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Google Announces New AI Agents for Data Analysis & Science
artificial-intelligence

Google Announces New AI Agents for Data Analysis & Science

Google launches six AI agents that automate data pipelines, code debugging, and conversational analytics for smarter business insights.

August 6, 2025
5 min read
@cmcky

Google launches six AI agents that automate data pipelines, code debugging, and conversational analytics for smarter business insights.

Google has introduced a suite of six AI agents designed to automate and simplify data analysis, engineering, and science tasks that have traditionally consumed significant time and effort for data teams. These agents integrate with key platforms like BigQuery, GitHub, and Spanner, and are powered by Gemini technology.

Key Highlights

  • Google launches AI agents integrated with BigQuery, GitHub, and Spanner to automate data workflows.
  • New Gemini-powered APIs enable developers to embed conversational analytics directly into applications.
  • BigQuery now supports AI-native SQL queries and vector search for enhanced data querying capabilities.
    • At the recent Google Cloud Next Tokyo event, the company revealed a comprehensive set of AI agents aimed at data engineers, scientists, analysts, and developers. This initiative aligns with Google's vision of an "agentic enterprise," where intelligent agents proactively assist users by understanding their needs and performing complex tasks without manual intervention.

    BigQuery AI Agents

    Google introduced the Data Engineering Agent within BigQuery, which can construct entire data pipelines from simple natural language prompts. For example, a user can instruct the agent to "Clean this CSV, join it with sales data, and push it into BigQuery," and the agent will execute the workflow automatically. For more advanced tasks, the Data Science Agent embedded in BigQuery Notebooks offers end-to-end model building, including visualization and reasoning capabilities.

    Conversational Analytics Agent

    The Conversational Analytics Agent has been significantly upgraded with a built-in Code Interpreter that runs Python scripts behind the scenes. Business analysts can now ask complex questions like "Segment customers by behavior in Q2," and receive the generated code, visual charts, and actionable insights—all within a secure enterprise data environment.

    Developer-Focused AI Agents

    Developers benefit from the new Gemini CLI GitHub Actions, an open-source AI agent integrated into GitHub repositories. This agent can triage issues, review pull requests, and respond to @mentions to automate specific tasks. It operates seamlessly with Google Cloud's secure Workload Identity Federation.

    Infrastructure Enhancements

    BigQuery now features an AI Query Engine that supports LLM-style queries embedded within SQL. It also introduces hybrid semantic search, vector embedding generation, and a new columnar engine for Spanner, bridging OLTP and OLAP workloads more closely than ever. Google is expanding these capabilities beyond structured data to include unstructured formats such as images, audio, and video. The Spanner columnar engine can execute analytical queries up to 200 times faster, while BigQuery supports multimodal tables that combine various data types.

    Developer APIs and Open Standards

    Google is releasing APIs that allow developers to embed conversational analytics into their own applications. The company is also adopting open standards like the Model Context Protocol to ensure interoperability with other AI tools. Most of these AI agent features are rolling out now and are available at no additional cost within existing BigQuery and Looker pricing plans.
    Source: Google Announces New AI Agents for Data Analysis & Science on August 5, 2025

    Frequently Asked Questions (FAQ)

    What are Google's new AI agents?

    Google has launched a suite of six AI agents designed to automate and simplify tasks in data analysis, engineering, and science. These agents leverage Gemini technology and integrate with platforms like BigQuery, GitHub, and Spanner.

    How do the BigQuery AI agents work?

    The Data Engineering Agent in BigQuery can create data pipelines from natural language prompts, such as cleaning data, joining datasets, and loading them into BigQuery. The Data Science Agent in BigQuery Notebooks assists with end-to-end model building, including visualization and reasoning.

    What is the Conversational Analytics Agent?

    This upgraded agent includes a Code Interpreter that runs Python scripts, allowing business analysts to ask complex questions in natural language and receive generated code, visual charts, and actionable insights.

    How do developers benefit from these new agents?

    Developers can utilize the Gemini CLI GitHub Actions, an open-source AI agent integrated into GitHub, to automate tasks like triaging issues, reviewing pull requests, and responding to @mentions, enhancing workflow efficiency.

    What infrastructure enhancements have been made?

    BigQuery now features an AI Query Engine for LLM-style SQL queries and vector search. Additionally, Spanner has a new columnar engine that aims to bridge OLTP and OLAP workloads and improve analytical query performance significantly.

    Are these AI agent features available at an additional cost?

    Most of these AI agent features are rolling out now and are available at no additional cost within existing BigQuery and Looker pricing plans.

    Crypto Market AI's Take

    Google's foray into specialized AI agents for data analysis and engineering marks a significant step towards making complex data workflows more accessible and efficient. This aligns with the broader trend of AI democratization, where powerful tools are being embedded into everyday enterprise applications. For the cryptocurrency market, where data analysis is paramount for trading, risk management, and identifying trends, such advancements can be particularly impactful. While these agents are currently focused on enterprise data, the underlying technology and principles could eventually influence tools used for analyzing on-chain data, market sentiment, and predicting crypto asset movements. The integration with platforms like GitHub also hints at a future where AI agents could assist in developing and maintaining decentralized applications (dApps) and smart contracts, potentially enhancing security and efficiency in the Web3 space. We explore how AI is shaping various aspects of finance and trading in our AI Crypto Market Platform and its related content.

    More to Read:

  • AI Agents Capabilities, Risks, and Growing Role
  • AI-Driven Crypto Trading Tools Reshape Market Strategies
  • Google Launches AI Agents for Enterprise Data Science and Engineering
Source: Google Announces New AI Agents for Data Analysis & Science on August 5, 2025