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Google GCP-DE Exam Syllabus Topics:

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

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The Google GCP-DE exam is one of the most valuable certification exams. The GCP-DE exam opens a door for beginners or experienced Google professionals to enhance in-demand skills and gain knowledge. GCP-DE credential is proof of candidates' expertise and knowledge. To get all these benefits Google you must have to pass the GCP-DE Exam which is not an easy task. Solutions provide updated, valid, and actual Data Engineer (GCP-DE) Dumps that will assist you in GCP-DE preparation and you can easily get success in this challenging Google GCP-DE exam with flying colors.

Google Data Engineer Sample Questions (Q36-Q41):

NEW QUESTION # 36
You used Cloud Dataprep to create a recipe on a sample of data in a BigQuery table. You want to reuse this recipe on a daily upload of data with the same schema, after the load job with variable execution time completes. What should you do?

Answer: C


NEW QUESTION # 37
Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?

Answer: A,B

Explanation:
using a timestamp as the first element of a row key can cause a variety of problems.
In brief, when a row key for a time series includes a timestamp, all of your writes will target a single node; fill that node; and then move onto the next node in the cluster, resulting in hotspotting.
Suppose your system assigns a numeric ID to each of your application's users. You might be tempted to use the user's numeric ID as the row key for your table. However, since new users are more likely to be active users, this approach is likely to push most of your traffic to a small number of nodes. [https://cloud.google.com/bigtable/docs/schema-design] Reference:
https://cloud.google.com/bigtable/docs/schema-design-time-series#ensure_that_your_row_key_avoids_hotspotti


NEW QUESTION # 38
What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

Answer: A

Explanation:
Triggers control when the elements for a specific key and window are output. As elements arrive, they are put into one or more windows by a Window transform and its associated WindowFn, and then passed to the associated Trigger to determine if the Windows contents should be output.
Reference:
https://cloud.google.com/dataflow/java-sdk/JavaDoc/com/google/cloud/dataflow/sdk/transforms/windowing/Tri


NEW QUESTION # 39
You work for a shipping company that uses handheld scanners to read shipping labels. Your company has strict data privacy standards that require scanners to only transmit recipients' personally identifiable information (PII) to analytics systems, which violates user privacy rules. You want to quickly build a scalable solution using cloud-native managed services to prevent exposure of PII to the analytics systems. What should you do?

Answer: C


NEW QUESTION # 40
You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

Answer: A


NEW QUESTION # 41
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