Creating a dataset using Google BigQuery
When Quick Sight uses and transfers information that is received from Google APIs, it adheres to theGoogle API Services User Data Policy.
Google BigQuery is a fully managed serverless data warehouse that customers use to manage and analyze their data. Google BigQuery customers use SQL to query their data without any infrastructure management.
Creating a data source connection with Google BigQuery
Prerequisites
Before you start, make sure that you have the following. These are all required to create a data source connection with Google BigQuery:
Project ID – The project ID that is associated with your Google account. To find this, navigate to the Google Cloud console and choose the name of the project that you want to connect to Quick Sight. Copy the project ID that appears in the new window and record it for later use.
Dataset Region – The Google region that the Google BigQuery project exists in. To find the dataset region, navigate to the Google BigQuery console and chooseExplorer. Locate and expand the project that you want to connect to, then choose the dataset that you want to use. The dataset region appears in the pop-up that opens.
Google account login credentials – The login credentials for your Google account. If you don't have this information, contact your Google account administrator.
Google BigQuery Permissions – To connect your Google account with Quick Sight, make sure that your Google account has the following permissions:
BigQuery Job Userat theProjectlevel.BigQuery Data Viewerat theDatasetorTablelevel.BigQuery Metadata Viewerat theProjectlevel.
For information about how to retrieve the previous prerequisite information, seeUnlock the power of unified business intelligence with Google Cloud BigQuery and Quick Sight.
Use the following procedure to connect your Quick Suite account with your Google BigQuery data source.
To create a new connection to a Google BigQuery data source from Quick Sight
Open theQuick Suite console.
From the left navigation pane, chooseData.
ChooseCreate then chooseNew Dataset
Choose theGoogle BigQuery tile.
Add the data source details that you recorded in the prerequisites section earlier:
Data source name – A name for the data source.
Project ID – A Google Platform project ID. This field is case sensitive.
Dataset Region – The Google cloud platform dataset region of the project that you want to connect to.
ChooseSign in.
In the new window that opens, enter the login credentials for the Google account that you want to connect to.
ChooseContinue to grant Quick Sight access to Google BigQuery.
After you create the new data source connection, continue toStep 4 in the following procedure.
Adding a new Quick Sight dataset for Google BigQuery
After you create a data source connection with Google BigQuery, you can create Google BigQuery datasets for analysis. Datasets that use Google BigQuery can only be stored in SPICE.
To create a dataset using Google BigQuery
Open theQuick Suite console.
From the start page, chooseData.
ChooseCreate, thenNew Dataset
Choose theGoogle BigQuery tile, and then chooseCreate dataset.
ForTables, do one of the following:
Choose the table that you want to use.
ChooseUse custom SQL to use your own personal SQL statement. For more information about using custom SQL in Quick Sight, seeUsing SQL to customize data.
ChooseEdit/Preview.
(Optional) In theData prep page that opens, you can add customizations to your data with calculated fields, filters, and joins.
When you are finished making changes, chooseSave to save and close the dataset.
