Data analytics

Documentation and resources for unlocking your data’s potential and transforming it into actionable AI insights with Google Cloud products.

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Access 20+ free products for common use cases, including AI APIs, VMs, data warehouses, and more.

Explore data analytics in Google Cloud

Read documentation and Cloud Architecture Center articles about data analytics products, capabilities, and procedures.
Learn how BigQuery helps organizations to get insights into their data.
Plan your approach with Architecture Center resources across a variety of data and analytics topics.
Plan how to design an analytics lakehouse to store, process, and activate data.

Training, blog articles, and more

Go to training courses, blog articles, and other related resources.
Study Google Cloud technologies essential to the data analyst role.
Study how to explore data in Looker and set up self-serve analytics for your users.
Go from prototyping with Gemini to deploying secure, enterprise-grade agents with hands-on training and guidance from Google experts.
Choose the services to run your data and analytics workloads.

Data analytics products by use case

Expand sections or use the filter to find products and guides for typical use cases.

Use a serverless, cost-effective, and multi-cloud data and AI platform designed to help you turn big data into valuable business insights powered by Gemini.

Understand your data using a fully managed, highly scalable data platform with built-in machine learning (ML).
Ground agents by providing AI-powered, high-quality context for enterprise data assets.

Get business intelligence in real time, built on governed data, that offers repeatable analysis and inspires in-depth understanding of the data.

Maximize your data analysis investments when running analytic queries on large datasets.
Access, analyze, and act on an up-to-date, trusted version of your data.
Tell great data stories to support better business decisions.

Manage the end-to-end data lifecycle and make it easier to manage, discover, govern, and share data and AI assets.

Enable intelligent data management with unified metadata and governance and security policies.
Share data and insights at scale across organizational boundaries with a robust security and privacy framework.
Ground agents by providing AI-powered, high-quality context for enterprise data assets.
Discover and redact sensitive data.

Ingest, transform, and load data from disparate data sources in a scalable and secure fashion, and build end-to-end orchestration for the enterprise.

Automate data ingestion at scale into BigQuery without writing code, on a scheduled or ad hoc basis.
Quickly build and manage data pipelines using fully managed, code-free data integration with a graphical interface.
Securely move data in and out of Cloud Storage by using SSH File Transfer Protocol (SFTP).
Get an end-to-end experience that helps data teams build, version control, and orchestrate SQL pipelines in BigQuery.
Use a serverless and easy-to-use change data capture (CDC) and replication service for real-time data ingestion.
Create, schedule, monitor, and manage workflows using a fully managed orchestration service built on Apache Airflow.
Transfer data between Cloud Storage services such as AWS S3 and Cloud Storage.
Ship large volumes of data to Google Cloud using rackable storage.
A unified, declarative orchestration and automated deployment framework optimized for seamlessly managing data and AI pipelines on Google Cloud.

Build an open, managed, high-performance lakehouse that provides a single source of truth, eliminating data duplication and ensuring consistent insights.

Unite Google Cloud and open source services to create a lakehouse for advanced analytics and AI.

Migrate your lakehouse or warehouse to BigQuery with easy to use tools powered by Gemini that assist in every phase of migration.

Learn about general concepts and a framework that you can use to organize and structure your migration to BigQuery.
Learn about the BigQuery Migration Service, which is a comprehensive solution for migrating your data warehouse or lakehouse to BigQuery.

Empower your data journey, from robust batch processing using managed Apache Spark and Apache Hadoop, to dynamic real-time stream processing with serverless, scalable pipelines using Apache Beam.

Develop real-time batch and streaming data processing pipelines.
A fully managed Apache Hive metastore (HMS) that runs on Google Cloud.
Perform batch processing, querying, and streaming using a managed Apache Spark and Apache Hadoop service.

Ingest, process, and analyze event streams in real time, and generate actionable, real-time insights.

Develop real-time batch and streaming data processing pipelines.
Use a managed cloud service that lets you ingest Apache Kafka streams directly into Google Cloud.
Ingest event streams from anywhere, at any scale.

Seamlessly integrate the power of generative AI and machine learning directly within your data to unlock deeper insights.

Build and train machine learning (ML) models directly using SQL queries.
Deploy and manage complete machine learning (ML) pipelines.
Use AI-powered assistance to help you work with your data in BigQuery.
Get AI-powered assistance to help you work with your data in Looker.
Manage your datasets, run queries, and deploy data pipelines directly from your preferred IDE or CLI.
Ground agents by providing AI-powered, high-quality context for enterprise data assets.
Build and use generative AI using a fully managed, unified AI development platform.
Get indexed blockchain data made available through BigQuery for easy analysis through SQL.
Get reference architectures, packaged solution deployment content, and integration services to kickstart your data and AI cloud journey with open source Cortex Framework.
Learn about Google Earth Engine, which is a geospatial processing service. With Earth Engine, you can perform geospatial processing at scale, powered by Google Cloud.
Use an end-to-end solution that delivers scalable and seamless connectivity between the factory floor and the cloud.