GCP-DE Exam Questions, GCP-DE study materials. Data Engineer

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Preparing data for analysis and machine learning	13%	- Enabling data analysis 1. Optimizing query performance 2. Implementing data sharing and governance 3. Preparing datasets for querying and reporting - Preparing data for ML 1. Supporting model training and serving 2. Feature engineering and data preparation
Topic 2: Ingesting and processing data	25%	- Building data pipelines 1. Implementing ingestion mechanisms 2. Handling data quality and consistency 3. Developing batch and streaming workflows - Transforming data 1. Applying data processing logic 2. Optimizing transformations for performance 3. Managing schema evolution
Topic 3: Maintaining and automating data workloads	18%	- Automation and optimization 1. Optimizing resource usage and costs 2. Automating deployment and management - Operationalizing workloads 1. Monitoring and troubleshooting pipelines 2. Orchestrating and scheduling jobs 3. Ensuring reliability and recoverability
Topic 4: Storing and managing data	20%	- Implementing storage solutions 1. Designing data warehouses and data lakes 2. Managing data lifecycle and retention 3. Using data storage services appropriately - Optimizing storage performance and cost 1. Implementing cost optimization strategies 2. Configuring storage for access patterns
Topic 5: Designing data processing systems	24%	- Planning data solutions 1. Planning for data security and compliance 2. Selecting appropriate storage solutions 3. Designing for reliability, scalability, and efficiency - Designing data pipelines 1. Designing for data transformation and enrichment 2. Planning for data migration and integration 3. Defining architecture for batch and streaming processing

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For the GCP-DE web-based practice exam no special software installation is required. because it is a browser-based GCP-DE practice test. The web-based Data Engineer practice exam works on all operating systems like Mac, Linux, iOS, Android, and Windows. In the same way, IE, Firefox, Opera and Safari, and all the major browsers support the web-based Google GCP-DE Practice Test. So it requires no special plugins.

Google Data Engineer Sample Questions (Q43-Q48):

NEW QUESTION # 43
You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

A. Process the generated Sentiment Analysis as labels.
B. Call the Cloud Natural Language API from your applicatio
C. Build and train a text classification model using TensorFlo
D. Deploy the model using a KubernetesEngine cluste
E. Process the generated Entity Analysis as labels.
F. Call the Cloud Natural Language API from your applicatio
G. Deploy the model using Cloud Machine Learning Engin
H. Call the model from your application and process the results as labels.
I. Build and train a text classification model using TensorFlo
J. Call the model from your application and process the results as labels.

Answer: E

NEW QUESTION # 44
You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?

A. Cloud Spanner
B. Cloud SQL
C. Cloud Datastore
D. Cloud Bigtable

Answer: B

NEW QUESTION # 45
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. Cloud Bigtable and Cloud SQL
B. Cloud Datastore and Cloud Bigtable
C. BigQuery and Cloud Storage
D. BigQuery and Cloud Bigtable

Answer: D

NEW QUESTION # 46
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

A. Use Cloud Dataflow to transform data to support query patterns.
B. Use Cloud Spanner for storag
C. Use Cloud Spanner for storag
D. Add secondary indexes to support query patterns.
E. Add secondary indexes to support query patterns.
F. Use Cloud Dataflow to transform data to support query patterns.
G. Use Cloud SQL for storag
H. Use Cloud SQL for storag

Answer: F

Explanation:
Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform

NEW QUESTION # 47
Flowlogistic's CEO wants to gain rapid insight into their customer base so his sales team can be better informed in the field. This team is not very technical, so they've purchased a visualization tool to simplify the creation of BigQuery reports. However, they've been overwhelmed by all the data in the table, and are spending a lot of money on queries trying to find the data they need. You want to solve their problem in the most cost-effective way. What should you do?

A. Create an additional table with only the necessary columns.
B. Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.
C. Create a view on the table to present to the virtualization tool.
D. Export the data into a Google Sheet for virtualization.

Answer: C

NEW QUESTION # 48
......

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