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By Greg Leon
New Google Earth AI models and datasets on BigQuery and Gemini Enterprise Agent Platform help to understand our planet and its communities.
BigQuery unveils new capabilities for lakehouse, knowledge graph, built-in AI, and agentic-first experiences.
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By Yan Sun
Templates in BigQuery Studio notebook gallery, now GA, help you bypass the setup phase and jump straight into discovery.
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By Candice Chen
BigQuery Graph lets data professionals model, analyze and visualize massive-scale relationships in an entirely new way.
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By Blessing Bamiduro
BigQuery Studio’s latest Gemini-powered assistant goes from being a code assistant into a fully context-aware analytics partner.
Use the Conversational Analytics API to build context-aware agents that understand natural language, query BigQuery data, and deliver answers in text, tables, and visual charts.
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By Andong Li
BigQuery autonomous embedding generation treats embeddings as a managed part of your table, making it easier to get your data AI-ready.
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By Wawrzek Hyska
The preview of global queries in BigQuery lets you query data stored in different geographic locations with a single, standard SQL query, with no ETL.
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By Vasiya Krishnan
Conversational Analytics in BigQuery in preview brings a sophisticated AI-powered reasoning engine directly into BigQuery Studio.
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By Tianxiang Gao
BigQuery gen AI functions AI.GENERATE and AI.GENERATE_TABLE are now GA, and can be used with the new AI.EMBED and AI.SIMILARITY.
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By Google Cloud Tech
Did you know that BigQuery can run GQL queries? BigQuery Graph easily uncovers connections in your datasets, alongside your relational SQL queries.
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By Google Cloud Tech
Did you know you can call a Gemini model directly from a SQL query in BigQuery? In this hands-on codelab, Ayo and Annie do exactly that, and use it to solve a real problem: converting messy, unstructured text into clean, structured data at scale. This is Episode 1 of our multi-part series where we build a fully functional, data-aware AI agent on Google Cloud. *What we cover:* Chapters: Speakers: Ayo Adedeji, Annie Wang Products Mentioned: Gemini, BigQuery.
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By Google Cloud Tech
Discover how to build a powerful data agent using ADK, BigQuery and CloudSQL. This video guides you through transforming unstructured data into structured knowledge, enabling intelligent applications. Watch along and learn how to create RAG pipelines, leverage Gemini for vector embeddings, and automate processes with Dataflow to achieve nuanced, context aware insights. Chapters: Speaker: Debi Cabrera Products Mentioned: BigQuery, CloudSQL, Agentverse, Gemini, Agent Development Kit.
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By Google Cloud Tech
You’ve moved your data to Google Cloud. Now it is time to make sure it’s accurate, secure, and cost effective. This video concludes our migration series by focusing on the critical steps following data transfer from Databricks, Teradata, Snowflake, Cloudera and many other platforms. You’ve moved your data to Google Cloud. Now it is time to make sure it’s accurate, secure, and cost effective. This video concludes our migration series by focusing on the critical steps following data transfer from Databricks, Teradata, Snowflake, Cloudera and many other platforms.
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By Google Cloud Tech
Following your migration assessment, it is time to execute the transfer of your data and SQL queries into Google Cloud. This video dives into the specific tools and services that simplify migrating workloads from Snowflake, Teradata, Cloudera, and Databricks into BigQuery, Dataproc, and Google Cloud Storage.
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By Google Cloud Tech
Embarking on a data lake or data warehouse migration to BigQuery can seem daunting, but a thorough assessment helps clarify the path forward. This video introduces Google Cloud's services and expert guidance for evaluating the cost and complexity of migrating your existing systems, providing a clear plan for your migration journey. Discover how initial assessments help estimate time, costs, and identify the best approach for a successful migration from Snowflake, Teradata, Cloudera, Databricks and more.
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By Google Cloud Tech
Transform messy JSON into a powerful AI recommendation engine, all within BigQuery. This demo showcases a low code workflow, using Data Prep's visual tools to clean raw data, BQML to generate Gemini powered vector embeddings, and a simple SQL query to find similar items. It's a look at how Google Cloud lets data analysts build end-to-end AI pipelines without complex ETL scripts. The entire project is open-source. Build it yourself!
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By Google Cloud Tech
Geospatial data is a powerful tool for gaining insights into everything from customer behavior to environmental patterns. BigQuery allows you to store and analyze this location data using standard SQL, and bringing that data into a Colab notebook gives you the flexibility to combine BigQuery's power with popular Python visualization libraries. This approach is perfect for ad-hoc or iterative analysis. In this video, we'll give you an overview of these capabilities and walk through a demo of how you can analyze and visualize your geospatial data.
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By Google Cloud Tech
BigQuery Data Engineering Agents are here to help data analysts and engineers build faster, and focus more on creative problem-solving. Lucia Subatin shows how these AI-powered agents can save your time from tedious coding, schema mapping, and manual metadata creation Speakers: Lucia Subatin Products Mentioned: AI Infrastructure, BigQuery.
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By Google Cloud Tech
Predictive analytics helps businesses move from guesswork to informed decisions—especially when it comes to inventory. Using sales data already stored in BigQuery, this demo walks through how to forecast future demand using BigQuery ML. With just a few lines of SQL, viewers see how to transform raw data, train an ARIMA model, and generate confident sales predictions without needing to export data or manage additional machine learning infrastructure.
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BigQuery is Google's serverless, highly scalable, enterprise data warehouse designed to make all your data analysts productive at an unmatched price-performance. Because there is no infrastructure to manage, you can focus on analyzing data to find meaningful insights using familiar SQL without the need for a database administrator.
Analyze all your data by creating a logical data warehouse over managed, columnar storage, as well as data from object storage and spreadsheets. Build and operationalize machine learning solutions with simple SQL. Easily and securely share insights within your organization and beyond as datasets, queries, spreadsheets, and reports. BigQuery allows organizations to capture and analyze data in real time using its powerful streaming ingestion capability so that your insights are always current, and it’s free for up to 1 TB of data analyzed each month and 10 GB of data stored.