Let's try some sample exam questions. Ready? The first question is, you need a storage solution for CSV files. Analysts will run ANSI SQL queries. You need to support complex aggregate queries, and reuse existing I/O-intensive custom Apache Spark transformations. How should you transform the input data? Looks like you've got a choice of BigQuery, or cloud storage for the storage part of the solution, and Cloud Dataflow or Cloud Dataproc for the transformation and processing part of the solution. Do you have an answer? How confident are you in the answer? This is a good time to consider whether you would bookmark this question and come back to it during an exam, or whether you feel confident in your answer. Let's see what the correct answer is. The correct answer is B, use BigQuery for the storage solution, and Cloud Dataproc for the processing solution. Okay, Cloud Dataproc is correct because the question states you need to plan to reuse Apache Spark code. The CSV files could be in Cloud Storage, or could be ingested into BigQuery. In this case, you need to support complex SQL queries, so best to use BigQuery for storage. This was not a once in a while straightforward case where you might consider just keeping the data in cloud storage. Ready for another one? You are selecting a streaming service for log messages that must include final result message ordering as part of building a data pipeline on Google Cloud. You want to stream input for five days, and be able to query the most recent message value. You'll be storing the data in a searchable repository. How should you set up the input messages? Ready to see the solution? The answer this time is A, Cloud Pub/Sub for input, and attach a timestamp at the publisher. We can kind of figure that Apache Kafka is not the recommended solution in this scenario because you would have to set it up and maintain it. That could be a lot of work. Why not just use the Cloud Pub/Sub service and eliminate the overhead. You need a timestamp to implement the rest of the solution. So, applying it at ingest in the publisher is a good consistent way to get the timestamp that's required.