PROFESSIONAL-DATA-ENGINEER Online Practice Questions and Answers

Your company has hired a new data scientist who wants to perform complicated analyses across very large datasets stored in Google Cloud Storage and in a Cassandra cluster on Google Compute Engine. The scientist primarily wants to create labelled data sets for machine learning projects, along with some visualization tasks. She reports that her laptop is not powerful enough to perform her tasks and it is slowing her down. You want to help her perform her tasks. What should you do?

A. Run a local version of Jupiter on the laptop.

B. Grant the user access to Google Cloud Shell.

C. Host a visualization tool on a VM on Google Compute Engine.

D. Deploy Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine.

Your company's on-premises Apache Hadoop servers are approaching end-of-life, and IT has decided to migrate the cluster to Google Cloud Dataproc. A like-for-like migration of the cluster would require 50 TB of Google Persistent Disk per node. The CIO is concerned about the cost of using that much block storage. You want to minimize the storage cost of the migration. What should you do?

A. Put the data into Google Cloud Storage.

B. Use preemptible virtual machines (VMs) for the Cloud Dataproc cluster.

C. Tune the Cloud Dataproc cluster so that there is just enough disk for all data.

D. Migrate some of the cold data into Google Cloud Storage, and keep only the hot data in Persistent Disk.

You are designing a system that requires an ACID-compliant database. You must ensure that the system requires minimal human intervention in case of a failure. What should you do?

A. Configure a Cloud SQL for MySQL instance with point-in-time recovery enabled.

B. Configure a Cloud SQL for PostgreSQL instance with high availability enabled.

C. Configure a Bigtable instance with more than one cluster.

D. Configure a BJgQuery table with a multi-region configuration.

You are developing a new deep teaming model that predicts a customer's likelihood to buy on your ecommerce site. Alter running an evaluation of the model against both the original training data and new test data, you find that your model is overfitting the data. You want to improve the accuracy of the model when predicting new data. What should you do?

A. Increase the size of the training dataset, and increase the number of input features.

B. Increase the size of the training dataset, and decrease the number of input features.

C. Reduce the size of the training dataset, and increase the number of input features.

D. Reduce the size of the training dataset, and decrease the number of input features.

The Dataflow SDKs have been recently transitioned into which Apache service?

A. Apache Spark

B. Apache Hadoop

C. Apache Kafka

D. Apache Beam

To run a TensorFlow training job on your own computer using Cloud Machine Learning Engine, what would your command start with?

A. gcloud ml-engine local train

B. gcloud ml-engine jobs submit training

C. gcloud ml-engine jobs submit training local

D. You can't run a TensorFlow program on your own computer using Cloud ML Engine .

Google Cloud Bigtable indexes a single value in each row. This value is called the _______.

A. primary key

B. unique key

C. row key

D. master key

What are two of the characteristics of using online prediction rather than batch prediction?

A. It is optimized to handle a high volume of data instances in a job and to run more complex models.

B. Predictions are returned in the response message.

C. Predictions are written to output files in a Cloud Storage location that you specify.

D. It is optimized to minimize the latency of serving predictions.

Which of these is not a supported method of putting data into a partitioned table?

A. If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.

B. Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".

C. Create a partitioned table and stream new records to it every day.

D. Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".

You want to analyze hundreds of thousands of social media posts daily at the lowest cost and with the fewest steps.

You have the following requirements:

1.

You will batch-load the posts once per day and run them through the Cloud Natural Language API.

2.

You will extract topics and sentiment from the posts.

3.

You must store the raw posts for archiving and reprocessing.

4.

You will create dashboards to be shared with people both inside and outside your organization.

You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?

A. Store the social media posts and the data extracted from the API in BigQuery.

B. Store the social media posts and the data extracted from the API in Cloud SQL.

C. Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.

D. Feed to social media posts into the API directly from the source, and write the extracted data from the API into BigQuery.