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Data Science on Google Cloud Platform: Designing Data Warehouses

via LinkedIn Learning

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Overview

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Learn how to design and build data warehouses using Google Cloud Platform solutions such as BigQuery.

Syllabus

Introduction
  • Why data warehouses are important
  • Data science modules covered
1. Storing Data in GCP
  • GCP storage options
  • Google Cloud Storage
  • Cloud SQL
  • Cloud Spanner
  • Cloud Bigtable
  • Cloud Datastore
  • Cloud BigQuery
2. BigQuery Data Creation
  • Intro to BigQuery
  • Projects and datasets
  • Tables
  • Create a dataset
  • Create a table with schema
  • Create a table from CSV
  • Load data from Cloud Storage
3. Querying Data in BigQuery
  • Simple queries
  • Filter data
  • SQL functions
  • Regular expressions
  • Grouping and aggregations
  • Joins and sub-queries
  • Update data
4. Advanced BigQuery
  • Partition tables
  • External data sources
  • Create views
  • Create labels
  • Google Cloud shell
  • Other interfaces
5. Best Practices in BigQuery
  • Table design considerations
  • Optimize storage
  • Load data
  • Speed up queries
  • Monitoring and logging
Conclusion
  • Next steps

Taught by

Kumaran Ponnambalam

Reviews

4.6 rating at LinkedIn Learning based on 271 ratings

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