03
Build Data Lakes and Data Warehouses on Google Cloud
03
Build Data Lakes and Data Warehouses on Google Cloud
These skills were generated by AI. Do you agree this course teaches these skills?
While the traditional approaches of using data lakes and data warehouses can be effective, they have shortcomings, particularly in large enterprise environments. This course introduces the concept of a data lakehouse and the Google Cloud products used to create one. A lakehouse architecture uses open-standard data sources and combines the best features of data lakes and data warehouses, which addresses many of their shortcomings.
Course Info
Objectives
- Differentiate between a data lake, data warehouse, data lakehouse
- Explain the data lakehouse concept and how it addresses the limitations of traditional data lakes and data warehouses
- Identifying various data sources that BigQuery can query
- Recognize the capabilities of using BigQuery to create and access AI models
Prerequisites
To benefit from this course participants should have familiarity, training, or experience with the principles and activities associated with data engineering, data warehouse or data lake architecture, SQL query language, or data management principles.
Audience
Data Engineer, Data Analyst, Database Administrators, Big Data Architects
Available languages
English, 日本語, español (Latinoamérica), français, português (Brasil), italiano, and 한국어
How do I earn a completion badge?
Upon finishing a course you will earn a badge of completion. Badges can be viewed on your profile and shared with your social network.
Do you prefer learning with an instructor?
View the public classroom schedule here