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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q57-Q62):

NEW QUESTION # 57
Which of these is not a supported method of putting data into a partitioned table?

A. If you have existing data in a separate file for each day, then create a partitioned table and upload each file into the appropriate partition.
B. Use ORDER BY to put a table's rows into chronological order and then change the table's type to "Partitioned".
C. Run a query to get the records for a specific day from an existing table and for the destination table, specify a partitioned table ending with the day in the format "$YYYYMMDD".
D. Create a partitioned table and stream new records to it every day.

Answer: B

Explanation:
You cannot change an existing table into a partitioned table. You must create a partitioned table from scratch. Then you can either stream data into it every day and the data will automatically be put in the right partition, or you can load data into a specific partition by using "$YYYYMMDD" at the end of the table name. Reference: https://cloud.google.com/bigquery/docs/partitioned-tables

NEW QUESTION # 58
You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

A. Workflow Templates on Cloud Dataproc
B. Cloud Composer
C. Cloud Scheduler
D. cron

Answer: A

NEW QUESTION # 59
You work for a manufacturing company that sources up to 750 different components, each from a different supplier. You've collected a labeled dataset that has on average 1000 examples for each unique component. Your team wants to implement an app to help warehouse workers recognize incoming components based on a photo of the component. You want to implement the first working version of this app (as Proof-Of-Concept) within a few working days. What should you do?

A. Use Cloud Vision API by providing custom labels as recognition hints.
B. Use Cloud Vision AutoML with the existing dataset.
C. Use Cloud Vision AutoML, but reduce your dataset twice.
D. Train your own image recognition model leveraging transfer learning techniques.

Answer: B

NEW QUESTION # 60
You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
The user profile: What the user likes and doesn't like to eat
The user account information: Name, address, preferred meal times
The order information: When orders are made, from where, to whom
The database will be used to store all the transactional data of the product. You want to optimize the data schem a. Which Google Cloud Platform product should you use?

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

Answer: B

NEW QUESTION # 61
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 Resource Manager to add the service account used by the Cloud Dataproc cluster to the Network User role
B. Use an SSH tunnel to give the Cloud Dataproc cluster access to the Internet
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

Answer: A

NEW QUESTION # 62
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