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Google GCP-DE Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Preparing data for analysis and machine learning13%- Preparing data for ML
  • 1. Feature engineering and data preparation
  • 2. Supporting model training and serving
- Enabling data analysis
  • 1. Optimizing query performance
  • 2. Implementing data sharing and governance
  • 3. Preparing datasets for querying and reporting
Topic 2: Ingesting and processing data25%- Building data pipelines
  • 1. Developing batch and streaming workflows
  • 2. Implementing ingestion mechanisms
  • 3. Handling data quality and consistency
- Transforming data
  • 1. Optimizing transformations for performance
  • 2. Managing schema evolution
  • 3. Applying data processing logic
Topic 3: Maintaining and automating data workloads18%- Operationalizing workloads
  • 1. Monitoring and troubleshooting pipelines
  • 2. Ensuring reliability and recoverability
  • 3. Orchestrating and scheduling jobs
- Automation and optimization
  • 1. Automating deployment and management
  • 2. Optimizing resource usage and costs
Topic 4: Storing and managing data20%- Optimizing storage performance and cost
  • 1. Implementing cost optimization strategies
  • 2. Configuring storage for access patterns
- Implementing storage solutions
  • 1. Using data storage services appropriately
  • 2. Managing data lifecycle and retention
  • 3. Designing data warehouses and data lakes
Topic 5: Designing data processing systems24%- Planning data solutions
  • 1. Planning for data security and compliance
  • 2. Designing for reliability, scalability, and efficiency
  • 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

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Google Data Engineer Sample Questions (Q18-Q23):

NEW QUESTION # 18
Which is not a valid reason for poor Cloud Bigtable performance?

Answer: C

Explanation:
The Cloud Bigtable cluster doesn't have enough nodes. If your Cloud Bigtable cluster is overloaded, adding more nodes can improve performance. Use the monitoring tools to check whether the cluster is overloaded.
Reference: https://cloud.google.com/bigtable/docs/performance


NEW QUESTION # 19
You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

Answer: C


NEW QUESTION # 20
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?

Answer: D


NEW QUESTION # 21
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?

Answer: C


NEW QUESTION # 22
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?

Answer: D


NEW QUESTION # 23
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