Performance and Cost Optimization with BigQuery

Complete this Guided Project in under 2 hours. This is a self-paced lab that takes place in the Google Cloud console. Learn how to improve your database ...

• Create BigQuery tables and load data into it. Reduce the cost of a query by using partitioning.
• Optimize a query by using denormalization. Improve row filtering and join performance by using clustering.
• Improve dashboard loading speed and cost by using materialized view. Reduce the elapsed time and cost by pruning the partitions with filters.
• Save cost by moving data out of unused partitions in BigQuery and onto cheaper Google Cloud Storage.