Exam Professional Machine Learning Engineer topic 1 question 165 discussion

A) Keep the data in BigQuery and create a new table to avoid latency moving data out of BigQuery

A seems the correct one

I go for A:

can export directly from big query as vertex ai managed dataset to use train an autoML model

A By writing a query that preprocesses the data using BigQuery and creating a new table, you can directly create a Vertex AI managed dataset with the new table as the data source. This approach is efficient because it leverages BigQuery’s powerful data processing capabilities and avoids the need to export data to another format or service. It also simplifies the process by keeping everything within the Google Cloud ecosystem. This makes it easier to manage and monitor your data and model training process.

I go for A:

Forgot to vote

A seems the easiest to me: preprocess the data on BigQuery (where the input table is stored) and export directly as Vertex AI managed dataset.

Dataflow seems like the easiest and most scalable way to deal with this issue. Option B.