Data Science on Google Cloud Platform: Designing Data Warehouses

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

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