Systems | Development | Analytics | API | Testing

Did you know that BigQuery can run GQL queries? BigQuery Graph easily uncovers connections in your datasets, alongside your relational SQL queries.

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.

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.

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.

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.

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.

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!

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.

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.

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.