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探索 Google Cloud中的数据分析和流水线
阅读有关数据分析和流水线产品、功能和流程的文档和 Cloud Architecture Center 文章。
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最后更新时间 (UTC)：2025-02-16。
[[["易于理解","easyToUnderstand","thumb-up"],["解决了我的问题","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["很难理解","hardToUnderstand","thumb-down"],["信息或示例代码不正确","incorrectInformationOrSampleCode","thumb-down"],["没有我需要的信息/示例","missingTheInformationSamplesINeed","thumb-down"],["翻译问题","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["最后更新时间 (UTC)：2025-02-16。"],[[["\u003cp\u003eExplore a variety of data analytics and pipeline solutions in Google Cloud, including products, capabilities, and recommended procedures.\u003c/p\u003e\n"],["\u003cp\u003eLearn how to load data into BigQuery, including batch loading and streaming, and discover resources to plan your data and analytics approach.\u003c/p\u003e\n"],["\u003cp\u003eAccess training courses, blog articles, and learning paths to study essential data analyst technologies and BI analytics with Looker.\u003c/p\u003e\n"],["\u003cp\u003eLeverage products and guides for typical data analytics and pipeline use cases, covering areas such as data analysis, governance, ingestion, orchestration, and processing.\u003c/p\u003e\n"],["\u003cp\u003eUtilize additional resources like Vertex AI, Blockchain Analytics, Dataprep by Trifacta, Cortex Framework, and Manufacturing Data Engine to enhance data-driven decision-making and insights.\u003c/p\u003e\n"]]],[],null,["# Data analytics\n==============\n\nDocumentation and resources for unlocking your data's potential and transforming it into actionable AI insights with Google Cloud products.\n[Get started for free](https://console.cloud.google.com/freetrial) \n\n#### Start your proof of concept with $300 in free credit\n\n- Get access to Gemini 2.0 Flash Thinking\n- Free monthly usage of popular products, including AI APIs and BigQuery\n- No automatic charges, no commitment \n[View free product offers](/free/docs/free-cloud-features#free-tier) \n\n#### Keep exploring with 20+ always-free products\n\n\nAccess 20+ free products for common use cases, including AI APIs, VMs, data warehouses,\nand more.\n\nExplore data analytics in Google Cloud\n--------------------------------------\n\nRead documentation and Cloud Architecture Center articles about data analytics products, capabilities, and procedures. \n[description](/bigquery/docs/introduction) \n\n### [Introduction to BigQuery](/bigquery/docs/introduction)\n\nLearn how BigQuery helps organizations to get insights into their data.[open_in_new](/bigquery/docs/introduction) \n[account_tree](/architecture/big-data-analytics) \n\n### [Data and analytics resources](/architecture/big-data-analytics)\n\nPlan your approach with Architecture Center resources across a variety of data and analytics topics.[open_in_new](/architecture/big-data-analytics) \n[account_tree](/architecture/big-data-analytics/analytics-lakehouse) \n\n### [Jump Start Solution: Analytics lakehouse](/architecture/big-data-analytics/analytics-lakehouse)\n\nPlan how to design an analytics lakehouse to store, process, and activate data.[open_in_new](/architecture/big-data-analytics/analytics-lakehouse)\n\nTraining, blog articles, and more\n---------------------------------\n\nGo to training courses, blog articles, and other related resources. \n[school](https://www.cloudskillsboost.google/paths/18) \n\n### [Data analyst learning path](https://www.cloudskillsboost.google/paths/18)\n\nStudy Google Cloud technologies essential to the data analyst role.[open_in_new](https://www.cloudskillsboost.google/paths/18) \n[school](https://www.cloudskillsboost.google/paths/28) \n\n### [BI and analytics with Looker learning path](https://www.cloudskillsboost.google/paths/28)\n\nStudy how to explore data in Looker and set up self-serve analytics for your users.[open_in_new](https://www.cloudskillsboost.google/paths/28) \n[cloud](https://cloud.google.com/blog/products/data-analytics/decision-tree-for-data-analytics-workloads-on-google-cloud) \n\n### [Decision tree for data and analytics workloads](https://cloud.google.com/blog/products/data-analytics/decision-tree-for-data-analytics-workloads-on-google-cloud)\n\nChoose the services to run your data and analytics workloads.[open_in_new](/blog/products/data-analytics/decision-tree-for-data-analytics-workloads-on-google-cloud)\n\nData analytics products by use case\n-----------------------------------\n\nExpand sections or use the filter to find products and guides for typical use cases. \n\n### Data and AI platform\n\n\nUse 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. \n\n#### [BigQuery](/bigquery/docs)\n\nUnderstand your data using a fully managed, highly scalable data platform with built-in machine learning (ML).\n\n### Data analysis\n\n\nGet business intelligence in real time, built on governed data, that offers repeatable analysis and inspires in-depth understanding of the data. \n\n#### [BigQuery analytics](/bigquery/docs/query-overview)\n\nMaximize your data analysis investments when running analytic queries on large datasets. \n\n#### [Looker](/looker/docs)\n\nAccess, analyze, and act on an up-to-date, trusted version of your data. \n\n#### [Looker Studio](/looker/docs/studio)\n\nTell great data stories to support better business decisions.\n\n### Data governance and sharing\n\n\nManage the end-to-end data lifecycle and make it easier to manage, discover, govern, and share data and AI assets. \n\n#### [Unified governance in BigQuery](/bigquery/docs/data-governance)\n\nEnable intelligent data management with unified metadata and governance and security policies. \n\n#### [BigQuery sharing](/bigquery/docs/analytics-hub-introduction)\n\nShare data and insights at scale across organizational boundaries with a robust security and privacy framework. \n\n#### [Dataplex Universal Catalog](/dataplex/docs)\n\nUnify distributed data, automate data management and governance, and enable data discovery and quality checks across various Google Cloud and third party sources. \n\n#### [Sensitive Data Protection](/sensitive-data-protection/docs)\n\nDiscover and redact sensitive data. \n\n#### [Data Catalog](/data-catalog/docs)\n\nDiscover and understand your data using a fully managed and scalable data discovery and metadata management service. (Deprecated)\n\n### Data integration and orchestration\n\n\nIngest, transform, and load data from disparate data sources in a scalable and secure fashion, and build end-to-end orchestration for the enterprise. \n\n#### [BigQuery Data Transfer Service](/bigquery/docs/dts-introduction)\n\nAutomate data ingestion at scale into BigQuery without writing code, on a scheduled or ad hoc basis. \n\n#### [Cloud Composer](/composer/docs)\n\nCreate, schedule, monitor, and manage workflows using a fully managed orchestration service built on Apache Airflow. \n\n#### [Cloud Data Fusion](/data-fusion/docs)\n\nQuickly build and manage data pipelines using fully managed, code-free data integration with a graphical interface. \n\n#### [Dataform](/dataform/docs)\n\nGet an end-to-end experience that helps data teams build, version control, and orchestrate SQL pipelines in BigQuery. \n\n#### [Datastream](/datastream/docs)\n\nUse a serverless and easy-to-use change data capture (CDC) and replication service for real-time data ingestion. \n\n#### [Storage Transfer Service](/storage-transfer/docs/overview)\n\nTransfer data between Cloud Storage services such as AWS S3 and Cloud Storage. \n\n#### [Transfer Appliance](/transfer-appliance/docs/4.0/overview)\n\nShip large volumes of data to Google Cloud using rackable storage.\n\n### Data migration\n\n\nMigrate your lakehouse or warehouse to BigQuery with easy to use tools powered by Gemini that assist in every phase of migration. \n\n#### [Overview: Migrate data warehouses to BigQuery](/bigquery/docs/migration/migration-overview)\n\nLearn about general concepts and a framework that you can use to organize and structure your migration to BigQuery. \n\n#### [BigQuery Migration Service](/bigquery/docs/migration-intro)\n\nLearn about the BigQuery Migration Service, which is a comprehensive solution for migrating your data warehouse or lakehouse to BigQuery.\n\n### Data processing\n\n\nEmpower 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. \n\n#### [Dataflow](/dataflow/docs)\n\nDevelop real-time batch and streaming data processing pipelines. \n\n#### [Dataproc](/dataproc/docs)\n\nPerform batch processing, querying, and streaming using a managed Apache Spark and Apache Hadoop service. \n\n#### [Dataproc Serverless](/dataproc-serverless/docs)\n\nUse Dataproc Serverless to run Apache Spark batch workloads without provisioning and managing your own cluster.\n\n### Streaming\n\n\nIngest, process, and analyze event streams in real time, and generate actionable, real-time insights. \n\n#### [Dataflow](/dataflow/docs)\n\nDevelop real-time batch and streaming data processing pipelines. \n\n#### [Google Cloud Managed Service for Apache Kafka](/managed-service-for-apache-kafka/docs)\n\nUse a managed cloud service that lets you ingest Apache Kafka streams directly into Google Cloud. \n\n#### [Pub/Sub](/pubsub/docs)\n\nIngest event streams from anywhere, at any scale.\n\n### AI and ML\n\n\nSeamlessly integrate the power of generative AI and machine learning directly within your data to unlock deeper insights. \n\n#### [BigQuery ML](/bigquery/docs/bqml-introduction)\n\nBuild and train machine learning (ML) models directly using SQL queries. \n\n#### [Dataflow](/dataflow/docs/machine-learning)\n\nDeploy and manage complete machine learning (ML) pipelines. \n\n#### [Gemini in BigQuery](/gemini/docs/bigquery/overview)\n\nUse AI-powered assistance to help you work with your data in BigQuery. \n\n#### [Gemini in Looker](/gemini/docs/looker/overview)\n\nGet AI-powered assistance to help you work with your data in Looker.\n\n### Related products, guides, and sites\n\n#### [Vertex AI](/vertex-ai/docs)\n\nBuild and use generative AI using a fully managed, unified AI development platform. \n\n#### [Blockchain Analytics](/blockchain-analytics/docs)\n\nGet indexed blockchain data made available through BigQuery for easy analysis through SQL. \n\n#### [Cortex Framework](/cortex/docs)\n\nGet reference architectures, packaged solution deployment content, and integration services to kickstart your data and AI cloud journey. \n\n#### [Earth Engine](https://developers.google.com/earth-engine)\n\nLearn about Google Earth Engine, which is a geospatial processing service. With Earth Engine, you can perform geospatial processing at scale, powered by Google Cloud. \n\n#### [Manufacturing Data Engine](/manufacturing-data-engine/docs)\n\nUse an end-to-end solution that delivers scalable and seamless connectivity between the factory floor and the cloud."]]