# Google BigQuery

Friends offers seamless integration with Google Cloud's [BigQuery](https://cloud.google.com/bigquery) service, enabling you to effortlessly connect data flows between your systems and BigQuery.

Frends has tasks for performing all core BigQuery operations.

## Use cases

Below you will find typical use cases for BigQuery integrations and how they are implemented in Frends.

## Insert data into BigQuery table

By using the file trigger and the [Insert](https://github.com/FrendsPlatform/FrendsDocs/blob/FrendsDocs/FrendsTasks/tasks/google-bigquery/insert/.md/README.md) task, we can create an integration that listens for incoming CSV files and inserts the data into the appropriate table.

<figure><img src="/files/LnyTEuHNNXAW29U2mO8U" alt=""><figcaption><p>Insert CSV data to BigQuery table</p></figcaption></figure>

## Get data from BigQuery and save as CSV

By using the [ExecuteQuery](https://github.com/FrendsPlatform/FrendsDocs/blob/FrendsDocs/FrendsTasks/tasks/google-bigquery/executequery/.md/README.md) task, we can create an integration that retrieves data from a BigQuery and generates CSV exports for further processing.

<figure><img src="/files/aGBFZwZlubEwqs92M0bN" alt=""><figcaption><p>Save BigQuery data as CSV</p></figcaption></figure>


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.frends.com/tasks/tasks/google-bigquery.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.