Google Exam Professional-Data-Engineer Topic 4 Question 73 Discussion

You know, I'm actually kind of curious about the Hive option (option C). Dataproc could give us a bit more flexibility in how we process the data, and using CSV format might be easier to work with than the proprietary format. But I agree, the Beam connector in option D seems like the most straightforward and efficient solution.

Haha, I can just imagine the IT team trying to figure out how to connect that proprietary data format to BigQuery. It's like trying to fit a square peg in a round hole! I think option D is the way to go - the Avro format should be more compatible than CSV, and Dataflow can handle the streaming without too much overhead.

I'm not sure about that. Option B with the Cloud Function batch job sounds promising too. It might be a bit more manual, but if the data format is really complex, it could give us more control over the transformation process. Plus, running it as a batch job could be more efficient than a continuous stream.

Hmm, this is a tricky one. We need to find the most efficient way to get that proprietary data into BigQuery without wasting resources. I'm leaning towards option D - using an Apache Beam custom connector to set up a Dataflow pipeline that streams the data directly into BigQuery in Avro format. That way, we can bypass the raw data storage and transformation steps, which could be resource-intensive.