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How do Glean's new BigQuery agents work?

How do Glean's new BigQuery agents work?

Glean’s new structured query agents let users access BigQuery data through SQL or plain English queries, providing real-time insights and transparency with generated SQL for enterprise workflows.

Glean has introduced structured query agents that enable both technical and non-technical users to extract real-time insights from BigQuery. This development addresses a common challenge in enterprise environments: structured data often remains underutilized because access requires specialized knowledge.

By combining natural language processing with SQL functionality in a single interface, Glean expands the ability for employees across different roles to query and analyze data efficiently.

Structured data is critical for enterprise decision-making, but teams frequently face bottlenecks as only data specialists can retrieve and interpret insights. Glean’s structured query agents allow organizations to streamline this process.

Users can interact directly with BigQuery data using either a traditional SQL interface or a natural language interface. This approach ensures that both analysts and employees with limited technical skills can access actionable data.

Expanding Data Access and Interface Design

Structured query agents provide two distinct methods for interacting with data. The SQL interface caters to data engineers and analysts who need precise control over queries, enabling tasks such as parameterized reporting, auditing, and detailed data-quality checks.

Users can craft complex queries and receive results directly within Glean’s platform without switching between tools.

For employees without SQL expertise, the natural language interface allows questions to be asked in plain English. Queries are translated into SQL via Google’s Conversational Analytics API, and results are returned in a straightforward, readable format.

This dual interface reduces reliance on specialized teams and accelerates insight generation. Glean states, “The new structured query agents allow anyone in an organization to access real-time insights from BigQuery data without switching platforms or needing advanced SQL knowledge.”

Business Relevance and Use Cases

The structured query agents support a range of enterprise workflows. Users can automate reporting, monitor key metrics, and incorporate insights into operational decisions. This integration reduces the friction between data collection and decision-making.

Teams across marketing, finance, operations, and other departments can retrieve and interpret data without waiting for manual extraction or analysis from data teams.

Automation is also enhanced through the platform. Insights can trigger notifications, generate reports, or feed into dashboards, improving efficiency and ensuring timely communication of critical information.

By unifying SQL and natural language access in one interface, Glean enables organizations to maximize the utility of their structured data while minimizing the overhead of traditional data querying processes.

Glean’s structured query agents bring enterprise data closer to everyday users. By offering multiple access methods and integrating seamlessly with BigQuery, the platform strengthens organizational data workflows and provides consistent, actionable insights to employees at all levels.

Key Takeaways

  • Glean's new structured query agents provide real-time BigQuery insights using SQL or plain English.
  • Expand data access for both technical and non-technical users, overcoming enterprise data bottlenecks.
  • Offer dual interfaces: precise SQL control for analysts and natural language for broader employee use.
  • Enhance transparency by generating SQL from natural language queries for auditing and analysis.