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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

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

2. All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.

A) before
B) once
C) after
D) only if

3. MJTelco is building a custom interface to share dat
a. They have these requirements:
They need to do aggregations over their petabyte-scale datasets.
They need to scan specific time range rows with a very fast response time (milliseconds). Which combination of Google Cloud Platform products should you recommend?

A) BigQuery and Cloud Storage
B) BigQuery and Cloud Bigtable
C) Cloud Bigtable and Cloud SQL
D) Cloud Datastore and Cloud Bigtable

4. You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A) Add a new column called FullName to the Users tabl
B) Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.
C) Use BigQuery to export the data for the table to a CSV fil
D) Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
E) Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
F) Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.

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

Solutions: