Preparing Practice Exam…
Please wait a moment while the system generates the exam questions, answers, and study session.
Please wait a moment while the system generates the exam questions, answers, and study session.
Google Cloud Certified Professional Data Engineer · Google Cloud
Select one answer.
Written by other learners. Comments can disagree with the marked answer — check the official documentation when in doubt.
Every time you hear financial, time series, fast reads and write data, Any of that combinations, think Big Table first. So A.
At first I thought that GCS was the answer but the question does mention that the data is updated frequently. Thereby, it has to be BigTable since we talk about a large amount of data, a streaming application and many individual updates. Storing the data in BigQuery and having to make individual updates doesn't make sense, and neither does running Apache jobs. If the requirement for updates was not there I would not see any issue with GCS. GCS could serve as a replacement to HDFS and run Hadoop jobs from Dataproc.
This scenario screams for BigTable. It's not B) BigQuery or C) Cloud Storage because both aren't supposed to contain data that is updated frequently. Then, we have to decide between A) BigTable and D) Datastore. It is A) BigTable because - it is the most suited for real-time / high-frequency updates - it is similar to HBase, which is commonly used in Hadoop ecosystem stacks to store streaming / time-series data.