Which of the following Google Cloud tools would be most appropriate for scheduling, automating, and monitoring a data processing task that needs to run daily in a data pipeline?

Your team is running a Dataflow streaming job to process and transform log data in real time. You notice a delay in the processed data reaching BigQuery, which suggests a potential bottleneck in the pipeline. You open the Dataflow Job UI to investigate. Which of the following steps in the Dataflow Job UI would be the most effective first step to identify where the bottleneck is occurring?

Your team receives weekly data updates from an external SaaS platform that must be loaded into BigQuery for analysis. The data is delivered via an API in JSON format. Which Google Cloud service is best suited for scheduling and automating the ingestion of this external data into BigQuery?

A data team is using Google Cloud to process a large dataset with inconsistent date formats, empty strings, and incorrectly capitalized text values. They want to standardize these formats, remove empty strings, and apply other basic data-cleaning operations. Which service should they use to process this data efficiently using SQL-like queries?

A financial services company processes data on stock trades and needs a pipeline to automate data ingestion, transformation, and loading every hour. They require a solution with fine-grained scheduling capabilities, dependency management between tasks, and automatic retries in case of failure. The company also wants to monitor job status and receive alerts when issues occur. Which Google Cloud service best meets these requirements?