BigQuery consulting for warehouse design, ingestion, reporting and cost.

We quote after a scoping call. The estimate depends on the number of sources, the volume of history to load, how much SQL needs translating, the reports in scope and whether you want support after handover. A first project is scoped to be verifiable in weeks, and the quote for anything beyond it is based on your own query history.

Usually because queries read more than they need to. The common causes are tables with no partitioning, dashboards that query raw tables, scheduled queries that rebuild full history every hour and SELECT * in views that other views build on. The fix starts with the job history, which shows exactly which queries bill the most bytes and who runs them, and then applies partition filters, clustering, materialised views and per-user limits in that order.

By the column your queries filter on, which is usually an event or transaction date. Ingestion-time partitioning is simpler to load but only helps when reports ask about when data arrived, which they rarely do. Where late-arriving records are common, the load uses MERGE into the correct date partition rather than appending to today's, and a partition-filter requirement stops anyone scanning the full table by accident.

Yes. The work starts with discovery of what exists and what depends on it, then a source-to-target mapping per object, SQL translated and tested, and reconciliation of counts, totals and reported metrics at each layer before the old platform is switched off. Platform-specific SQL, stored procedures and cross-database joins are the usual blockers, and they are found in discovery rather than at cutover.

Yes. MV.tech works from Ahmedabad, India, and agrees a collaboration window in your timezone before the engagement starts, which typically covers UK and European business hours, US Eastern mornings, Gulf hours or Asia-Pacific afternoons. Access is through your own Google Cloud project with IAM roles you grant and can revoke, logs stay in your project and no credentials are needed for an initial enquiry.

Looker Studio is reasonable for reporting over BigQuery when the model lives in the warehouse and the reports read curated views. Power BI becomes the better choice when you need a governed semantic layer, row-level security or complex measures, or when the organisation already runs on Microsoft 365. Either way the metric definitions belong in BigQuery, so changing the reporting tool later is a repointing exercise rather than a rebuild.

No. MV.tech is not a Google partner. Its founder holds the Google Cloud Professional Data Engineer credential, which is an individual certification, and has built BigQuery pipelines in previous roles. If partner status matters for your procurement, say so on the first call.