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    04

    Modernizing Data Lakes and Data Warehouses with Google Cloud

    04

    Modernizing Data Lakes and Data Warehouses with Google Cloud

    magic_button Data Lake Data Warehouse
    These skills were generated by AI. Do you agree this course teaches these skills?
    8 hours Intermediate universal_currency_alt 25 Credits

    The two key components of any data pipeline are data lakes and warehouses. This course highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud in technical detail. Also, this course describes the role of a data engineer, the benefits of a successful data pipeline to business operations, and examines why data engineering should be done in a cloud environment.

    This is the first course of the Data Engineering on Google Cloud series. After completing this course, enroll in the Building Batch Data Pipelines on Google Cloud course.

    When you complete this course, you can earn the badge displayed here! View all the badges you have earned by visiting your profile page. Boost your cloud career by showing the world the skills you have developed!

    Badge for Modernizing Data Lakes and Data Warehouses with Google Cloud
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    Course Info
    Objectives
    • Differentiate between data lakes and data warehouses.
    • Explore use-cases for each type of storage and the available data lake and warehouse solutions on Google Cloud.
    • Discuss the role of a data engineer and the benefits of a successful data pipeline to business operations.
    • Examine why data engineering should be done in a cloud environment.
    Prerequisites
    To benefit from this course, participants should have completed “Google Cloud Big Data and Machine Learning Fundamentals” or have equivalent experience. Participant should also have: • Basic proficiency with a common query language such as SQL. • Experience with data modeling and ETL (extract, transform, load) activities. • Experience with developing applications using a common programming language such as Python. • Familiarity with machine learning and/or statistics
    Audience
    This course is intended for developers who are responsible for: Querying datasets, visualizing query results, and creating reports. Specific job roles include: Data Engineer, Data Analyst, Database Administrators, Big Data Architects
    Available languages
    English, 日本語, español (Latinoamérica), français, português (Brasil), italiano, and 한국어
    What do I do when I finish this course?
    After finishing this course, you can explore additional content in your learning path or browse the catalog.
    What badges can I earn?
    Upon finishing the required items in a course, you will earn a badge of completion. Badges can be viewed on your profile and shared with your social network.
    Interested in taking this course with one of our authorized on-demand partners?
    Explore Google Cloud content on Coursera and Pluralsight.
    Prefer learning with an instructor?
    View the public classroom schedule here.
    Can I take this course for free?
    When you enroll into most courses, you will be able to consume course materials like videos and documents for free. If a course consists of labs, you will need to purchase an individual subscription or credits to be able consume the labs. Labs can also be unlocked by any campaigns you participate in. All required activities in a course must be completed to be awarded the completion badge.
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