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Modernizing Data Lakes and Data Warehouses with Google Cloud
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...
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$900 USD
Duration
1 day
Course Code
GCP-DLW
Available Formats
Classroom, Virtual
Overview
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.
Skills Gained
- 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.
Who Can Benefit
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
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
Course Details
Course Outline
Introduction
- This module introduces the Data Engineering on Google Cloud source series and this Modernizing Data Lakes and Data Warehouses with Google Cloud course.
Introduction to Data Engineering
- This module discusses the role of data engineering and motivates the claim why data engineering should be done in the Cloud
Building a Data Lake
- In this module, we describe what data lake is and how to use Cloud Storage as your data lake on Google Cloud.
Building a Data Warehouse
- In this module, we talk about BigQuery as a data warehousing option on Google Cloud
Summary
- A summary of the key learning points
Course Resources
- Links to PDF versions of each module
Schedule
1 options available
-
Sep 5, 2025 - Sep 5, 2025 (1 day)
Live Virtual | 9:00AM – 5:00PM EDT Language English Select from 1 options below Live Virtual |9:00AM – 5:00PM EDT- Enroll
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FAQ
Does the course schedule include a Lunchbreak?
Classes typically include a 1-hour lunch break around midday. However, the exact break times and duration can vary depending on the specific class. Your instructor will provide detailed information at the start of the course.
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Most courses are conducted in English, unless otherwise specified. Some courses will have the word "FRENCH" marked in red beside the scheduled date(s) indicating the language of instruction.
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GTR stands for Guaranteed to Run; if you see a course with this status, it means this event is confirmed to run. View our GTR page to see our full list of Guaranteed to Run courses.
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At Ascendient Learning, we offer training that is Instructor-Led, Online, Virtual, and Self-Paced.
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As a vendor-authorized training partner, we offer a curriculum that our partners have vetted. We use the same course materials and facilitate the same labs as our vendor-delivered training. These courses are considered the gold standard and, as such, are priced accordingly.
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Ascendient Learning instructors have an average of 27 years of practical IT experience and have also served as consultants for an average of 15 years. To stay current, instructors spend at least 25 percent of their time learning new, emerging technologies and courses.
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Reviews
The platform is very intuitive and easy to navigate. Great tool for learning
Class was very informative, although one lab didnt but will try again later
Overall experiance is very nice. the online training plateform is very advance.
Instructor, Training material & span of the training is neatly planned.
Simply great training provider that I can go for updating/acquiring my skill sets.
