To enable usage of Solvimon’s data seamlessly in your BigQuery instance. This page describes the steps necessary to connect your BigQuery instance to Solvimon for data exporting.
The following access is required for us to set-up a connection from your BigQuery instance to Solvimon.
BigQuery User and BigQuery Data Editor rights.Storage Admin for the service account you created.This step is optional if you already have a service account with the BigQuery User and BigQuery Data Editor roles, but highly recommended a separate service account for ease of permissioning and auditing. A service account with these roles can run BigQuery jobs, write to BigQuery datasets and read table metadata.
We recommend to create a Service Account by following GCP’s guide for Creating a Service Account. Once you’ve created the Service Account, make sure save its ID as you will need to reference it when granting roles. Service Account IDs typically take the form {ACCOUNT_NAME}@{PROJECT_NAME}.iam.gserviceaccount.com. Subsequently you will need to assign the BigQuery User and BigQuery Data Editor roles to the service account. This guide describes how to assign a role to the service account.
To use the created service account, we will need to generate a Service Account Key. You can follow this guide to generate one, ensure you select JSON as the Key type and save the contents for the next step.
To insert Solvimon’s data into your BigQuery instance we require a staging bucket in your Google Cloud environment. This bucket will be used to stage data to which can then be written to your BigQuery.
The following steps are necessary to create the storage bucket:
Your bucket must be encrypted using a Google-managed encryption key (this is the default setting when creating a new bucket). We currently do not support buckets using customer-managed encryption keys (CMEK). You can view this setting under the “Configuration” tab of your GCS bucket, in the Encryption type row.
This step is optional if you already have a BigQuery dataset to which we should export data to. However, we recommend creating a separate dataset to ensure data is saved in the right place.
To create a BigQuery dataset you can follow this guide. Make sure you save the dataset name.
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