Google has introduced new features to its BigQuery data warehouse that make data analysis more intuitive and efficient. The latest updates include a conversational analytics agent and tools for building custom AI agents, aimed at helping both technical and non-technical users explore data using natural language. These additions are designed to speed up insights and reduce the need for prebuilt dashboards or complex queries.

Conversational Analytics in BigQuery

The new conversational analytics feature, currently in preview, allows users to ask questions about their data in natural language. Found under the Conversations tab in the Agents Hub, it can be activated by pointing to specific data tables. This builds on BigQuery’s existing text-to-SQL capabilities, making it easier for users to interact with data without needing to write SQL code.

What sets this apart is the agent’s ability to hold a contextual conversation. Instead of treating each question as separate, it remembers previous prompts, including datasets, filters, time ranges, and assumptions. This means users can refine their analysis step-by-step, just like chatting with a knowledgeable colleague. Experts say this makes data exploration more flexible and less dependent on prebuilt dashboards or scripts.

Benefits for Data Teams and Business Users

This new approach reduces the pressure on developers, who no longer need to predefine every possible question or scenario. Instead, teams can let the agent interpret user intent dynamically, while still maintaining access controls and governance rules already set in BigQuery. This makes it easier for business users and analysts to get quick answers without waiting for custom reports or dashboards.

Additionally, the conversational agent can remember context over multiple steps, allowing for more natural and iterative data analysis. Users can start with broad questions and then narrow down or explore further without losing their place or needing to repeat information. This improves productivity and helps teams make faster, more informed decisions.

Tools for Building and Managing Custom Agents

Alongside the conversational agent, Google has added tools to build, deploy, and manage custom AI agents through API endpoints in the Agents Hub. These tools are designed to address common enterprise needs such as reducing duplicated logic, ensuring consistent data definitions, and centralizing access controls. This helps organizations streamline their analytics workflows across multiple applications.

Custom agents can be deployed across different platforms, including Looker, which now has a built-in conversational analytics feature. This integration simplifies the process for developers and analysts to create tailored AI assistants that fit their specific workflows and data security requirements. It also means teams can avoid rebuilding the same logic repeatedly for different tools or use cases.

By offering these capabilities, Google aims to make enterprise data analysis more scalable and manageable. The ability to build, customize, and centrally control AI agents enables organizations to maintain governance while empowering users with more natural, conversational access to their data.

Ongoing Improvements to BigQuery’s SQL and Language Capabilities

Google continues to enhance BigQuery’s natural language and SQL features. Recently, it previewed a Comments to SQL tool that translates natural language instructions written in SQL comments into executable queries within BigQuery Studio. This makes it easier for developers and analysts to create complex queries without manually coding every step.

Earlier this month, Google also introduced new AI-powered SQL functions, further improving the platform’s ability to understand and process natural language requests. These ongoing updates show Google’s focus on making BigQuery more accessible and efficient for a wide range of users, from data scientists to business analysts.

Overall, these new features position BigQuery as a more intelligent, conversational, and user-friendly data warehouse, helping organizations unlock faster insights and streamline their data workflows more effectively than ever before.

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• https://www.infoworld.com/article/4124972/google-expands-bigquery-with-conversational-agent-and-custom-agent-tools.html