Learning Paths

Google Cloud Big Data - Foundations

  • Number of Courses3 courses
  • Duration11 hours
  • Skill IQ available Skill IQ

This path introduces participants to the Big Data capabilities of Google Cloud Platform. It provides an overview of the many data processing products and tools, and then does a deep dive into BigQuery’s data analysis capabilities and its use as a data warehouse, as well as Cloud Storage as a data lake.

Courses in this path


This section introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.


In this Section, we will see what the common challenges faced by data analysts are and how to solve them with the big data tools on Google Cloud Platform. You’ll pick up some SQL along the way and become very familiar with using BigQuery and Cloud Dataprep to analyze and transform your datasets.

By the end, you’ll be able to query and draw insight from millions of records in our BigQuery public datasets. You’ll learn how to assess the quality of your datasets and develop an automated data cleansing pipeline that will output to BigQuery. Lastly, you’ll get to practice writing and troubleshooting SQL on a real Google Analytics e-commerce dataset to drive marketing insights.


This section talks about the two key components of any data pipeline, data lakes and warehouses. It highlights use-cases for each type of storage and dives into the available data lake and warehouse solutions on Google Cloud Platform in technical detail. This section also covers 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. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.

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