- Standard connectors and standard tools that allow for seamless integrations with existing SQL workﬂows.
- Regional buckets that enable faster access from storage to compute servers within the region.
- Fully managed relational database services that use edge caching to provide performance.
- Application patches and updates that optimize data processing when it comes to leveraging user data.
High PUC cores and GPUs Ease of use and speed Idle clusters and scaling inﬂexibility Integration and customization Download Google Cloud Platform Business Professional Accreditation Exam Answers (PDF)
With Cloud Firestore, you no longer need to determine the number of nodes or add servers or storage because:
It’s a fully managed compute service. It’s a database service that allows complete control. It’s a database service that uses SQL. It’s a fully managed database service. Download Google Cloud Platform Business Professional Accreditation Exam Answers (PDF)
Cloud Dataﬂow is a tool for developing and executing a wide range of data processing patterns on very large datasets. Which of these examples aligns with what Cloud Dataﬂow can do?
Process queries written in structured query language (SQL). Perform the transformations in “extract, transform, and load (ETL).” Scale without downtime. Develop apps faster and easier with cloud backend services. Download Google Cloud Platform Business Professional Accreditation Exam Answers (PDF)