[[["容易理解","easyToUnderstand","thumb-up"],["確實解決了我的問題","solvedMyProblem","thumb-up"],["其他","otherUp","thumb-up"]],[["難以理解","hardToUnderstand","thumb-down"],["資訊或程式碼範例有誤","incorrectInformationOrSampleCode","thumb-down"],["缺少我需要的資訊/範例","missingTheInformationSamplesINeed","thumb-down"],["翻譯問題","translationIssue","thumb-down"],["其他","otherDown","thumb-down"]],["上次更新時間：2025-09-04 (世界標準時間)。"],[],[],null,["# Teradata to BigQuery migration: Introduction\n============================================\n\nThis document outlines the reasons you might migrate from Teradata to\nBigQuery, compares features between Teradata and BigQuery,\nand provides an outline of steps to begin your BigQuery migration.\n\nWhy migrate from Teradata to BigQuery?\n--------------------------------------\n\nTeradata was an early innovator in managing and analyzing substantial\ndata volumes. However, as your cloud computing needs evolve, you might require a\nmore modern solution for your data analytics.\n\nIf you have previously used Teradata, consider migrating to BigQuery\nfor the following reasons:\n\n- Overcome legacy platform constraints\n - Teradata's conventional architecture often struggles to meet the demands of modern analytics, particularly the need for unlimited concurrency and consistently high performance for diverse workloads. The serverless architecture in BigQuery is designed to handle these demands with minimal effort.\n- Adopt a cloud-native strategy\n - Many organizations are strategically moving from on-premises infrastructure to the cloud. This shift necessitates a departure from conventional, hardware-bound solutions like Teradata towards a fully managed, scalable, and on-demand service like BigQuery to reduce operational overhead.\n- Integrate with modern data sources and analytics\n - Key enterprise data increasingly resides in cloud-based sources. BigQuery is natively integrated with the Google Cloud ecosystem, providing seamless access to these sources and enabling advanced analytics, machine learning, and real-time data processing without the infrastructure limitations of Teradata.\n- Optimize cost and scalability\n - Teradata often involves complex and costly scaling processes. BigQuery offers transparent and automatic scaling of both storage and compute independently, eliminating the need for manual reconfiguration and providing a more predictable and often lower total cost of ownership.\n\nFeature comparison\n------------------\n\nThe following table compares the features and concepts in Teradata\nto equivalent features in BigQuery:\n\nGet started\n-----------\n\nThe following sections summarize the Teradata to BigQuery\nmigration process:\n\n### Run a migration assessment\n\nIn your Teradata to BigQuery migration, we\nrecommend that you start by running the [BigQuery migration\nassessment tool](/bigquery/docs/migration-assessment) to assess the feasibility\nand potential benefits of moving your\ndata warehouse from Teradata to BigQuery. This tool\nprovides a structured approach to understanding your current Teradata\nenvironment and estimating the effort involved in a successful migration.\n\nRunning the BigQuery migration assessment tool produces an\nassessment report that contains the following sections:\n\n- Existing system report: a snapshot of the existing Teradata system and usage, including the number of databases, schemas, tables, and total size in TB. It also lists the schemas by size and points to potential sub-optimal resource utilization, like tables with no writes or few reads.\n- BigQuery steady state transformation suggestions: shows what the system will look like on BigQuery after migration. It includes suggestions for optimizing workloads on BigQuery and avoiding wastage.\n- Migration plan: provides information about the migration effort itself. For example, getting from the existing system to the BigQuery steady state. This section includes the count of queries that were automatically translated and the expected time to move each table into BigQuery.\n\nFor more information about the results of a migration assessment, see [Review the Looker Studio report](/bigquery/docs/migration-assessment#review_the_data_studio_report).\n\n### Migrate schema and data from Teradata\n\nOnce you've reviewed the results of your migration assessment, you can start your Teradata migration by [preparing BigQuery for the migration](/bigquery/docs/migration/teradata#before_you_begin), then [setting up a data transfer job](/bigquery/docs/migration/teradata#set_up_a_transfer).\n\nFor more information about the Teradata migration process,\nsee [Migrate schema and data from Teradata](/bigquery/docs/migration/teradata).\n\n### Validate your migration\n\nOnce you've migrated your Teradata data to BigQuery,\nrun the Data Validation Tool (DVT) to perform a data\nvalidation on your newly migrated BigQuery data\nThe DVT validates various functions, from the table level to the row level, to\nverify that your migrated data works as intended. For more information about\nthe DVT, see [Introducing the Data Validation Tool for EDW migrations](https://cloud.google.com/blog/products/databases/automate-data-validation-with-dvt).\n\nYou can access the DVT in the [DVT public GitHub repository](https://github.com/GoogleCloudPlatform/professional-services-data-validator).\n\nWhat's next\n-----------\n\n- Try a [test migration](/bigquery/docs/migration/teradata-tutorial) of Teradata to BigQuery."]]
