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Googles Vision for AI-Native Data Analytics Comes Into Focus

2025-04-14•Chris McKay•Original Link•2 minutes
AI
Data Analytics
Google Cloud

At Google Cloud Next 2025, Google rolled out Gemini-powered agents and assistive tools across BigQuery and Looker, offering enterprises a smarter, AI-native way to work with data.

At Google Cloud Next 2025, the company unveiled groundbreaking updates to its data analytics platform, emphasizing AI-native solutions powered by Gemini. These enhancements aim to make data work more conversational, contextual, and intelligent.

Google’s Vision for AI-Native Data Analytics Comes Into Focus

Key Developments:

  • Gemini Integration: Now embedded in BigQuery and Looker, enabling code assist, analytics, and data agents.
  • Specialized Agents: Tailored for roles like data engineers and business analysts, streamlining workflows.
  • BigQuery Knowledge Engine: Improves accuracy by understanding context, semantics, and organizational data patterns.
  • Real-World Impact: Customers report major cost savings and productivity boosts.

According to Peter Bailis, VP of Engineering at Google Cloud, "Google is the only frontier model provider with models at the top of the leader boards in all the benchmarks and evaluations that are tracked, that also has a data stack." The goal is to infuse data tools with Gemini’s intelligence.

How It Works:

  • Autonomous Platform: Suggests joins, transformations, and datasets without manual effort.
  • 60% Acceptance Rate: For SQL and Python code assistance in BigQuery, double the typical rate for coding models.
  • 350% Growth: Usage has surged in the past nine months.

Addressing Data Challenges:

Bailis highlighted the repetitive nature of data work: "A lot of data work is still drudgery... remembering the correct formula for parsing timestamps into canonical formats." Gemini’s organizational context makes suggestions far more relevant.

BigQuery Knowledge Engine

Future Vision:

  • Proactive Analytics: Agents will act like analysts, surfacing changes proactively.
  • Unstructured Data: Making images, audio, and text first-class citizens in BigQuery.
  • Trust and Governance: Bailis advises starting small with internal-facing agents and layering in governance.

Why It Matters:

The future of data work isn’t just about smarter tools—it’s about expanding participation in data conversations and accelerating decision-making. Google’s autonomous data-to-AI platform is a significant step toward this vision.

Chris McKay is the founder and chief editor of Maginative. His thought leadership in AI literacy and strategic AI adoption has been recognized by top academic institutions, media, and global brands.

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