BigQuery’s trajectory has always trended toward more capability with less overhead. But now, we’re seeing a shift beyond analytics. As workloads grow more complex and expectations for real-time insights increase, BigQuery is adapting. It’s not just about storing and querying data—it’s about enabling data-driven AI workflows across teams.
Whether you're building ML models, surfacing predictive insights or tapping into third-party datasets, BigQuery is laying the groundwork to bring those capabilities closer to the people who need them most.
400+ Updates: A Few That Caught Our Eye
There were quite a few announcements, to say the least! Here are a few that stood out to us:
Gemini in BigQuery
Generate SQL-like queries using natural language; use Gemini to explain and complete your SQL code. Useful? Absolutely. Especially for speeding up analysis across teams with mixed skill levels. Less context switching, more insight discovery.
Data Agents
AI Agents allow you to automate tasks done in BigQuery. With Conversational Analytics, Data Engineering, and Data Science agents available, you gain a knowledgeable co-pilot that's available as you develop within BigQuery.
BigQuery Semantic Search
Utilize remote models to generate text embeddings, create vector indexes and use vector search to utilize semantic search directly within BigQuery.
Native multimodal support (in Preview)
BigQuery introduced a new ObjectRef data type that enables storage and querying of structured and unstructured data using Python or SQL functions. This allows you to integrate audio, video or images into existing BigQuery tables.
It’s like opening up a whole new layer of spatial insights. Think foot traffic trends, location scoring, proximity-based segmentation. For brands focused on geo-driven personalization, this is a big win.
Friendly UI Enhancements for the Curious Analyst
BigQuery Studio UX improvements, data canvas, built-in AI code assistance, and richer notebook experiences signal a better data scientist and analyst workflow. Exploration just got more accessible.
What This Means for Marketers
These innovations aren’t just exciting from a technical standpoint—they're practical upgrades for the marketing and analytics teams we support. This includes:
- Faster access to real-time insights with less technical friction
- Easier AI exploration and prototyping for advanced use cases
- New doors opened for location intelligence and predictive modeling
As more brands lean into utilizing marketing data strategies, BigQuery continues to mature as a foundational platform to unify, enrich, and predict on data, especially when paired with Google Cloud’s broader ecosystem. And ultimately, it allows trusted partners like Adswerve to deliver more innovative solutions.
Final Thought
The changes keep coming—and they’re coming fast. If BigQuery’s transformation over the last year is any indication, we’re looking at a platform that’s not just keeping up with AI it’s helping define what’s next.
Best of all, these innovations are creating more effective and creative solutions. It’s another reason to start a conversation with us about how your strategies can grow. We help marketers and agencies architect modern data stacks that integrate seamlessly with BigQuery, advise on scalable strategies across analytics, media and AI-readiness and activate those strategies across channels with insights that drive impact. Whether you're early in your cloud journey or evolving an advanced stack, we work with you to turn innovation into execution.
Additional Resources:
Interested in learning how these updates could impact your strategy? Get in touch to see what’s possible with BigQuery and Adswerve.
