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Reducing monthly BigQuery cost by 25%

Combining query analysis, table design, slot tuning, retention, and tiered storage to reduce recurring analytics cost.

Area
Analytics cost optimization
Role
Senior Data Engineer
lower monthly BigQuery cost
25%

Optimization system

Cost optimization system

Usage evidence drives coordinated changes to queries, table layout, capacity, retention, and storage placement.

Method

  • Identified expensive queries and optimized how they accessed data.
  • Partitioned and clustered tables to reduce unnecessary scanning.
  • Tuned slot capacity and controlled storage growth.
  • Removed obsolete data and moved suitable data from BigQuery to Cloud Storage.

Outcome

After the process was implemented, recurring monthly BigQuery cost was reduced by 25 percent.

Team credit

I implemented the optimization work in collaboration with the data engineering team.

System materials

Stack

  • BigQuery
  • Cloud Storage
  • Apache Airflow
  • Python
  • SQL
  • Terraform