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Course
- Cloud
Modernizing Data Lakes and Data Warehouses with GCP
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 Platform in technical detail.
What you'll learn
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 Platform 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. Learners will get hands-on experience with data lakes and warehouses on Google Cloud Platform using QwikLabs.
Table of contents
- Explore the role of a data engineer | 6m 59s
- Analyze data engineering challenges | 8m 59s
- Intro to BigQuery | 3m 22s
- Data Lakes and Data Warehouses | 5m 59s
- Demo:Federated Queries with BigQuery | 6m 50s
- Transactional Databases vs Data Warehouses | 4m 53s
- Partner effectively with other data teams | 6m 20s
- Manage data access and governance | 2m 12s
- Demo:Finding PII in your dataset with DLP API | 1m 57s
- Build production-ready pipelines | 2m 8s
- Review GCP customer case study | 3m 55s
- Recap | 1m 24s
- Getting Started With GCP And Qwiklabs | 3m 48s
- Lab Intro:Using BigQuery to do Analysis | 17s
- Lab: Using BigQuery to do Analysis | 10s
