Which tool is used for monitoring data quality in pipelines on Google Cloud?

Dataflow is indeed the appropriate tool for monitoring data quality in pipelines on Google Cloud. It is a fully managed service designed to execute data processing pipelines, allowing users to handle stream and batch data efficiently. One of the key features of Dataflow is its ability to incorporate data quality checks directly into the pipelines. This can include validation, cleansing, and transformations as data flows through the pipeline, ensuring that the output meets the required quality standards.

Moreover, Dataflow provides monitoring and management tools integrated with Google Cloud Stackdriver, which allows users to track the performance of their data processing jobs, detect anomalies, and implement alerts based on specific data quality metrics. This makes it easier to ensure that the data being processed adheres to pre-defined quality guidelines.

In contrast, while Cloud Functions and Cloud Pub/Sub are valuable tools for serverless computing and messaging, respectively, they are not specifically designed for monitoring data quality in the context of data pipelines. BigQuery is primarily a data warehousing solution and although it can perform some data quality checks through SQL queries, it lacks the pipeline-specific monitoring and real-time processing capabilities of Dataflow. Thus, Dataflow stands out as the most suitable option for ensuring data quality in pipeline processes on Google Cloud.