Load and query data with the Google Cloud console

Create a BigQuery dataset

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 panel, click your project name.
3. Expand the more_vert View actions > Create dataset.
4. On the Create dataset page, do the following:
1. For Dataset ID, enter babynames.
2. From the Data location list, 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 source data file

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.

Load data into a table

Next, load the data into a new table.

1. In the Explorer panel, click your project name.
2. Next to the babynames dataset, click More actions more_vert and select Open.
3. In the details panel, 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, enter names_2014 for Table name.
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 panel to review the job details.

Preview table data

To preview the table data, follow these steps:

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

Query table data

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. Click add_box Compose new query. A new Editor tab opens.
2. In the Editor tab, 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 Cloud console.