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Showing content from https://developers.google.com/bigquery/docs/quickstarts/load-data-console below:

Load and query data with the Google Cloud console

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Learn how to use the Google Cloud console to create a dataset, load sample data into a BigQuery table, and query tables.

To follow step-by-step guidance for this task directly in the Google Cloud console, click Guide me:

Guide me

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

4. Optional: If you select an existing project, make sure that you enable the BigQuery API. The BigQuery API is automatically enabled in new projects.

Use the Google Cloud console to create a dataset that stores the data.

1. In the Google Cloud console, open the BigQuery page.
Go to BigQuery
2. In the Explorer pane, click your project name.
3. Click more_vert View actions.
4. Select Create dataset.
5. On the Create dataset page, do the following:
1. For Dataset ID, enter babynames.
2. For Location type, select Multi-region, and then choose US (multiple regions in United States). The public datasets are stored in the us multi-region location. For simplicity, store your dataset in the same location.
3. Leave the remaining default settings as they are, and click Create dataset .

For more information about the dataset, see the Social Security Administration's dataset information page.

1. Download the US Social Security Administration's dataset by opening the following URL in a new browser tab:

   https://www.ssa.gov/OACT/babynames/names.zip
   

2. Extract the file.

   For more information about the dataset schema, see the zip file's NationalReadMe.pdf file.

3. To see what the data looks like, open the yob2014.txt file. This file contains comma-separated values for name, assigned sex at birth, and number of children with that name. The file has no header row.

4. Note the location of the yob2014.txt file so that you can find it later.

Next, load the data into a new table.

1. In the Explorer pane, click your project name.
2. Next to the babynames dataset, click more_vert View actions and select Open.
3. Click add_box Create table.

   Unless otherwise indicated, use the default values for all settings.

4. On the Create table page, do the following:
1. In the Source section, choose Upload from the Create table from list.
2. In the Select file field, click Browse.
3. Navigate to and open your local yob2014.txt file, and click Open.
4. From the File format list, choose CSV.
5. In the Destination section, in the Table field, enter names_2014.
6. In the Schema section, click the Edit as text toggle, and paste the following schema definition into the text field:

name:string,assigned_sex_at_birth:string,count:integer

7. Click Create table .

   Wait for BigQuery to create the table and load the data. When BigQuery finishes loading the data, expand the Personal history and Project history pane to review the job details.

To preview the table data, follow these steps:

1. In the Explorer pane, expand your project and babynames dataset, and then select the names_2014 table.
2. Click the Preview tab. BigQuery displays the first few rows of the table.

Next, query the table. The process is identical to the previous example, except that this time, you're querying your table instead of a public table.

1. In the details pane, click add_box SQL query. A new editor tab opens.
2. In the query editor, paste the following query. This query retrieves the top five names for US babies that were assigned male at birth in 2014.
   

   
       SELECT
         name,
         count
       FROM
         `babynames.names_2014`
       WHERE
         assigned_sex_at_birth = 'M'
       ORDER BY
         count DESC
       LIMIT
         5;
       

3. Click Run . The results are displayed in the Query results section.
   

You have successfully queried a table in a public dataset and then loaded your sample data into BigQuery using the Google Cloud console.

To avoid incurring charges to your Google Cloud account for the resources used on this page, follow these steps.

1. In the Google Cloud console, open the BigQuery page.
Go to BigQuery
2. In the Explorer pane, click the babynames dataset that you created.
3. Expand the more_vert View actions option and click Delete.
4. In the Delete dataset dialog, confirm the delete command: type the word delete and then click Delete.

• To learn more about using the Google Cloud console, see Using the Google Cloud console.
• To learn more about loading data into BigQuery, see Introduction to loading data.
• To learn more about querying data, see Overview of querying BigQuery data.
• To learn how to load a JSON file with nested and repeated data, see Loading nested and repeated JSON data.
• To learn more about accessing BigQuery programmatically, see the REST API reference or the BigQuery client libraries page.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License, and code samples are licensed under the Apache 2.0 License. For details, see the Google Developers Site Policies. Java is a registered trademark of Oracle and/or its affiliates.

Last updated 2025-08-07 UTC.

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