Your enterprise analytics team runs Tableau Server in an on-premises data center protected by a strict outbound firewall that only allows HTTPS (TCP 443). To avoid the daily export of Google BigQuery tables to CSV and keep dashboards closer to real time, you need to let Tableau query BigQuery directly with minimal re-engineering of existing workbooks. Which approach best satisfies these requirements?
Set up Cloud VPN to peer with Google Cloud, mirror each BigQuery table into a Cloud SQL for PostgreSQL instance using federation, and point Tableau to the replica with a PostgreSQL driver.
Stream BigQuery data into Cloud Bigtable via Dataflow and connect Tableau through a custom JDBC driver that issues HBase API calls.
Install the Simba BigQuery JDBC or ODBC driver on Tableau Server and configure a service-account-based connection that queries BigQuery over HTTPS (port 443).
Continue exporting BigQuery data to Cloud Storage, but schedule exports every hour and use Tableau's flat-file connector to read the parquet files.
Tableau can connect to BigQuery natively through the Google-supported Simba JDBC or ODBC drivers. The drivers transmit SQL requests over the BigQuery REST API using HTTPS (port 443), so no additional firewall openings are needed beyond the existing HTTPS allowance. Because the connection string and credentials are supplied in Tableau, existing workbooks can be repointed without redesign. Replicating data to Cloud SQL or Bigtable would introduce unnecessary data movement and schema changes, and exporting to Cloud Storage still relies on batch transfers, not direct querying. Therefore, configuring Tableau Server with the BigQuery JDBC or ODBC driver and authenticating with a service account key is the simplest, lowest-effort solution that meets the connectivity and real-time requirements.
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