BigQuery

with the bigquery app in {{product name}} , you can monitor tables and completed query jobs, and manage the datasets and tables in your bigquery account requirements to use the bigquery app in {{product name}} , you must have a google account and a project created you can create an account at google cloud platform https //console cloud google com/ {{product name}} 's use and transfer of information received from google apis to any other app will adhere to google api services user data policy https //developers google com/terms/api services user data policy connect bigquery to {{product name}} to get started, you must first create a connection between bigquery and {{product name}} , allowing the two services to communicate to create the connection, you need to log in to your {{product name}} account, add a bigquery module to your {{scenario singular lowercase}} and click create a connection note if you add a module with an instant tag, click create a webhook , then create a connection optional in the connection name field, enter a name for the connection optional switch on the show advanced settings toggle and enter your google cloud platform project client credentials for more information, see the create and configure a google cloud platform project for bigquery section below click sign in with google if prompted, authenticate your account and confirm access you've successfully created the connection and can now use the bigquery app in your {{scenario plural lowercase}} if you want to make changes to your connection in the future, follow the steps connect an application docid\ so88fm6pkt0g adkddfzz create and configure a google cloud platform project for bigquery to connect to {{product name}} using your own client credentials, you can create and configure a project in the google cloud platform create a google cloud platform project for bigquery to create a google cloud platform project log in to the google cloud platform https //console cloud google com/ using your google credentials on the welcome page, click create or select a project > new project enter a project name and select the location for your project click create in the top menu, check if your new project is selected in the select a project dropdown if not, select the project you just created to create a new project or work in the existing one, you need to have the serviceusage services enable permission if you don’t have this permission, ask the google cloud platform project owner or project iam admin to grant it to you enable apis for bigquery to enable the required apis open the left navigation menu and go to apis & services > library search for the following api bigquery api click bigquery api , then click enable configure your oauth consent screen for bigquery to configure your oauth consent screen in the left sidebar, click google auth platform click get started in the overview section, under app information , enter make as the app name and provide your gmail address click next under audience , select external for more information regarding user types, refer to google's exceptions to verification requirements documentation https //support google com/cloud/answer/9110914#exceptions ver reqts under contact information , enter your gmail address under finish , agree to the google user data policy click continue > create in the branding section, under authorized domains , add make com and integromat com click save optional in the audience section, add your gmail address on the test users page, then click save and continue if you want the project to remain in the testing publishing status in the data access section, click add or remove scopes , add the following scopes, and click update click save publishing status testing if you keep your project in the testing status, you will be required to reauthorize your connection {{product name}} every week to avoid weekly reauthorization, update the project status to in production in production if you update your project to the in production status, you will not be required to reauthorize the connection weekly to update your project's status, go to the google auth platform , the audience section, and click publish app if you see the notice needs verification , you can choose whether to go through the google verification process https //support google com/cloud/answer/13463073?authuser=1\&visit id=638718595933013017 1855034908\&rd=1 for the app or to connect to your unverified app currently connecting to unverified apps works in {{product name}} , but we cannot guarantee the google will allow connections to unverified apps for an indefinite period for more information regarding the publishing status, refer to the publishing status section of google's setting up your oauth consent screen help https //support google com/cloud/answer/10311615#zippy= create your bigquery client credentials to create your client credentials in google auth platform, click clients click + create client in the application type dropdown, select web application update the name of your oauth client this will help you identify it in the platform in the authorized redirect uris section, click + add uri and enter the following redirect uri https //www integromat com/oauth/cb/google/ click create click the oauth 2 0 client you created, copy your client id and client secret values, and store them in a safe place you'll use these values in the client id and client secret connection fields in {{product name}} bigquery modules after connecting to the app, you can use the following types of modules to build your {{scenario plural lowercase}} dataset list datasets get a dataset create a dataset update a dataset delete a dataset table watch tables list tables get a table create a table update a table delete a table table data watch rows list table data upload data (streaming) update a file query job watch query jobs completed list jobs get query results by job id run a query other make an api call templates you can look for bigquery templates in make's template gallery , where you'll find thousands of pre created {{scenario plural lowercase}} bigquery resources bigquery api documentation https //cloud google com/bigquery/docs/reference/rest bigquery product documentation