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Google GCP-DE Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Ingesting and processing data | 25% | - Transforming data
|
| Storing and managing data | 20% | - Implementing storage solutions
|
| Preparing data for analysis and machine learning | 13% | - Preparing data for ML
|
| Designing data processing systems | 24% | - Planning data solutions
|
| Maintaining and automating data workloads | 18% | - Automation and optimization
|
Google Data Engineer Sample Questions:
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 SQL, and Cloud Storage
- D. Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage
Correct Answer: C 🗳️
Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.
SELECT person FROM `project1.example.table1` WHERE city = "London"
How would you correct the error?
- A. Add ", UNNEST(city)" before the WHERE clause.
- B. Change "person" to "person.city".
- C. Add ", UNNEST(person)" before the WHERE clause.
- D. Change "person" to "city.person".
Correct Answer: C 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
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 deep learning by creating a neural network with multiple hidden layers to automatically detect features of faces.
- 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. Build a neural network with an input layer of pixels, a hidden layer, and an output layer with two categories.
Correct Answer: A 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
Which Google Cloud Platform service is an alternative to Hadoop with Hive?
- A. Cloud Datastore
- B. BigQuery
- C. Cloud Bigtable
- D. Cloud Dataflow
Correct Answer: B 🗳️
Explanation: Only visible for VCE4Plus members. You can sign-up / login (it's free).
As your organization expands its usage of GCP, many teams have started to create their own projects. Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects. Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies. Which two steps should you take? Choose 2 answers.
- A. Create distinct groups for various teams, and specify groups in Cloud IAM policies.
- B. For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces
- C. Use Cloud Deployment Manager to automate access provision.
- D. Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
- E. Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
- F. Introduce resource hierarchy to leverage access control policy inheritance.
Correct Answer: A,F 🗳️
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