包阅导读总结
1. 关键词：Gemini in BigQuery、Google、Data Cloud、AI、Data Insights
2. 总结：Google 的 Data and AI Trends Report 指出生成式 AI 作用显著，谷歌云推出 Gemini in BigQuery 预览，现其部分功能已全面可用，它能带来 AI 驱动体验，改变数据管理和分析，提升效率。
3. 主要内容：
– Google 的报告显示多数组织认为生成式 AI 可加速获取洞察，不少非技术用户已利用其提取价值
– 谷歌数据云致力于用 AI 变革数据管理和分析，云大会上介绍 Gemini in BigQuery 预览，覆盖数据旅程并提供智能推荐
– 如今 Gemini in BigQuery 的多项功能如 SQL 代码生成等已全面可用
– 它具有诸多优势，如能理解意图、基于数据学习、提供集成体验
– 数据分析从数据发现开始，Data Insights 提供预验证查询消除猜测，在 BigQuery Studio 中提供洞察
思维导图：
文章地址：https://cloud.google.com/blog/products/data-analytics/gemini-in-bigquery-features-are-now-ga/
文章来源：cloud.google.com
作者：Deepak Dayama,Honza Fedak
发布时间：2024/8/29 0:00
语言：英文
总字数：993字
预计阅读时间：4分钟
评分：90分
标签：BigQuery,Gemini,生成式 AI,数据分析,SQL 代码生成
以下为原文内容
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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.
