# Translate queries with the interactive SQL translator The BigQuery interactive SQL translator lets you translate queries from other SQL dialects into GoogleSQL queries by using the [Google Cloud console](https://docs.cloud.google.com/bigquery/docs/bigquery-web-ui.md.txt), the Google Cloud CLI, or the [BigQuery Migration Service MCP server](https://docs.cloud.google.com/bigquery/docs/use-bigquery-migration-mcp). Using the interactive SQL translator helps reduce the time and effort required to migrate workloads to BigQuery, and you can customize translations by using the [translation rule feature](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator.md.txt#customize). To build a custom software integration, an automated CI/CD pipeline, or another programmatic workflow, see the [BigQuery Migration API guide](https://docs.cloud.google.com/bigquery/docs/api-sql-translator). For information about supported dialects and processing locations, see [Supported SQL dialects](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations#supported_sql_dialects) and [Locations](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations.md.txt#locations). ## Before you begin Before you submit a translation job, do the following steps. ### Enable SQL translations Enable the required API, and get the permissions needed to use a BigQuery SQL translator. For more information, see [Enable SQL translations](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations#enable_sql_translations). ### Required permissions To get the permissions that you need to create translation jobs with the interactive translator, the translation API, or the batch SQL translator, ask your administrator to grant you the following IAM roles on the `parent` resource: - Viewing and monitoring migration jobs: [MigrationWorkflow Viewer](https://docs.cloud.google.com/iam/docs/roles-permissions/bigquerymigration.md.txt#bigquerymigration.viewer) (`roles/bigquerymigration.viewer`) - Submitting migration jobs: [MigrationWorkflow Editor](https://docs.cloud.google.com/iam/docs/roles-permissions/bigquerymigration.md.txt#bigquerymigration.editor) (`roles/bigquerymigration.editor`) - Access the Cloud Storage buckets for input and files: Storage Object Admin (`roles/storage.objectAdmin`) - on the source and destination Cloud Storage bucket. For more information about granting roles, see [Manage access to projects, folders, and organizations](https://docs.cloud.google.com/iam/docs/granting-changing-revoking-access.md.txt). These predefined roles contain the permissions required to create translation jobs with the interactive translator, the translation API, or the batch SQL translator. To see the exact permissions that are required, expand the **Required permissions** section: #### Required permissions The following permissions are required to create translation jobs with the interactive translator, the translation API, or the batch SQL translator: - `bigquerymigration.workflows.create` - `bigquerymigration.workflows.get` - `bigquerymigration.workflows.list` - `bigquerymigration.workflows.delete` - `bigquerymigration.subtasks.get` - `bigquerymigration.subtasks.list` - `storage.objects.get` - `storage.objects.list` - `storage.objects.create` You might also be able to get these permissions with [custom roles](https://docs.cloud.google.com/iam/docs/creating-custom-roles.md.txt) or other [predefined roles](https://docs.cloud.google.com/iam/docs/roles-overview.md.txt#predefined). To restrict specific translation workflow configurations in your organization, such as disallowing Gemini AI suggestions or restricting translation output types, configure [Custom Org Policies for BigQuery Migration Service](https://docs.cloud.google.com/bigquery/docs/migration-custom-org-policies.md.txt#example_constraints). ## Handling unsupported SQL functions with helper UDFs When translating SQL from a source dialect to BigQuery, some functions might not have a direct equivalent. To address this, the BigQuery Migration Service (and the broader BigQuery community) provide helper user-defined functions (UDFs) that replicate the behavior of these unsupported source dialect functions. These UDFs are often found in the `bqutil` public dataset, allowing translated queries to initially reference them using the format `bqutil..()`. For example, `bqutil.fn.cw_count()`. ### Important considerations for production environments: While `bqutil` offers convenient access to these helper UDFs for initial translation and testing, direct reliance on `bqutil` for production workloads is not recommended for several reasons: 1. Version control: The `bqutil` project hosts the latest version of these UDFs, which means their definitions can change over time. Relying directly on `bqutil` could lead to unexpected behavior or breaking changes in your production queries if a UDF's logic is updated. 2. Dependency isolation: Deploying UDFs to your own project isolates your production environment from external changes. 3. Customization: You might need to modify or optimize these UDFs to better suit your specific business logic or performance requirements. This is only possible if they are within your own project. 4. Security and governance: Your organization's security policies might restrict direct access to public datasets like `bqutil` for production data processing. Copying UDFs to your controlled environment aligns with such policies. ### Deploying helper UDFs to your project: For reliable and stable production use, you should deploy these helper UDFs into your own project and dataset. This gives you full control over their version, customization, and access. For detailed instructions on how to deploy these UDFs, refer to the [UDFs deployment guide on GitHub](https://github.com/GoogleCloudPlatform/bigquery-utils/tree/master/udfs#deploying-the-udfs). This guide provides the necessary scripts and steps to copy the UDFs into your environment. ## Locations The interactive SQL translator is only available in select processing locations. For more information, see [Locations](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations.md.txt#locations). [Gemini-based translation configurations](https://docs.cloud.google.com/bigquery/docs/config-yaml-translation.md.txt#ai_yaml_guidelines) are only available in specific processing locations. For more information, see [Google model endpoint locations](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/learn/locations#google_model_endpoint_locations) ## Translate a query into GoogleSQL You can translate a query using the Google Cloud console, the gcloud CLI, or the BigQuery Migration Service MCP server. Select one of the following options: ### Console Follow these steps to translate a query into GoogleSQL: 1. In the Google Cloud console, go to the **BigQuery** page. [Go to BigQuery](https://console.cloud.google.com/bigquery) 2. In the **Editor** pane, click **Tools** \> **Translation settings**. 3. For **Source dialect**, select the SQL dialect that you want to translate. 4. Optional. For **Processing location** , select the location where you want the translation job to run. For example, if you are in Europe and you don't want your data to cross any location boundaries, select the `eu` region. 5. Click **Save**. 6. In the **Editor** pane, click **Tools** \> **Enable SQL translation**. The **Editor** pane splits into two panes. 7. In the left pane, enter the query you want to translate. 8. Click **Translate**. BigQuery translates your query into GoogleSQL and displays it in the right pane. For example, the following screenshot shows translated Teradata SQL: ![Displays a Teradata SQL query translated into GoogleSQL](https://docs.cloud.google.com/static/bigquery/images/translated-teradata-query.png) 9. Optional: To run the translated GoogleSQL query, click **Run**. 10. Optional: To return to the SQL editor, click **More** \> **Disable SQL translation**. The **Editor** pane returns to a single pane. ### gcloud > [!WARNING] > > **Preview** > > > This product or feature is > > subject to the "Pre-GA Offerings Terms" in the General Service Terms section > of the [Service Specific > Terms](https://docs.cloud.google.com/terms/service-terms#1). > > Pre-GA products and features are available "as is" and might have limited support. > > For more information, see the > [launch stage descriptions](https://cloud.google.com/products/#product-launch-stages).
To translate a query from the Google Cloud CLI, use the [`gcloud alpha bq migration translate` command](https://docs.cloud.google.com/sdk/gcloud/reference/alpha/bq/migration/translate.md.txt): ``` gcloud alpha bq migration translate \ --source-dialect=SOURCE_DIALECT \ --target-dialect=TARGET_DIALECT \ --location=LOCATION \ --input-file=INPUT_FILE ``` Replace the following: - `SOURCE_DIALECT`: the SQL dialect that you want to translate, such as `teradata`. For the supported values, see [Supported SQL dialects](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations.md.txt#supported_sql_dialects). - `TARGET_DIALECT`: the dialect to translate the query into. For example, `bigquery`. - `LOCATION`: the [location](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations.md.txt#locations) where you want the translation job to run. For example, if you are in Europe and you don't want your data to cross any location boundaries, specify the `eu` region. - `INPUT_FILE`: the local file that contains the query that you want to translate. The command prints the translated query to the gcloud CLI. To write the translated query to a file instead, add the `--output-file` flag. To translate a query without creating a file, pipe it through standard input and omit the `--input-file` flag: ``` echo 'SELECT 1;' | gcloud alpha bq migration translate \ --source-dialect=teradata \ --target-dialect=bigquery \ --location=us ``` To apply the customizations that you would otherwise set in **Translation settings**, use the following flags: - `--translation-config-files`: a comma-separated list of [configuration YAML files](https://docs.cloud.google.com/bigquery/docs/config-yaml-translation.md.txt). File names must end with `.config.yaml` or `.ai_config.yaml`. - `--metadata-gcs-uri`: the Cloud Storage URI of a metadata ZIP file. ### MCP To translate a query from an AI application or agent, connect your MCP client to the BigQuery Migration Service MCP server. For setup instructions and required roles, see [Configure an MCP client to use the BigQuery Migration Service MCP server](https://docs.cloud.google.com/bigquery/docs/use-bigquery-migration-mcp.md.txt#configure-client). Prompt your MCP client to translate a query: ``` Translate this query from DIALECT: QUERY. Use PROJECT_NUMBER and LOCATION. ``` Replace the following: - `DIALECT`: the dialect of the SQL query that you're translating, such as `Teradata`. For the supported values, see [Supported SQL dialects](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations.md.txt#supported_sql_dialects). - `QUERY`: the SQL query that you're translating. - `PROJECT_NUMBER`: your Google Cloud [project number](https://docs.cloud.google.com/resource-manager/docs/creating-managing-projects.md.txt#before_you_begin). - `LOCATION`: the [location](https://docs.cloud.google.com/bigquery/docs/enable-sql-translations.md.txt#locations) where you want the translation job to run, such as `us` or `eu`. When you use this prompt, the MCP client calls the [`translate_query` tool](https://docs.cloud.google.com/bigquery/docs/reference/migration/mcp/tools_list/translate_query.md.txt), and then periodically calls the [`get_translation` tool](https://docs.cloud.google.com/bigquery/docs/reference/migration/mcp/tools_list/get_translation.md.txt) until the translation state is `SUCCEEDED` or `FAILED` and displays the translated query and any translation logs. You can also ask your MCP client to include a [metadata ZIP file](https://docs.cloud.google.com/bigquery/docs/generate-metadata.md.txt) or [configuration YAML files](https://docs.cloud.google.com/bigquery/docs/config-yaml-translation.md.txt) in the translation, explain the translation with the [`explain_translation` tool](https://docs.cloud.google.com/bigquery/docs/reference/migration/mcp/tools_list/explain_translation.md.txt), or infer source DDL statements with the [`generate_ddl_suggestion`](https://docs.cloud.google.com/bigquery/docs/reference/migration/mcp/tools_list/generate_ddl_suggestion.md.txt) and [`fetch_ddl_suggestion`](https://docs.cloud.google.com/bigquery/docs/reference/migration/mcp/tools_list/fetch_ddl_suggestion.md.txt) tools. For more sample prompts, see [Use the BigQuery Migration Service MCP server](https://docs.cloud.google.com/bigquery/docs/use-bigquery-migration-mcp.md.txt#sample-prompts). ## Explore the translation output Depending on the configuration files that you provide, translating a query can produce the translated SQL, rewritten source SQL from `SOURCE_SQL` rules, rewritten target SQL from `TARGET_SQL` rules, and a translation explanation. For more information, see [Transform SQL translations with YAML](https://docs.cloud.google.com/bigquery/docs/config-yaml-translation.md.txt). To find each translation output, select one of the following options: ### Console In the Google Cloud console, find each output in the following locations of the SQL editor: - Translated SQL: the right pane of the SQL editor after you click **Translate**. - Rewritten source SQL: the **Preview suggested changes** dialog that appears after you run the translation, or click **Assist** \> **View suggestions** in the left pane. For more information, see [Create and apply Gemini-enhanced translation rules](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator#create-apply-rules). - Rewritten target SQL: click **Assist** \> **View suggestions** in the right pane. For more information, see [Create and apply Gemini-enhanced translation rules](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator#create-apply-rules). - Translation explanation: click **Assist** \> **Explain this translation** . For more information, see [Explain a translation](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator.md.txt#explain_a_translation). ### gcloud > [!WARNING] > > **Preview** > > > This product or feature is > > subject to the "Pre-GA Offerings Terms" in the General Service Terms section > of the [Service Specific > Terms](https://docs.cloud.google.com/terms/service-terms#1). > > Pre-GA products and features are available "as is" and might have limited support. > > For more information, see the > [launch stage descriptions](https://cloud.google.com/products/#product-launch-stages).
By default, the `gcloud alpha bq migration translate` command prints the translated SQL, any rewritten source SQL, and any rewritten target SQL to standard output. To write each output to a local file instead, use the following flags: - `--output-file`: a local file that receives the translated SQL that the translation engine produces after applying any rules in `*.config.yaml` files. - `--source-sql-suggestion-output-file`: a local file that receives the rewritten source SQL that Gemini produces before translation by applying `SOURCE_SQL` rules in `*.ai_config.yaml` files to the input SQL. - `--target-sql-suggestion-output-file`: a local file that receives the rewritten target SQL that Gemini produces by applying `TARGET_SQL` rules in `*.ai_config.yaml` files to the translated SQL. - `--explanation-output-file`: a local file that receives a Gemini-generated explanation of the translation. The command generates an explanation only when you specify this flag, and it doesn't print the explanation to standard output. ## Use Gemini with the interactive SQL translator You can configure the interactive SQL translator to adjust how the interactive SQL translator translates your source SQL. You can do so by providing your own rules for use with Gemini in a YAML configuration file, or by providing a configuration YAML file containing SQL object metadata or object mapping information. ### Create and apply Gemini-enhanced translation rules > [!NOTE] > **Note:** To get support and provide feedback for preview features, contact [ai-sql-translation-help@google.com](mailto:ai-sql-translation-help@google.com). You can customize the way the interactive SQL translator translates SQL by creating translation rules. The interactive SQL translator adjusts its translations based on any Gemini-enhanced SQL translation rules that you assign to it, letting you customize the translation results based on your migration needs. To create a Gemini-enhanced SQL translation rule, you can either create it in the console, or create a configuration YAML file and upload it to Cloud Storage. ### Console To create a Gemini-enhanced SQL translation rule for the input SQL, write an input SQL query in the query editor, then click **ASSIST** \> **Customize** . ([Preview](https://cloud.google.com/products#product-launch-stages)) ![Customize translation input](https://docs.cloud.google.com/static/bigquery/images/customize-translation-input.png) Similarly, to create a Gemini-enhanced SQL translation rule for the output SQL, run an interactive translation, then click **ASSIST** \> **Customize this translation**. ![Customize translation output](https://docs.cloud.google.com/static/bigquery/images/customize-translation-output.png) When the **Customize** menu appears, continue with the following steps. 1. Use one or both of the following prompts to create a translation rule: - In the **Find and replace a pattern** prompt, specify a SQL pattern that you want to replace in the **Replace** field, and a SQL pattern to replace it in the **With** field. A SQL pattern can contain any number of statements, clauses, or functions in a SQL script. When you create a rule using this prompt, the Gemini enhanced SQL translation identifies any instances of that SQL pattern in the SQL query and dynamically replaces it with another SQL pattern. For example, you can use this prompt to create a rule that replaces all occurrences of `months_between (X,Y)` with `date_diff(X,Y,MONTH)`. - In the **Describe a change to the output** field, type a change to the SQL translation output in natural language. When you create a rule using this prompt, the Gemini-enhanced SQL translation identifies the request and makes the specified change to the SQL query. 2. Click **Preview**. 3. In the **Suggestions generated by Gemini** dialog, review the changes made by the Gemini-enhanced SQL translation to the SQL query based on your rule. ![Apply changes from Gemini-based configuration YAML file](https://docs.cloud.google.com/static/bigquery/images/gemini-suggested-changes-1.png) 4. Optional: To add this rule for use with future translations, select the **Save this prompt...** checkbox. Rules are saved in the default configuration YAML file, or `__default.ai_config.yaml`. This configuration YAML file is saved to the Cloud Storage folder as specified in the **Translation Configuration Source Location** field in the [translation settings](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator.md.txt#translate-with-additional-configs). If the **Translation Configuration Source Location** isn't already set, a folder browser appears and lets you select one. A configuration YAML file is subject to [configuration file size limitations](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator.md.txt#config-limitations). 5. To apply the suggested changes to the SQL query, click **Apply**. ### YAML To create a Gemini-enhanced SQL translation rule, you can create a Gemini-based configuration YAML file and upload it to Cloud Storage. For more information, see [Create a Gemini-based configuration YAML file](https://docs.cloud.google.com/bigquery/docs/config-yaml-translation.md.txt#ai_yaml_guidelines). Once you have uploaded a Gemini-enhanced SQL translation rule and uploaded it to Cloud Storage, you can apply the rule by doing the following: 1. In the Google Cloud console, go to the **BigQuery** page. [Go to BigQuery](https://console.cloud.google.com/bigquery) 2. In the query editor, click **Tools** \> **Translation settings**. 3. In the **Translation Configuration Source Location** field, specify the path to the Gemini-based YAML file stored in a Cloud Storage folder. 4. Click **Save**. Once saved, run an interactive translation. The interactive translator suggests changes to your translations based on the rules in your configuration YAML file if one is available. If a Gemini suggestion is available for the input based on your rule, then the **Preview suggested changes** dialog appears and shows possible changes to the translation input. ([Preview](https://cloud.google.com/products#product-launch-stages)) If a Gemini suggestion is available for the output based on your rule, a notification banner appears in the code editor. To review and apply these suggestions, do the following: 1. Click **Assist** \> **View suggestions** on either side of the code editor to revisit the suggested changes to the corresponding query. ![Apply changes from Gemini-based configuration YAML file](https://docs.cloud.google.com/static/bigquery/images/gemini-suggested-changes-2.png) 2. In the **Suggestions generated by Gemini** dialog, review the changes made by Gemini to the SQL query based on your translation rule. 3. To apply the suggested changes to the translation output, click **Apply**. #### Update Gemini-based configuration YAML file To update an existing configuration YAML file, do the following: 1. On the **Suggestions generated in Gemini** dialog, click **View Gemini rule config file**. 2. When the configuration editor appears, select the configuration YAML file that you want to edit. 3. Make the change and click **Save**. 4. Close the YAML editor by clicking **Done**. 5. Run an interactive translation to apply the updated rule. ### Explain a translation > [!WARNING] > > **Preview** > > > This product or feature is > > subject to the "Pre-GA Offerings Terms" in the General Service Terms section > of the [Service Specific > Terms](https://docs.cloud.google.com/terms/service-terms#1). > > Pre-GA products and features are available "as is" and might have limited support. > > For more information, see the > [launch stage descriptions](https://cloud.google.com/products/#product-launch-stages). > [!NOTE] > **Note:** With Gemini-enhanced SQL translations, you can generate text explanation for your scripts by the Gemini model. Gemini-enhanced SQL translations are allowed a limited amount of Gemini usage at no charge. This usage is sufficient for most migration projects. To request an increase to this limit, or to get support and provide feedback for this Preview feature, contact [ai-sql-translation-help@google.com](mailto:ai-sql-translation-help@google.com). After running an interactive translation, you can request a Gemini-generated text explanation. The generated text includes a summary of the translated SQL query. Gemini also identifies translation differences and inconsistencies between the source SQL query and the translated GoogleSQL query. To get Gemini-generate SQL translation explanation, do the following: 1. To create a Gemini-generated SQL translation explanation, click **Assist** , and then click **Explain this translation**. ![Explain translation button.](https://docs.cloud.google.com/static/bigquery/images/int-translate-explain.png) ### Translate with a batch translation configuration ID You can run an interactive query with the same translation configurations as a batch translation job by providing a batch translation configuration ID. 1. In the query editor, click **Tools** \> **Translation settings**. 2. In the **Translation Configuration ID** field, provide a batch translation configuration ID to apply the same translation configuration from a completed BigQuery batch migration job. To find a job's batch translation configuration ID, select a batch translation job from the **SQL translation** page, and then click the **Translation Configuration** tab. The batch translation configuration ID is listed as **Resource name**. 3. Click **Save**. ### Translate with additional configurations You can run an interactive query with additional translation configurations by specifying configuration YAML files stored on a Cloud Storage folder. Translation configurations might include SQL object metadata or object mapping information from the source database that can improve translation quality. For example, include DDL information or schemas from the source database to improve interactive SQL translation quality. To specify translation configurations by providing a location to the translation configuration source files, do the following: 1. In the query editor, click **Tools** \> **Translation settings**. 2. In the **Translation Configuration Source Location** field, specify the path to the translation configuration files stored in a Cloud Storage folder. The BigQuery interactive SQL translator supports metadata ZIP files containing [translation metadata](https://docs.cloud.google.com/bigquery/docs/generate-metadata.md.txt) and [object name mapping](https://docs.cloud.google.com/bigquery/docs/output-name-mapping.md.txt). For information on how to upload files to Cloud Storage, see [Upload objects from a filesystem](https://docs.cloud.google.com/storage/docs/uploading-objects.md.txt). 3. Click **Save**. ### Configuration file size limitations When you use a translation configuration file with the BigQuery interactive SQL translator, the compressed metadata file or YAML config file must be smaller than 50 MB. If the file size exceeds 50 MB, the interactive translator skips that configuration file during translation and produces an error message similar to the following: `CONFIG ERROR: Skip reading file "gs://metadata-file.zip". File size (150,000,000 bytes) exceeds limit (50 MB).` One method to reduce metadata file size is to use the `--database` or `--schema` flags to only extract metadata for databases or schemas that are relevant for the translation input queries. For more information about using these flags when you [generate metadata files](https://docs.cloud.google.com/bigquery/docs/generate-metadata.md.txt), see [Global flags](https://docs.cloud.google.com/bigquery/docs/generate-metadata.md.txt#global_flags). ## Troubleshoot translation errors The following sections describe commonly encountered errors when using the interactive SQL translator. ### `RelationNotFound` or `AttributeNotFound` translation issues After translating a query using the [interactive SQL translator](https://docs.cloud.google.com/bigquery/docs/interactive-sql-translator.md.txt#translate_a_query_into_standard_sql), you might encounter a failed translation with the `RelationNotFound` or `AttributeNotFound` error. You can find failed translations by going to the **Translation details** page in BigQuery in the Google Cloud console and opening the **Log Messages** tab. To ensure the most accurate translation, you can enter the data definition language (DDL) statements for any tables used in a query prior to the query itself. For example, if you want to translate the Amazon Redshift query `select table1.field1, table2.field1 from table1, table2 where table1.id = table2.id;`, enter the following SQL statements into the interactive SQL translator: ```sql create table schema1.table1 (id int, field1 int, field2 varchar(16)); create table schema1.table2 (id int, field1 varchar(30), field2 date); select table1.field1, table2.field1 from table1, table2 where table1.id = table2.id; ``` #### Fix translation issues with Gemini > [!WARNING] > > **Preview** > > > This product or feature is > > subject to the "Pre-GA Offerings Terms" in the General Service Terms section > of the [Service Specific > Terms](https://docs.cloud.google.com/terms/service-terms#1). > > Pre-GA products and features are available "as is" and might have limited support. > > For more information, see the > [launch stage descriptions](https://cloud.google.com/products/#product-launch-stages). > [!NOTE] > **Note:** To request feedback or support for this feature, contact [bq-edw-migration-support@google.com](mailto:bq-edw-migration-support@google.com). To fix failed translation jobs with the `RelationNotFound` or `AttributeNotFound` errors, you can also use Gemini to resolve these issues: 1. In BigQuery in the Google Cloud console, go to the **Translation details** page and open the **Log Messages** tab. 2. Click the query that has the message `RelationNotFound` or `AttributeNotFound` in the **Category** column. 3. Click **Suggested fix**. 4. Click **Apply**. 5. To retranslate the query, click **Translate**. ## Pricing There is no charge to use the interactive SQL translator. However, storage used to store input and output files incurs the normal fees. For more information, see [Storage pricing](https://cloud.google.com/bigquery/pricing#storage). ## What's next Learn more about the following steps in data warehouse migration: - [Migration overview](https://docs.cloud.google.com/bigquery/docs/migration/migration-overview) - [Migration assessment](https://docs.cloud.google.com/bigquery/docs/migration-assessment.md.txt) - [Schema and data transfer overview](https://docs.cloud.google.com/bigquery/docs/migration/schema-data-overview.md.txt) - [Batch SQL translation](https://docs.cloud.google.com/bigquery/docs/batch-sql-translator.md.txt) - [Use the BigQuery Migration Service MCP server](https://docs.cloud.google.com/bigquery/docs/use-bigquery-migration-mcp) - [Data pipelines](https://docs.cloud.google.com/bigquery/docs/migration/pipelines.md.txt) - [Data security and governance](https://docs.cloud.google.com/bigquery/docs/data-governance.md.txt) - [Data validation tool](https://github.com/GoogleCloudPlatform/professional-services-data-validator#data-validation-tool)