Load and query data in BigQuery Studio

Get started with BigQuery by using BigQuery Studio to create a dataset, load data into a table, and query the table.

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

Guide me

Before you begin

Before you can explore BigQuery, you must sign in to Google Cloud console and create a project. If you don't enable billing in your project, then all of the data you upload will be in the BigQuery sandbox. The sandbox makes it possible for you to learn BigQuery at no charge while working with a limited set of BigQuery features. For more information, see Enable the BigQuery sandbox.

  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.

    Go to project selector

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

    Go to project selector

    4.
  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.

Create a BigQuery dataset

Use the Google Cloud console to create a dataset to store the data. You create your dataset in the US multi-region location. For information on BigQuery regions and multi-regions, see Locations.

  1. In the Google Cloud console, open the BigQuery Studio page.
    2. Go to BigQuery Studio
  2. In the Explorer pane, click your project name.
  3. Click 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.

Download the file that contains the source data

The file that you're downloading contains approximately 7 MB of data about popular baby names. It's provided by the US Social Security Administration.

For more information about the data, see the Social Security Administration's Background information for popular names.

  1. Download the US Social Security Administration's data 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 yob2024.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 yob2024.txt file so that you can find it later.

Load data into a table

Next, load the data into a new table.

  1. In the Explorer pane, expand your project name.
  2. Next to the babynames dataset, click View actions and select Open.
  3. Click 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, for Create table from, choose Upload from the list.
    2. In the Select file field, click Browse.
    3. Navigate to and open your local yob2024.txt file, and click Open.
    4. From the File format list, choose CSV.
    5. In the Destination section, in the Table field, enter names_2024.
    6. In the Schema section, click the Edit as text toggle, and paste the following schema definition into the text field:
      7. name:string,assigned_sex_at_birth:string,count:integer
    7. Click Create table.

      Wait for BigQuery to create the table and load the data.

Preview table data

To preview the table data, follow these steps:

  1. In the Explorer pane, expand your project and babynames dataset, and then select the names_2024 table.
  2. Click the Preview tab. BigQuery displays the first few rows of the table.
    3. The table preview tab.
The Preview tab is not available for all table types. For example, the Preview tab is not displayed for external tables or views.

Query table data

Next, query the table.

  1. Next to the names_2024 tab, click the SQL query option. A new editor tab opens.
  2. In the query editor, paste the following query. This query retrieves the top five names for babies born in the US that were assigned male at birth in 2024.
    
  SELECT
    name,
    count
  FROM
    `babynames.names_2024`
  WHERE
    assigned_sex_at_birth = 'M'
  ORDER BY
    count DESC
  LIMIT
    5;
  3. Click Run. The results are displayed in the Query results section.
    The query results panel

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

Clean up

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

What's next