According to Google’s Data and AI Trends Report 2024, 84% of organizations believe that generative AI will expedite their access to insights, and notably 52% of non-technical users are already leveraging generative AI to extract valuable insights.
With Google’s Data Cloud, we’re on a mission to bring our decades of research and investments in AI to revolutionize data management and analytics, enabling organizations to reimagine experiences and build data agents grounded in their proprietary data. At Google Cloud Next 2024, we introduced the preview of Gemini in BigQuery, which delivers AI-powered experiences such as data discovery and exploration, data preparation and engineering, analysis and insight generation covering the data journey, as well as intelligent recommendations to enhance user productivity and optimize costs.
“Gemini in BigQuery has transformed our query generation process. The integration into BigQuery makes it easy to generate SQL templates and has helped boost the efficiency of our label and feature engineering, including crucial machine learning model monitoring queries. Gemini’s ability to understand complex data structures and deliver accurate queries has made our workflow smoother and faster than ever.” – Martijn Wieriks, Chief Data Officer, Julo
Today, we are announcing general availability of several Gemini in BigQuery features, including SQL code generation and explanation, Python code generation, data canvas, data insights and partitioning, and clustering recommendations.
Let’s take a closer look at some of the functionality you can enjoy today with Gemini in BigQuery.
What makes Gemini in BigQuery different?
Gemini in BigQuery brings the best of Google’s capabilities across data management and AI infrastructure with state-of-the-art models optimized for your business needs.
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Context aware: decodes your intent, understands your goals and proactively engages with you to accelerate your workflows
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Grounded in your data: continuously learns and adapts to your business data to uncover new opportunities and anticipate issues
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Integrated experience: directly accessible within the BigQuery interface, providing a seamless experience across the analytics workflows
Getting started with data insights
The data analysis journey first begins with data discovery and assessing which insights you can get from your data assets. Imagine having a library of insightful questions tailored specifically to your data – questions you didn’t even know you should ask! Data Insights eliminates the guesswork with pre-validated, ready-to-run queries offering immediate insights. For instance, if you’re working with a table containing customer churn data, Data Insights might prompt you to explore the factors contributing to churn within specific customer segments — an angle you might not have thought to investigate.
These actionable queries are built into BigQuery Studio, providing the insights, right where you need them, to advance your analysis with a single-click.
