Your data science team needs to collaboratively analyze a 25 TB BigQuery dataset to support the development of a machine learning model. You want to use Colab Enterprise notebooks while ensuring efficient data access and minimizing cost. What shout you do?

A. Export the BigQuery dataset to Google Drive. Load the dataset into the Colab Enterprise notebook using Pandas. B. Use BigQuery magic commands within a Colab Enterprise notebook to query and analyze the data. C. Create a Dataproc cluster connected to a Colab Enterprise notebook, and use Spark to process the data BigQuery. D. Copy the BigQuery dataset to the local storage of the Colab Enterprise runtime, and analyze the data using Pandas.