Configure an Amazon S3 integration

1. In your AWS management console, create a bucket and an IAM user using the steps described here. Be sure to make this bucket private and give the IAM user access to the bucket with list objects and read permissions. Refer to the IAM policy for proper access:
   

   {
    "Version": "2012-10-17",
    "Statement": [
         {
          "Effect": "Allow",
          "Action": ["s3:ListBucket"],
          "Resource": ["arn:aws:s3:::{{bucket_name}}"]
         },
         {
          "Effect": "Allow",
          "Action": ["s3:GetObject"],
          "Resource": [
           "arn:aws:s3:::{{bucket_name}}",
           "arn:aws:s3:::{{bucket_name}}/*"
          ]
         }
     ]
   }

2. After setting up an IAM user with access to the S3 bucket holding your data, locate your AWS access key ID and secret.
3. In Catalyst, navigate to Settings > Integrations.
4. Locate S3 from the list of inactive integrations, click + Add.
5. Enter the AWS access key ID, AWS secret access key, and region.
6. Click Connect.
   Once connected, add your data source (see below).

Although it is optional, we recommend adding Catalyst IP addresses to your allowlist: 3.95.50.240 | 34.206.178.38 | 34.192.22.163

1. From within the S3 integration in Catalyst (see above), click + Add Source.
2. Enter the details for the data source (see below).
3. Click Save.
   You can now add a new Catalyst data warehouse field that syncs to the field in your S3 data source.

Data Warehouse integrations update every 6 hours, 4 times a day. You can map Catalyst fields immediately after adding a data source, but fields will not populate with data until after the next sync.

Data source details

• Source nickname: Unique name to identify the source in Catalyst.
• Catalyst object: Choose the object you're mapping to in Catalyst.
• Data path: Map the data path you're connecting Catalyst to in your GCS warehouse: 
  • Enter the bucket name
  • Enter the CSV name. If the CSV is in a folder, enter [folder name]/[csv name]
• Matching strategy: Choose the identifier to use to match your data to your records:
  • Salesforce Field ID: Highly recommended. It's best to use an 18-digit SFDC ID when setting up your tables; however, both 15 and 18-digit IDs work.
  • Select a field: Choose any supported field that exists in Catalyst for the selected object (e.g., text, number, Boolean, ISO 8601 formatted dates)
• Matching column name: Choose the column in your table that is your identifier.
• Table structure: Specify how your table is structured (unique or multiple rows).
  • Current snapshot of Salesforce Object ID: Choose this option if the table you're using already has a unique row per Salesforce Object ID record.
    

  • Latest entry per Salesforce Object ID using timestamp: Choose this option if the table you're using contains multiple rows for a single unique Salesforce Object ID record. Select a timestamp field from the drop-down to indicate the most recently updated record for each Salesforce Object ID; allows Catalyst to reflect the most accurate value at the end of each day.
    

    Performing this operation in your data warehouse could have cost implications, depending on your pricing structure.