AI data analytics
Write SQL, build predictive models, and visualize data with AI data analytics
Use foundational models and chat assistance for predictive analytics, sentiment analysis, and AI-enhanced business intelligence.
New customers get $300 in free credits to try AI data analytics in BigQuery Studio.
Overview
What is AI data analytics?
AI data analytics refers to the practice of using artificial intelligence (AI) to analyze large data sets, simplify and scale trends, and uncover insights for data analysts.
How can AI be used with data analytics?
AI data analytics is designed to support, automate, and simplify each stage of the data analysis journey. AI tools can help with data collection (ingesting from multiple sources) and preparation (cleaning and organizing for analysis). Machine learning (ML) models can be trained and applied on prepared data to extract insights and patterns. Finally, AI can help analysts interpret trends and insights for more informed decision-making.
How can data analysts use AI data analytics?
Data analysts across industries can use AI data analytics to enhance their work. From real-time credit card fraud detection and assisting in disease diagnosis to demand forecasting in retail and propensity modeling for gaming apps, AI data analytics can assist with all types of industry-specific use cases.
Can AI do the work of a data analyst?
AI data analytics is designed to enhance the core contributions and skill sets of data analysts. Given their subject matter expertise, critical thinking abilities, and the capacity to pose insightful queries, data analysts are critical to the success of any AI-assisted data analysis.
How It Works
BigQuery Studio provides a single, unified interface for all data practitioners to simplify analytics workflows from data preparation and visualization to ML model creation and training. Using simple SQL, access Vertex AI foundational models and chat assist directly in BigQuery for a variety of data analytics use cases.
BigQuery Studio provides a single, unified interface for all data practitioners to simplify analytics workflows from data preparation and visualization to ML model creation and training. Using simple SQL, access Vertex AI foundational models and chat assist directly in BigQuery for a variety of data analytics use cases.
Common Uses
AI-powered predictive analytics and forecasting
Build predictive and forecasting models using SQL and AI
Leverage your existing SQL skills to build, train, and deploy batch predictive models directly within BigQuery or your chosen data warehouse with BigQuery ML. Plus, BigQuery ML integrates with Vertex AI, our end-to-end platform for AI and ML, broadening your access to powerful models that generate real-time, low-latency online predictions, including identifying new audiences based on current customer lifetime value, recommending personalized investment products, and forecasting demand.
How-tos
Build predictive and forecasting models using SQL and AI
Leverage your existing SQL skills to build, train, and deploy batch predictive models directly within BigQuery or your chosen data warehouse with BigQuery ML. Plus, BigQuery ML integrates with Vertex AI, our end-to-end platform for AI and ML, broadening your access to powerful models that generate real-time, low-latency online predictions, including identifying new audiences based on current customer lifetime value, recommending personalized investment products, and forecasting demand.
Sentiment analysis
Run sentiment analysis on datasets using BigQuery ML
From understanding customer feedback on social media or product reviews to developing market research through competitor analysis and campaign effectiveness, data analysts use sentiment analysis to parse positive, negative, and neutral scores on their datasets. With BigQuery ML, you use SQL to train models to automatically run sentiment analysis and predictions for stronger insights, including customer pain points, product feature enhancements, and more.
How-tos
Run sentiment analysis on datasets using BigQuery ML
From understanding customer feedback on social media or product reviews to developing market research through competitor analysis and campaign effectiveness, data analysts use sentiment analysis to parse positive, negative, and neutral scores on their datasets. With BigQuery ML, you use SQL to train models to automatically run sentiment analysis and predictions for stronger insights, including customer pain points, product feature enhancements, and more.
Image and video analysis
Analyze unstructured data images and videos with AI
Effortlessly analyze images and videos to extract valuable information, streamline processes, and enhance decision-making with Google Cloud AI. To analyze unstructured data in images, use remote functions in BigQuery like Vertex AI Vision or perform inference on unstructured image data with BigQuery ML. For video analysis, Video Description on Vertex AI summarizes short video clip content, providing detailed metadata about videos for storing and searching.
How-tos
Analyze unstructured data images and videos with AI
Effortlessly analyze images and videos to extract valuable information, streamline processes, and enhance decision-making with Google Cloud AI. To analyze unstructured data in images, use remote functions in BigQuery like Vertex AI Vision or perform inference on unstructured image data with BigQuery ML. For video analysis, Video Description on Vertex AI summarizes short video clip content, providing detailed metadata about videos for storing and searching.
AI assistance for SQL generation and completion
Write queries, SQL, and code with Gemini in BigQuery
Gemini in BigQuery provides AI-powered assistive and collaboration features including help with writing and editing SQL or Python code, visual data preparation, and intelligent recommendations for enhancing productivity and optimizing costs. You can leverage BigQuery’s in-console chat interface to explore tutorials, documentation, and best practices for specific tasks using simple prompts such as: “How can I use BigQuery materialized views?” “How do I ingest JSON data?” and “How can I improve query performance?”
How-tos
Write queries, SQL, and code with Gemini in BigQuery
Gemini in BigQuery provides AI-powered assistive and collaboration features including help with writing and editing SQL or Python code, visual data preparation, and intelligent recommendations for enhancing productivity and optimizing costs. You can leverage BigQuery’s in-console chat interface to explore tutorials, documentation, and best practices for specific tasks using simple prompts such as: “How can I use BigQuery materialized views?” “How do I ingest JSON data?” and “How can I improve query performance?”
AI-enhanced data visualization
Use AI chat to derive data insights, generate reports, and visualize trends
Gain insights and build data-powered applications with AI-powered business intelligence from Looker. Using Gemini in Looker, chat directly with your data to uncover business opportunities, create entire reports or advanced visualizations, and build formulas for calculated fields—all with only a few sentences of conversational instruction.
How-tos
Use AI chat to derive data insights, generate reports, and visualize trends
Gain insights and build data-powered applications with AI-powered business intelligence from Looker. Using Gemini in Looker, chat directly with your data to uncover business opportunities, create entire reports or advanced visualizations, and build formulas for calculated fields—all with only a few sentences of conversational instruction.
Natural language-driven analysis
Discover, transform, query, and visualize data using natural language
Reimagine your data analysis experience with the AI-powered BigQuery data canvas. This natural language centric tool simplifies the process of finding, querying, and visualizing your data. Its intuitive features help you discover data assets quickly, generate SQL queries, automatically visualize results, and seamlessly collaborate with others—all within a unified interface.
How-tos
Discover, transform, query, and visualize data using natural language
Reimagine your data analysis experience with the AI-powered BigQuery data canvas. This natural language centric tool simplifies the process of finding, querying, and visualizing your data. Its intuitive features help you discover data assets quickly, generate SQL queries, automatically visualize results, and seamlessly collaborate with others—all within a unified interface.
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New customers get $300 in free credits to spend on BigQuery
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