Storage & Warehousing

BigQuery

Google Cloud's serverless analytics warehouse — scale without limits

https://cloud.google.com/bigquery

What It Is

BigQuery is Google Cloud’s fully managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google’s infrastructure. It separates storage and compute completely, scales automatically, and requires zero infrastructure management — making it an excellent choice for organizations in the GCP ecosystem who want analytics without operational overhead.

How We Use It

We build BigQuery-based analytics platforms for GCP-native clients. Our work typically includes dataset architecture, table design with proper partitioning and clustering, cost optimization through slot reservations and on-demand pricing analysis, and integration with dbt for transformation layers. We connect BigQuery to BI tools, build streaming ingestion pipelines, and implement data governance with IAM and column-level security.

Our Expertise

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Dataset Architecture

We design BigQuery environments with proper project, dataset, and table structures. Multi-region considerations, data transfer configurations, and cross-project access patterns.
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Partitioning & Clustering

We optimize BigQuery tables for cost and performance: time-based and integer-range partitioning, multi-column clustering, and partition pruning strategies that reduce both scan costs and query times.
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Cost Management

We implement BigQuery cost controls: slot reservations vs. on-demand pricing analysis, query cost estimation, custom quotas, and monitoring dashboards. Optimization recommendations that typically reduce costs by 30-50%.
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dbt Integration

We set up dbt projects optimized for BigQuery: incremental models, merge strategies, BigQuery-specific materializations, and proper use of partitioning and clustering in dbt models.