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Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer Sample Questions (Q19-Q24):

NEW QUESTION # 19
Which of the following statements is NOT true regarding Bigtable access roles?

A. Using IAM roles, you cannot give a user access to only one table in a project, rather than all tables in a project.
B. You can configure access control only at the project level.
C. To give a user access to only one table in a project, grant the user the Bigtable Editor role for that table.
D. To give a user access to only one table in a project, you must configure access through your application.

Answer: C

Explanation:
For Cloud Bigtable, you can configure access control at the project level. For example, you can grant the ability to:
Read from, but not write to, any table within the project.
Read from and write to any table within the project, but not manage instances. Read from and write to any table within the project, and manage instances. Reference: https://cloud.google.com/bigtable/docs/access-control

NEW QUESTION # 20
You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems. Which solutions should you choose?

A. Dialogflow Enterprise Edition
B. Cloud AutoML Natural Language
C. Cloud Natural Language API
D. Cloud Speech-to-Text API

Answer: B

NEW QUESTION # 21
You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
B. Create a temporary table in Cloud Spanner that will act as a buffer for new data
C. Create a temporary table in Cloud Bigtable that will act as a buffer for new data
D. Use a larger instance type for your Cloud Dataflow workers
E. Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
F. Increase the number of max workers
G. Change the zone of your Cloud Dataflow pipeline to run in us-central1

Answer: A,D

NEW QUESTION # 22
You receive data files in CSV format monthly from a third party. You need to cleanse this data, but every third month the schema of the files changes. Your requirements for implementing these transformations include:
Executing the transformations on a schedule
Enabling non-developer analysts to modify transformations
Providing a graphical tool for designing transformations
What should you do?

A. Load each month's CSV data into BigQuery, and write a SQL query to transform the data to a standard scheme
B. Use Apache Spark on Cloud Dataproc to infer the schema of the CSV file before creating a Dataframe.Then implement the transformations in Spark SQL before writing the data out to Cloud Storage and loading into BigQuery
C. Help the analysts write a Cloud Dataflow pipeline in Python to perform the transformatio
D. The Python code should be stored in a revision control system and modified as the incoming data's schema changes
E. Use Cloud Dataprep to build and maintain the transformation recipes, and execute them on a scheduled basis
F. Merge the transformed tables together with a SQL query

Answer: C

NEW QUESTION # 23
You need to choose a database for a new project that has the following requirements:
Fully managed
Able to automatically scale up
Transactionally consistent
Able to scale up to 6 TB
Able to be queried using SQL Which database do you choose?

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

Answer: D

NEW QUESTION # 24
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