Backward-looking reports alone won’t give you an edge. The next wave of value comes from conversational analytics and agentic workflows, where people and AI agents ask your data questions and act on the answers.
We bring BigQuery, Looker and Gemini Enterprise together into one trusted source of truth that grounds your AI agents in your actual data. Your teams get insights in real time, and repetitive data work runs by itself.
Your modern data platform in three steps
From scattered sources to data that powers your daily workflows. This is how we build it with you.
Step 1: Unify your data
It all starts with bringing your data together. BigQuery is Google’s Autonomous Data to AI Platform: serverless, auto-scaling, and built to handle structured, unstructured, and multimodal data. It supports open formats like Apache Iceberg, so your data stays portable. No lock-in. And with Gemini built in, even the data engineering gets easier through automated pipelines and smart data quality checks.
Step 2: Turn data into insights
Once your data is unified, Google offers multiple ways to extract value: Looker for governed enterprise BI with consistent metric definitions, Looker Studio for quick visual dashboards, and Conversational Analytics to ask your data questions in plain language. BigQuery also works with the BI tools you already have, like Power BI, Qlik, and Tableau.
Step 3: Connect data to workflows
This is where it gets interesting. Your data platform becomes an active part of how your business operates. Imagine an employee asking their AI agent: “Show me the open proposals from the last three months with their close rates.” No dashboard needed, no waiting for analytics. Connect your data platform to your CRM, your service desk, your supply chain tools, and AI agents pull relevant data in real time.
Data foundation for AI
Here’s something we keep coming back to in conversations with our clients: data and AI are inseparable. You can’t do meaningful AI without a solid data platform, and modern data platforms all have AI baked in.
We help you build that foundation. Get your data clean, connected, and accessible, so when you’re ready to deploy AI models, build agents, or automate workflows, the data layer is already there. A solid data foundation first, then AI on top.
This connects directly to our AI services. If you’re looking at the AI side of things, check out our AI page.
Why Google is the data platform to build on
Google is, at its core, a data company. Search, YouTube, Gmail, Maps: every one of these products runs on the same data infrastructure that powers BigQuery. When you build your data platform on Google Cloud, you’re using technology that processes exabytes of data daily at a scale no other provider matches.
That shows in the analyst recognition too: Google is a Leader in the 2025 Gartner Magic Quadrant for both Cloud DBMS and Analytics & BI Platforms. But more importantly, it shows in the approach. Google built BigQuery to solve their own data challenges first, then made it available to everyone. Open formats, native AI integration, and a serverless architecture that scales without you having to think about infrastructure.
That’s the kind of platform you build your data strategy on.
What a modern Google Cloud data platform delivers in practice
A data platform is only as good as the results it produces. Here’s how we’ve helped organizations go from scattered data to a single source of truth, faster decision-making, and AI-ready infrastructure.
