Solution will combine a proven data platform visibility and automation engine with DoiT’s market-leading depth of BigQuery customer experience.
SANTA CLARA, Calif., April 16, 2026 /PRNewswire/ — SELECT by DoiT, the data platform optimization company purpose-built to help engineering and data teams optimize cloud data platform spend, today announced plans for an automated cost observability and optimization platform for Google BigQuery, alongside the launch of an Early Access Program now open at select.dev. The announcement coincides with Google Cloud Next 2026 in Las Vegas, where attendees can see live demos of the product at the DoiT booth.
The Cost Visibility Gap in Cloud Data Platforms
As organizations deepen their investment in Google Cloud, BigQuery has become central infrastructure for analytics, machine learning and AI workloads, introducing a cost management challenge most teams are only beginning to confront. BigQuery’s pricing model spans on-demand queries, slot-based capacity reservations and storage billing distinctions that compound over time. Optimizing across all of these simultaneously, while also identifying wasted spend from failed or inefficient queries, is a sustained operational commitment that most engineering and FinOps teams aren’t resourced to maintain.
“Across thousands of BigQuery customer interactions, we’ve seen the level of expertise required to understand and optimize spend,” said John Purcell, chief product officer at DoiT. “That’s exactly the problem an automated platform is built to solve.”
A Foundation Built on Experience
SELECT’s BigQuery solution is built on two complementary capabilities: SELECT’s automation engine, refined through production deployments across more than $250 million in Snowflake spend and DoiT’s institutional depth in BigQuery, accumulated through nearly a decade of direct customer engagement and close to 2,000 BigQuery customers served since the launch of BigQuery Editions.
“SELECT’s automation engine has been proven in production across hundreds of Snowflake customers and will be scaled to BigQuery in combination with DoiT’s remarkable BigQuery expertise,” said Ian Whitestone, GM and co-founder of SELECT by DoiT. “Building on that foundation means we’re starting from a position of genuine expertise rather than building toward it.”
How the Solution Works
SELECT’s BigQuery solution integrates across the data stack to end-to-end costs, then optimizes across three automated layers:
