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Data Science on Google Cloud Platform

Cloud computing brings unlimited scalability and elasticity to data science applications. Expertise in the major platforms, such as Google Cloud Platform (GCP), is essential to the IT professional. This course—one of a series by veteran cloud engineering specialist and data scientist Kumaran Ponnambalam—shows how to design and build data warehouses using GCP. Explore the different types of storage options available in GCP for files, relational data, documents, and big data, including Cloud SQL, Cloud Bigtable, and Cloud BigQuery. Then learn how to use one solution, BigQuery, to perform data storage and query operations, and review advanced use cases, such as working with partition tables and external data sources. Finally, learn best practices for table design, storage and query optimization, and monitoring of data warehouses in BigQuery.

Contents:

  • Introduction
  • 1. Storing Data in GCP
  • 2. BigQuery Data Creation
  • 3. Querying Data in BigQuery
  • 4. Advanced BigQuery
  • 5. Best Practices in BigQuery
  • Conclusion

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Length 1h
Starts On Demand (Start anytime)
Cost $29/month (Access to entire library- free trial available)
From LinkedIn Learning
Instructor Kumaran Ponnambalam
Download Videos Only via the LinkedIn Learning mobile app
Language English
Subjects IT & Networking Data Science Programming
Tags IT Databases Big Data SQL Data Warehousing Database Development Data Modeling Google Cloud Platform (GCP)

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Rating Not enough ratings
Length 1h
Starts On Demand (Start anytime)
Cost $29/month (Access to entire library- free trial available)
From LinkedIn Learning
Instructor Kumaran Ponnambalam
Download Videos Only via the LinkedIn Learning mobile app
Language English
Subjects IT & Networking Data Science Programming
Tags IT Databases Big Data SQL Data Warehousing Database Development Data Modeling Google Cloud Platform (GCP)

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