes associated with configuring data discovery in the Google Cloud Platform (GCP). FREE ACCESS
  • Locked
    7.  Best Practices for Cost Control to a GCP Data Lake
    6m 18s
    Upon completion of this video, you will be able to outline best practices that can reduce the costs for a GCP data lake. FREE ACCESS
  • Locked
    8.  Best Practices for Access to a GCP Data Lake
    3m 55s
    After completing this video, you will be able to recognize when to choose various methods of using Identity and Access Management (IAM) and access control lists (ACLs) to control access. FREE ACCESS
  • Locked
    9.  Processing Data in a Data Lake
    5m 11s
    Upon completion of this video, you will be able to identify the tools used to process data in a GCP data lake for different end goals. FREE ACCESS
  • Locked
    10.  Monitoring on GCP
    7m 15s
    After completing this video, you will be able to list the tools and techniques used to monitor a GCP data lake. FREE ACCESS
  • Locked
    11.  Building a Data Mesh on GCP
    7m 9s
    Upon completion of this video, you will be able to identify the tools used to build a GCP data mesh based on various business requirements. FREE ACCESS
  • Locked
    12.  Building Governance for a GCP Data Mesh
    4m 54s
    After completing this video, you will be able to devise segmentation options that integrate with a federated governance plan to ensure the security of a data mesh end-to-end. FREE ACCESS
  • Locked
    13.  ELT and ETL
    6m 55s
    Upon completion of this video, you will be able to compare and contrast the different processes used to bring data into a data warehouse. FREE ACCESS
  • Locked
    14.  Course Summary
    1m
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE

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