Data agents: Automated and accelerated

Year: 2025 · ▶ Watch on YouTube

Jeff Nelson (Developer Advocate)

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Segments (5)

  • 00:00:05 · Introduction to Data Agents — Jeff Nelson
    • The speaker introduces the challenge of working with raw data and sets up the presentation on how new Data Science Agents can help.
  • 00:41:00 · Demo: Building a Sales Forecast — Jeff Nelson
    • The demo begins in a BigQuery notebook, showing how to query and prepare sales data using SQL and Python (BigFrames).
  • 01:55:00 · Demo: Using the Gemini Data Science Agent — Jeff Nelson
    • The speaker uses a natural language prompt to instruct the built-in Gemini agent to perform feature engineering and generate a sales forecast.
  • 03:51:00 · Demo: Creating a Data App — Jeff Nelson
    • With a single click, the speaker turns the notebook’s visualization into a fully deployed, interactive, and shareable web application.
  • 04:54:00 · Announcing More Data Agents — Jeff Nelson
    • The speaker announces the launch of specialized agents for data engineering and conversational analytics, expanding the agent ecosystem.

Products Announced (6)

  • 00:28 · Data Science Agent in BigQuery (New)
    • Turns raw data into data apps using natural language. · Integrates directly into BigQuery notebooks. · Collaborative chat-based interface.
    • Coming soon to BigQuery notebooks.
  • 02:27 · Serverless Spark engine in BigQuery (New)
    • Run Spark code directly within BigQuery. · Seamlessly switch between SQL, Spark, and Python. · No infrastructure management required.
    • Available now.
  • 02:55 · TimesFM Foundation Model (New)
    • Pre-trained on massive time-series datasets for forecasting. · Accessible directly in BigQuery via the AI.FORECAST function. · Generates forecasts with confidence intervals without model training.
    • Available now in BigQuery.
  • 03:53 · Data App creation from BigQuery Notebooks (New)
    • One-click creation of shareable web apps from notebook cells. · Automatically packages assets and provides an external link. · Requires no application development experience.
    • Available now.
  • 04:55 · Data Engineering Agent (Preview)
    • Specialized agent for data engineering tasks.
    • In Preview.
  • 04:55 · Conversational Analytics Agent (Preview)
    • Specialized agent for data analysts and business users.
    • In Preview.

Demos (1)

  • 00:41:00 ✓ · Building a Sales Forecast App with Data Agents — Jeff Nelson
    • The entire workflow from a raw data table in BigQuery to a fully deployed, interactive forecasting web application was demonstrated, using a combination of SQL, Python, the Gemini Data Science Agent, and a one-click app creation feature.

Notable Quotes (3)

  • 00:22:00 — Jeff Nelson:

    I know firsthand just how hard it is to turn that raw data into something useful.

  • 03:48:00 — Jeff Nelson:

    But here’s a secret: I don’t really like building apps.

  • 04:32:00 — Jeff Nelson:

    Now that’s powerful.

Visual Signals

On-screen (5)

  • 00:05:00 · Data agents: Automated and accelerated
    • This is the official title of the presentation.
  • 00:11:00 · Jeff Nelson Developer Advocate Google Cloud
    • Identifies the speaker and his role.
  • 04:35:00 · A flowchart showing: Raw data -> Data science agent -> Data application
    • Visually summarizes the end-to-end workflow demonstrated.
  • 04:55:00 · An expanded flowchart showing 'Data engineering agent' and 'Conversational analytics agent' in previ
    • Announces the new specialized agents and their preview status.
  • 05:03:00 · Try the Data Science Agent in Colab [QR Code] goo.gle/data-science-agent
    • Provides a direct call to action for the audience to try the technology.

Stage (2)

  • 00:07:00 · Jeff Nelson walks onto the main stage to applause.
  • 04:35:00 · The audience applauds after the successful completion of the end-to-end demo.

Visual demos (6)

  • 00:42:00 · BigQuery Notebook UI
    • A Colab-style notebook interface inside the Google Cloud console. The speaker pastes and runs SQL and Python code in cells.
  • 01:38:00 · Data Visualization in Notebook
    • The notebook output switches from a data table to a ‘Chart’ view, displaying a line graph of sales trends and a bar chart of sales by state.
  • 01:57:00 · Gemini Data Science Agent Chat
    • An ‘Ask Agent’ chat box appears. The speaker pastes a detailed natural language prompt asking the agent to generate a sales forecast.
  • 02:05:00 · Agent Code Generation
    • The agent thinks and then automatically generates and inserts multiple cells of Python/Spark and SQL code to perform feature engineering and forecasting.
  • 03:54:00 · Create Data App Wizard
    • The speaker clicks a ‘Create Data app’ button, which opens a modal dialog to select cells and configure the application before deployment.
  • 04:15:00 · Deployed Data Application
    • A new browser tab opens with a URL, showing the final, interactive web application. The app has dropdown filters and the forecast chart, which can be used by non-technical users.

Key Topics

Data Agents · Generative AI · Google BigQuery · Data Science · Sales Forecasting · Time-Series Analysis · Serverless Spark · Data Applications · Low-Code Development · Natural Language Processing · Gemini · Foundation Models · Data Visualization

Takeaways

  • Google is launching ‘Data Agents’ powered by Gemini to automate complex data workflows directly within BigQuery.
  • The new Data Science Agent uses natural language to generate code for data preparation, analysis, and model building, drastically reducing manual effort.
  • BigQuery now features a serverless Spark engine, allowing seamless use of SQL, Spark, and Python in a unified environment.
  • A new foundation model, TimesFM, is now available in BigQuery for high-quality, pre-trained time-series forecasting without needing to train a model.
  • Users can convert notebook visualizations into shareable, interactive data applications with a single click, democratizing access to data insights.
  • The entire process from raw data to a deployed application is streamlined into a single, integrated workflow within the Google Cloud ecosystem.
  • Google is expanding its agent offerings with specialized agents for Data Engineering and Conversational Analytics, currently in preview.