How to migrate an on-premises data warehouse to BigQuery on Google CloudHow to migrate an on-premises data warehouse to BigQuery on Google CloudDeveloper Advocate, GoogleSpecialist Customer Engineer

Why BigQuery?

On-premises data warehouses become difficult to scale so most companies’ biggest goal is to create a forward looking system to store data that is secure, scalable and cost effective. GCP’s BigQuery is serverless, highly scalable, and cost-effective and is a great technical fit for the EDW use-case. It’s a multicloud data warehouse designed for business agility. But, migrating a large, highly-integrated data warehouse from on-premise to BigQuery is not a flip-a-switch kinda migration. You need to make sure your downstream systems dont break due to inconsistent results in migrating datasets, both during and after the migration. have to plan your migration. 

Data warehouse migration strategy

 The following steps are typical for a successful migration: 

  • Validation and testing

    •  Look for tools to allow automated, intelligent data validation 

    • Scope must include both schema and data validation

    • Ideally solutions will allow continuous validation from source to target system during migration

    • Testing complexity and duration will be driven by number and complexity of applications consuming data from the EDW and rate of change of those applications 

A key to successful migration is finding Google Cloud partners with experience migrating EDW workloads. For example, our Google Cloud partner Datametica offers services and specialized Migration Accelerators for each of these migration stages to make it more efficient to plan and execute migrations.

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