# Load and query data
Get started with BigQuery by creating a dataset, loading data into a
table, and querying the table.
*** ** * ** ***
To follow step-by-step guidance for this task directly in the
Google Cloud console, click **Guide me**:
[Guide me](https://console.cloud.google.com/freetrial?redirectPath=/?walkthrough_id%3Dbigquery--bigquery-quickstart-load-data-console)
*** ** * ** ***
## Before you begin
1.
Enable the BigQuery API, if it is not already enabled.
**Roles required to enable APIs**
To enable APIs, you need the `serviceusage.services.enable` permission. If you
created the project, then you likely already have this permission through the
Owner role (`roles/owner`). Otherwise, you can get this permission through the
Service Usage Admin role (`roles/serviceusage.serviceUsageAdmin`).
[Learn how to grant roles](https://docs.cloud.google.com/iam/docs/granting-changing-revoking-access).
[Enable the API](https://console.cloud.google.com/apis/enableflow?apiid=bigquery)
For new projects, the BigQuery API is
automatically enabled.
2. Optional: [Enable
billing](https://docs.cloud.google.com/billing/docs/how-to/modify-project) for the project. If you don't want to enable billing or provide a credit card, the steps in this document still work. BigQuery provides you a sandbox to perform the steps. For more information, see [Enable the BigQuery sandbox](https://docs.cloud.google.com/bigquery/docs/sandbox#setup).
> [!NOTE]
> **Note:** If your project has a billing account and you want to use the BigQuery sandbox, then [disable billing for your project](https://docs.cloud.google.com/billing/docs/how-to/modify-project#disable_billing_for_a_project).
### Required roles
To get the permissions that
you need to create a dataset, create a table, load data, and query data,
ask your administrator to grant you the
following IAM roles on the project:
- Run load jobs and query jobs: [BigQuery Job User](https://docs.cloud.google.com/iam/docs/roles-permissions/bigquery#bigquery.jobUser) (`roles/bigquery.jobUser`)
- Create a dataset, create a table, load data into a table, and query a table: [BigQuery Data Editor](https://docs.cloud.google.com/iam/docs/roles-permissions/bigquery#bigquery.dataEditor) (`roles/bigquery.dataEditor`)
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).
You might also be able to get
the required permissions through [custom
roles](https://docs.cloud.google.com/iam/docs/creating-custom-roles) or other [predefined
roles](https://docs.cloud.google.com/iam/docs/roles-overview#predefined).
## 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](https://docs.cloud.google.com/bigquery/docs/dataset-locations).
1. In the Google Cloud console, open the BigQuery page.
[Go to BigQuery](https://console.cloud.google.com/bigquery)
2. In the left pane, click **Explorer**.
3. In the **Explorer** pane, click your project name.
4. Click **View actions**.
5. Select **Create dataset**.
6. 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](http://www.ssa.gov/OACT/babynames/background.html).
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 left pane, click **Explorer**.
2. In the **Explorer** pane, expand your project name.
3. Click **Datasets** and then next to the **babynames** dataset, click **View
actions** and select **Open**.
4. Click **Create
table** .
Unless otherwise indicated, use the default values for all settings.
5. 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:
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 left pane, click **Explorer**.
2. In the **Explorer** pane, expand your project and click **Datasets**.
3. Click the `babynames` dataset, and then select the `names_2024` table.
4. Click the **Preview** tab. BigQuery displays the first few rows of the table.
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.
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.
[Go to BigQuery](https://console.cloud.google.com/bigquery)
2. In the left pane, click **Explorer**.
3. In the **Explorer** pane, click **Datasets** and then click the `babynames` dataset that you created.
4. Expand the **View actions** option and click **Delete**.
5. In the **Delete dataset** dialog, confirm the delete command: type the word `delete` and then click **Delete**.
## What's next
- To learn more about loading data into BigQuery, see [Introduction to loading data](https://docs.cloud.google.com/bigquery/docs/loading-data).
- To learn more about querying data, see [Overview of BigQuery analytics](https://docs.cloud.google.com/bigquery/docs/query-overview).
- To learn how to load a JSON file with nested and repeated data, see [Loading nested and repeated JSON data](https://docs.cloud.google.com/bigquery/docs/loading-data-cloud-storage-json#loading_nested_and_repeated_json_data).
- To learn more about accessing BigQuery programmatically, see the [REST API](https://docs.cloud.google.com/bigquery/docs/reference/rest/v2) reference or the [BigQuery client libraries](https://docs.cloud.google.com/bigquery/docs/reference/libraries) page.