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Google Data Engineer Sample Questions:

1. When a Cloud Bigtable node fails, is lost.

A) no data
B) the time dimension
C) the last transaction
D) all data

2. 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) Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.
B) Use feature engineering to add features for eyes, noses, and mouths to the input data.
C) Use K-means Clustering to detect faces in the pixels.
D) Use deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.

3. You launched a new gaming app almost three years ago. You have been uploading log files from the previous day to a separate Google BigQuery table with the table name format LOGS_yyyymmdd. You have been using table wildcard functions to generate daily and monthly reports for all time ranges. Recently, you discovered that some queries that cover long date ranges are exceeding the limit of 1,000 tables and failing. How can you resolve this issue?

A) Create separate views to cover each month, and query from these views
B) Enable query caching so you can cache data from previous months
C) Convert the sharded tables into a single partitioned table
D) Convert all daily log tables into date-partitioned tables

4. Flowlogistic's management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?

A) Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage
B) Cloud Pub/Sub, Cloud Dataflow, and Local SSD
C) Cloud Pub/Sub, Cloud SQL, and Cloud Storage
D) Cloud Load Balancing, Cloud Dataflow, and Cloud Storage

5. You need to deploy additional dependencies to all of a Cloud Dataproc cluster at startup using an existing initialization action. Company security policies require that Cloud Dataproc nodes do not have access to the Internet so public initialization actions cannot fetch resources. What should you do?

A) Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
B) Use Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
C) Copy all dependencies to a Cloud Storage bucket within your VPC security perimeter
D) Deploy the Cloud SQL Proxy on the Cloud Dataproc master

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