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03

Build Data Lakes and Data Warehouses on Google Cloud

03

Build Data Lakes and Data Warehouses on Google Cloud

magic_button Data Modelling Datastream Data Fusion Data Lake Modernization
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5 hours Intermediate

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.

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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 и 한국어

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