BigQuery removes the warehouse-sizing question entirely — there is no cluster to provision. What it introduces instead is a pricing model where a careless query can scan a terabyte and a well-partitioned one can scan a gigabyte for the same answer. Design decisions show up directly on the bill.
Overview
Partitioning is the whole game
The difference between an expensive BigQuery estate and a cheap one is almost entirely partitioning, clustering, and whether queries filter on the partition column. We design tables around how they will actually be queried, and put the controls in place — custom quotas, required partition filters — that stop an ad-hoc query becoming an incident.
What we deliver
Beyond the warehouse
BigQuery sits inside a wider Google Cloud estate, and the integrations are usually where the value is: streaming in through Pub/Sub and Dataflow, serving out to Looker, and running models without moving the data.
- Partitioning and clustering designed against real query patterns
- Required partition filters and per-user quotas
- Streaming ingestion through Pub/Sub and Dataflow
- Scheduled queries and materialised views where they pay
- BigQuery ML where a model belongs next to the data
Why it matters
Why teams pick it
BigQuery suits bursty, unpredictable analytical workloads and teams who do not want to run infrastructure. It suits steady heavy workloads less well, where flat-rate or a provisioned warehouse can be cheaper — and we will model both before recommending either.
Workflow
How we work in it.
- 01
Assessment
- Query patterns, volumes and burst profile
- Current spend, broken down by table and user
- Source systems and ingestion latency needs
- Residency and access requirements
- 02
Dataset & Table Design
- Partitioning and clustering strategy
- Dataset layout and access boundaries
- Required partition filters and quotas
- Cost model and forecast
- 03
Pipelines
- Batch and streaming ingestion
- Transformations under version control, with tests
- Scheduled queries and materialised views
- Orchestration and dependency management
- 04
Operate
- Per-query cost attribution
- Slot and quota monitoring
- Access review and audit logging
- Handover and training
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