Overview
Cloud data modernization means moving data off aging warehouses, on-premises databases and scattered spreadsheets onto a cloud platform your teams can trust, query and build on. On Google Cloud that platform is typically BigQuery, with Looker on top for governed reporting.
The goal is not just a cheaper warehouse. It is a single source of truth that analysts can use today and AI can use tomorrow, because your AI is only as good as your data. We move the data, migrate the SQL and reports that depend on it, and set up the governance that keeps it useful. Data modernization often starts alongside infrastructure and application modernization, and it feeds directly into our AI and ML work.
What we modernize
What you get
Migration tooling
Google Cloud provides managed tools for each stage of a migration. We choose and combine them based on your sources, your volumes and how fresh the data needs to be.
Assess your current warehouse, translate its SQL to GoogleSQL and transfer the data. Supported sources include Amazon Redshift, Hadoop, Hive and Apache Spark, IBM Netezza, Oracle and Oracle Exadata, Snowflake and Teradata.
Learn more →Automate scheduled, managed transfers into BigQuery from sources such as Salesforce, Google Ads, Google Analytics 4, Cloud Storage and Amazon S3, and from databases including MySQL, PostgreSQL and Oracle.
Talk to a data architect →Serverless change data capture replicates changes from databases such as MySQL, Oracle, PostgreSQL and SQL Server into BigQuery, for near real-time analytics.
Talk to a data architect →Describe your data model once in LookML and give every team the same trusted numbers in interactive dashboards.
Learn more →AI readiness
AI agents and models are only as good as the data behind them. Once your data is in BigQuery and described in a governed model, it can serve as a trusted source for Gemini and for agents built on Gemini Enterprise Agent Platform (formerly Vertex AI).
We prepare datasets for AI while we migrate them: clear definitions, consistent keys, access controls and documentation. Read our guide to Vertex AI or see our Gemini services.
It is the process of moving data from legacy warehouses, on-premises databases and ad hoc files to a modern cloud platform, and rebuilding the pipelines and reports that depend on it, so the data is trusted, governed and ready for analytics and AI.
BigQuery is Google Cloud’s fully managed data warehouse. It connects directly to Looker and to Google’s AI tools, and it has migration tooling for common warehouses.
Yes. BigQuery Migration Service supports assessment, SQL translation and data transfer from sources including Teradata, Amazon Redshift and Snowflake, as well as Oracle, IBM Netezza and Hadoop. We handle the parts that tooling cannot, such as pipeline redesign and report rebuilds.
We plan the cutover with you, validate results against the source system, and keep existing reports available until the new ones are signed off.
AI is only as good as your data. A governed single source of truth in BigQuery gives Gemini and your AI agents a trusted foundation. See our AI and ML solutions and our Gemini services.
Start with a Data Warehouse or Data Lake Modernization pilot: a fixed-scope project that proves the approach on one data domain. Book a discovery call.
