Looker (Google Cloud)
Smart data, secure decisions: Your AI-driven business intelligence with Google Gemini and the Agentic Data Cloud
Looker is the cloud-native business intelligence platform from Google Cloud. It offers companies a flexible semantic layer, AI-powered analytics with Gemini, and powerful data visualization tools for informed, data-driven decisions.
Independent B2B performance index (0–100 points). It is calculated mathematically and without subjective influence from four verified pillars: company stability, aggregated feedback from publicly available online sources, documented compliance certifications, and operational transparency.
Headquarters
1600 Amphitheatre Parkway, 94043 Mountain View, United States
Employees
188000
Founded
2010
Management
Anita Kuba
Overview
Looker (Google Cloud) is a leading business intelligence and data platform that serves as the central experience layer of the Google Agentic Data Cloud. Founded in 2010 and headquartered in Mountain View, California, Looker is now fully integrated into the Google ecosystem, which employs over 188,000 people worldwide. The platform enables companies to transform raw data into a unified, governed, and intelligent data hub to make informed, data-driven decisions. Looker stands out for its cloud-native infrastructure and a flexible semantic layer that creates a 'Single Source of Truth' for the entire enterprise. Through deep integration of Gemini AI and Google Cloud technologies like BigQuery, Looker offers advanced features for self-service analytics, interactive dashboards, and embedded analytics. Developers benefit from a powerful IDE for data modeling as well as extensive APIs to build custom data applications. Security and governance are paramount in Looker. The platform supports Single Sign-On (SSO) via Google Cloud IAM, offers private network configurations, and is ISO 27001 certified. Looker supports a variety of languages, including German, English, Portuguese, Korean, and Traditional Chinese, facilitating global deployment in multinational corporations.
Core features
Compliance & security
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🚀 Product updates & press releases
Google Cloud is driving the modernization of its business intelligence platform, Looker, to optimize data-driven decisions through deeper system integrations and AI-powered features. The focus of current updates is on expanding the Looker Semantic Layer for third-party tools like Tableau and Microsoft Power BI, as well as deeper integration of Gemini AI for automated report generation. Through global infrastructure expansions in new Google Cloud regions and compliance with strict security standards, the offering is increasingly targeted at global enterprise customers in regulated B2B markets. These innovations strengthen Looker's positioning as a central data platform and expand its application possibilities for diverse target groups.
- •Connectivity Expansion: The Looker Semantic Layer now supports leading BI tools like Tableau and Microsoft Power BI for consistent data metrics across platform boundaries.
- •AI-Powered Analytics: Deep integration of Gemini in Looker enables B2B users to create reports, queries, and formulas using natural language.
- •Global Expansion: The deployment of Looker instances in additional Google Cloud regions guarantees local data residency and reduced latency.
- •Security and Compliance: Optimized security controls facilitate privacy-compliant deployment of the platform in highly regulated industries such as finance and healthcare.
- •Developer Tools: New API interfaces and optimized Git integration accelerate the deployment and management of complex data models.
Source: Publicly available product updates or press releases from Looker (Google Cloud).
📰 Social media feedback about the product
Since no specific social media mentions or data on Looker (Google Cloud) were provided for this analysis, a content-based evaluation of user sentiment is not possible. No specific praise, criticism, or open questions can be identified. Accordingly, the sentiment is classified as neutral, and speculation is avoided.
- •Lack of Data: No specific posts or mentions were submitted for evaluation.
- •No Content Takeaways: Statements regarding features, issues, comparisons, or target groups cannot be made due to a lack of data.
Source: Publicly available social media posts (X/Twitter, LinkedIn, Reddit) from the last 12 months. The opinions shown come from users and do not represent BenchTrust's assessment.
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