Google Professional-Cloud-Database-Engineer Exam With Confidence Using Practice Dumps

Create extracts from your on-premises databases periodically, and push these extracts to Cloud Storage.

Upload the changes into BigQuery, and merge them with existing tables.

Use Cloud Data Fusion and scheduled workflows to extract data from MySQL. Transform this data into the appropriate schema, and load this data into your BigQuery database.

Use Datastream to connect to your on-premises database and create a stream. Have Datastream write to Cloud Storage. Then use Dataflow to process the data into BigQuery.

Use Database Migration Service to replicate data to a Cloud SQL for MySQL instance. Create federated tables in BigQuery on top of the replicated instances to transform and load the data into your BigQuery database.

Create a Cloud SQL instance in HA mode with a cross-region read replica.

Create an AlloyDB instance in HA mode with a cross-region read replica.

Create a spanner instance across regions for optimal performance.

Implement Bigtable with replication across multiple regions and configure to prioritize data accuracy.

Take nightly snapshots of the primary database instance, and restore them in a secondary zone.

Build a change data capture (CDC) pipeline to read transactions from the primary instance, and replicate them to a secondary instance.

Create a read replica in another region, and promote the read replica if a failure occurs.

Enable high availability (HA) for the database to make it regional.