Google PROFESSIONAL-DATA-ENGINEER Exam Questions & Answers

Suppose you have a dataset of images that are each labeled as to whether or not they contain a human face. To create a neural network that recognizes human faces in images using this labeled dataset, what approach would likely be the most effective?

A. Use K-means Clustering to detect faces in the pixels.

B. Use feature engineering to add features for eyes, noses, and mouths to the input data.

C. Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.

D. Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.

You have a data pipeline with a Dataflow job that aggregates and writes time series metrics to Bigtable. You notice that data is slow to update in Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the data. What should you do?

Choose 2 answers

A. Configure your Dataflow pipeline to use local execution.

B. Modify your Dataflow pipeline lo use the Flatten transform before writing to Bigtable.

C. Modify your Dataflow pipeline to use the CoGrcupByKey transform before writing to Bigtable.

D. Increase the maximum number of Dataflow workers by setting maxNumWorkers in PipelineOptions.

E. Increase the number of nodes in the Bigtable cluster.

You operate a logistics company, and you want to improve event delivery reliability for vehicle-based sensors. You operate small data centers around the world to capture these events, but leased lines that provide connectivity from your event collection infrastructure to your event processing infrastructure are unreliable, with unpredictable latency. You want to address this issue in the most cost-effective way. What should you do?

A. Deploy small Kafka clusters in your data centers to buffer events.

B. Have the data acquisition devices publish data to Cloud Pub/Sub.

C. Establish a Cloud Interconnect between all remote data centers and Google.

D. Write a Cloud Dataflow pipeline that aggregates all data in session windows.