Empowers business users with conversational data agents
Reduces SQL bottlenecks to help speed up daily decision-making
Accelerates business planning and operational decision-making for the teams using it
Supports data governance through layered security controls
Best Buy empowers users to explore BigQuery data using conversational agents, accelerating forecasting and decision-making.
Best Buy empowers users to explore BigQuery data using conversational agents, accelerating forecasting and decision-making.
Modernizing enterprise data access to accelerate
retail decision-making
BigQuery provides us with a cloud data platform that supports both accessibility and security at scale. By automating parts of our Google Cloud environment, our team has been able to reduce technical friction and give business users more room to focus on discovering value rather than managing infrastructure.
Kishor Patil
Senior Manager, Cloud Engineering, Best Buy
Across several business teams at Best Buy, existing reports could not always answer specific questions. Over time, Best Buy built a strong data analytics environment, enabling technical analysts to construct automated data pipelines across diverse enterprise domains. But when teams needed answers beyond existing reports, they often relied on technical colleagues to write SQL queries or build custom dashboards. The process for requesting those queries or dashboards worked, but it could slow the follow-up analysis needed as new questions came up. Best Buy wanted to make it easier and faster for business teams to explore data without losing the access and security controls required for its cloud environment. The company already used BigQuery for its data and analytics work, so its Google Cloud platform team looked at conversational analytics as a way to build on that existing foundation.
Implementing conversational analytics in BigQuery has provided business teams with a way to ask questions in natural language and continue exploring through follow-up questions. It reduces the need to request a new query or dashboard each time, while keeping the work connected to data and controls already in place.
Democratizing insights through natural language conversational data agents
With conversational analytics, business users can engage in natural language and explore the data they already have access to. It's reduced how often they need to depend on engineering teams for technical SQL support, which has made our business teams more self-sufficient in how they work.
Kishor Patil
Senior Manager, Cloud Engineering, Best Buy
Best Buy deployed intelligent conversational data agents that interface directly with enterprise BigQuery datasets which have enabled business users across the organization to query complex data using natural language, removing the operational friction of manual SQL authoring or complex data modeling requirements. This deployment allows business teams to interact with live data in an ongoing, multi-turn dialogue. Rather than simply reviewing a static dashboard and walking away, teams can ask intuitive follow-up questions to explore unexpected trends, diagnose root business drivers, and refine strategic plans in real time.
This shift has been particularly impactful for teams that previously relied on scheduled reports or waited days for custom dashboards.
Teams across the organization can explore data independently, ask follow-up questions, and arrive at decisions with greater confidence and speed.
This conversational capability has reduced dependencies on technical data teams and shortened decision cycles for the business teams involved, transforming everyday data exploration into a more agile, self-service experience for the teams using it.
Ensuring enterprise governance, data accuracy, and cost observability
Deploying enterprise generative AI into active production required Best Buy to address critical operational challenges around data integrity and access governance. To support high analytical accuracy and maintain response quality, the team worked closely with Google Cloud engineering to refine underlying knowledge sources, implement guardrails, and validate query results against established historical sales records.
Best Buy also architected a multi-layered security framework, which included:
- Implementing enterprise-grade access controls aligned with corporate governance standards for conversational agents alongside direct authorization for underlying BigQuery datasets.
- Utilizing role-based access management to help govern access across teams, restricting agent creation to platform admins while granular resource-level sharing limits distribution to authorized teams.
- Safeguarding sensitive information with data protection controls while supporting self-service analytics, to protect sensitive attributes.
The validation approach has improved response accuracy and built confidence among business teams, which has accelerated adoption of conversational analytics.
Through disciplined internal engineering and security practices, supported by Google Cloud, Best Buy moved conversational analytics into production for key planning workflows, creating a scalable enterprise model for secure, cost-effective AI innovation.
Security was a core part of how we designed this new capability. Through layered access controls, combined with data-level protections, we can help ensure business teams interact with data appropriate to their role, which supports our broader approach to governance in a self-service environment.
Kishor Patil
Senior Manager, Cloud Engineering, Best Buy
Best Buy is a leading provider of consumer technology products and services, operating hundreds of stores and digital channels across North America to enrich lives through technology.
Industry: Retail
Location: United States
Products: BigQuery, Conversational Analytics
