Overview
Google Cloud consulting: data, integration and AI workloads, run onshore
Google Cloud, often called GCP, is Google's infrastructure, data and AI platform: compute and containers, BigQuery for analytics, Looker for business intelligence, Apigee for API management, and the Gemini Enterprise Agent Platform, which Google describes as the evolution of Vertex AI, for building AI on Gemini and other models. It suits organisations moving workloads off ageing infrastructure, building a warehouse that brings CRM, ERP and marketing data together, or developing AI applications that need to run in Australia.
Google Cloud has two Australian regions, Sydney (australia-southeast1) and Melbourne (australia-southeast2), each with three zones. Running across zones protects against a single data centre failing; running across both regions keeps a recovery copy in the country. The services and machine types on offer differ between the two, so region choice is a design decision, not a default.
Great Minds is a Sydney-based systems integrator, the integrator for the gaps between platforms. Most of our Google Cloud work connects it to systems that live elsewhere: Salesforce, Dynamics 365, Atlassian, Adobe and your own applications. AI agents handle repetitive migration, mapping and test work; senior consultants own the architecture. Our data integration and analytics pages cover the wider practice.
Capabilities
Google Cloud services we deliver
We provide services across infrastructure, data and AI for mid-market and enterprise organisations, sized to the workloads you actually have. Each engagement starts with what you run today and what it costs, so the case for moving is made on your numbers.
How we deliver
How we deliver on Google Cloud
An inventory of workloads, data and dependencies, each sorted into keep, move, modernise or retire, with an estimate of what it would cost to run on Google Cloud.
Organisation structure, projects, identity, networking, logging and security policies set up in the Australian regions before any workload moves.
Workloads and data pipelines moved in waves, each tested and reconciled before cutover. AI agents generate mapping and test scripts; consultants review them.
Monitoring, cost reports and runbooks, then support from us or a hand-over to your team, with regular reviews of spend and sizing.
Australian considerations
Data residency, privacy and APRA on Google Cloud
Choosing Sydney or Melbourne keeps most workloads onshore, but not every service is regional: some run globally or across multiple regions, and some features and machine types aren't offered in both Australian regions. We check each service in the design. For generative AI, Google lists Sydney among the locations for its AI endpoints, but which models are offered there varies, so the model choice and the residency requirement are settled together.
Under the Privacy Act, data residency is about more than the primary database. Logs, backups, analytics copies and support access can all move personal information, and APP 8 applies to any of them that leave Australia, while APP 11 requires reasonable steps to keep the data secure. BigQuery datasets are created in a location, so we set an Australian one from the start rather than move data later.
For APRA-regulated entities, a cloud platform that supports a critical operation falls within CPS 230's requirements for service providers, and the data on it within CPS 234's information security requirements. We document the architecture, controls and recovery arrangements those assessments need.
FAQ
Google Cloud questions
Does Google Cloud have Australian regions?
Yes, two: Sydney (australia-southeast1) and Melbourne (australia-southeast2), each with three zones. Services and machine types differ slightly between them, so we confirm availability for each part of your design.
Should we choose Google Cloud, Azure or AWS?
Start from what you already run. Organisations on Google Workspace, BigQuery or Gemini often find Google Cloud the natural fit; those on Microsoft 365 and Dynamics 365 often lean to Azure; and an existing AWS estate is a reason to stay. We also deliver on Microsoft Azure and AWS, and compare them on your workloads.
Is Vertex AI still a product?
Google now describes the Gemini Enterprise Agent Platform as the evolution of Vertex AI, and its documentation uses the new name. It's the same developer platform for building with Gemini and other models, under a new name.
Can BigQuery bring together our Salesforce and ERP data?
Yes. We load data from Salesforce, your ERP and marketing systems into BigQuery through managed pipelines, model it so the same customer and order mean the same thing across sources, and report on it in Looker or your existing BI tool.
How do you keep Google Cloud costs under control?
Budgets and alerts per project, labels that tie spend to teams, right-sizing after workloads settle, and committed use discounts once usage is predictable. We review spend with you regularly rather than only at renewal.
Where do we start?
With one workload or one data use case, such as a reporting warehouse that combines CRM and ERP data. We assess it, agree scope and price, and build from there.
Case studies
Data, integration and infrastructure work
We don't yet have a published Google Cloud case study. The work below shows the integration, data migration and infrastructure projects our Google Cloud work draws on.
Insights
Reading on cloud, data and integration
Atlassian Data Center to Cloud: the Australian migration guideAtlassian Data Center goes read-only on 28 March 2029. Key dates, Australian data residency, CPS 230 and privacy checks, and a migration plan.
Moving work management to the cloud: a guide for Australian organisationsData Center end of life, data residency in Sydney, IRAP, Cloud plans and AI, and how to plan the move.