BigQuery Consulting
Architecture reviews, data modeling, partitioning and clustering strategies, and performance tuning for new and existing BigQuery environments.
- Architecture design
- Data modeling
- Query performance
- Cost controls
Modernize legacy data warehouses on BigQuery with expert Google Cloud data engineering: BigQuery migration, governed pipelines, real-time analytics and data that is ready for Vertex AI and Gemini.
We combine BigQuery consulting, migration and Google Cloud data engineering to give analytics and AI teams trusted, fast and well-governed data.
Architecture reviews, data modeling, partitioning and clustering strategies, and performance tuning for new and existing BigQuery environments.
Move Teradata, Netezza, Oracle, SQL Server, Snowflake, Redshift and Hadoop workloads to BigQuery with automated SQL translation.
Replace rigid, expensive warehouses with a serverless platform that scales on demand and supports lakehouse patterns.
Reliable batch and streaming pipelines using Dataflow, Pub/Sub, Dataproc, Cloud Composer and dbt.
Catalog, lineage, data quality rules and fine-grained access controls with Dataplex and BigQuery policies.
Put data to work with BigQuery ML, Looker and Vertex AI. See our enterprise AI solutions.
We de-risk every data warehouse migration with automated translation, side-by-side validation and a clear decommissioning plan for the legacy platform.
Profile queries, data volumes, dependencies and users to size and sequence the migration.
Use the BigQuery migration service to translate legacy SQL, then review edge cases by hand.
Move historical data with BigQuery Data Transfer Service and Storage Transfer at scale.
Run old and new platforms side by side and reconcile results before switching over.
Partitioning, clustering and materialized views to keep queries fast and predictable.
Editions, reservations and query governance so BigQuery costs stay under control.
A phased path for data modernization that delivers value early instead of one risky big-bang project.
Map sources, workloads, data quality and business priorities.
Define the target BigQuery architecture, governance and security model.
Translate SQL, move data and rebuild pipelines in prioritized waves.
Reconcile results in parallel and move reports and users across.
Add real-time, ML and generative AI use cases on the new platform.
We build data platforms with the end use in mind: dashboards people trust today, and data foundations ready for Vertex AI, Gemini and Agentic AI tomorrow.
Priorities driven by reports, decisions and AI use cases that matter.
BigQuery, Dataflow, Dataplex, Looker and Vertex AI under one roof.
Access, lineage and quality controls from the first pipeline.
Workload-aware pricing choices backed by FinOps practices.
What teams ask most before modernizing their data warehouse.
BigQuery is serverless and scales automatically, separates storage from compute, and connects directly to Looker, BigQuery ML and Vertex AI, which removes most infrastructure management.
Yes. We migrate Teradata, Netezza, Oracle, SQL Server, Snowflake, Redshift and Hadoop using automated SQL translation plus manual review of complex logic.
Through partitioning and clustering, the right pricing edition, reservations, query governance and regular cost reviews.
We run old and new platforms in parallel, reconcile results and re-point dashboards so business users move over without disruption.
Get a data modernization assessment with a target architecture, migration plan and cost estimate for BigQuery.
Book a Data AssessmentCopyright © 2026 Auriqo| All rights Reserved.