Incoming data is written to BigQuery but is dirty; you need an automated daily data-quality/cleaning process that controls cost. What should you implement?

Cloud Dataprep is a fully managed, serverless data preparation service designed for exploring, cleaning, and preparing data for analysis. It integrates natively with BigQuery, allowing you to use BigQuery tables as sources and destinations. Scheduling a daily cleanup job directly within Dataprep provides an automated, cost-effective solution for data quality, as you only pay for the processing time. Streaming Cloud Dataflow is overkill for a daily batch process and more complex to set up for simple cleaning. A Cloud Function triggered by a Compute Engine instance adds unnecessary infrastructure and complexity compared to Dataprep's integrated scheduling. A SQL view in BigQuery can transform data but lacks the robust data profiling, visual interface, and advanced cleaning capabilities of Dataprep, making it less efficient for "dirty" data.