Google GCP-DE日本語サンプル & GCP-DEクラムメディア

社会の発展と相対的な法律と規制の完成により、私たちのキャリア分野でのGCP-DE証明書は私たちの国にとって必要になります。 GCP-DEに合格して証明書を取得することが、あなたの立場を変えて目標を達成するための最も迅速で直接的な方法かもしれません。そして、私たちはあなたを助けるためにちょうどここにいます。このキャリアで最も本物のブランドと見なされているプロの専門家は、お客様に最新の有効なGCP-DE試験シミュレーションを提供するために絶え間ない努力を行っています。

Google GCP-DE Exam Syllabus Topics:

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

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Google Data Engineer 認定 GCP-DE 試験問題 (Q26-Q31):

質問 # 26
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?

正解：D


質問 # 27
Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?

正解：A、D

解説：
The following rules will apply when you use preemptible workers with a Cloud Dataproc cluster: Processing only-Since preemptibles can be reclaimed at any time, preemptible workers do not store data.
Preemptibles added to a Cloud Dataproc cluster only function as processing nodes.
No preemptible-only clusters-To ensure clusters do not lose all workers, Cloud Dataproc cannot create preemptible-only clusters.
Persistent disk size-As a default, all preemptible workers are created with the smaller of 100GB or the primary worker boot disk size. This disk space is used for local caching of data and is not available through HDFS.
The managed group automatically re-adds workers lost due to reclamation as capacity permits. Reference:
https://cloud.google.com/dataproc/docs/concepts/preemptible-vms


質問 # 28
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?

正解：B


質問 # 29
Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.
You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

正解：D、F


質問 # 30
What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

正解：A

解説：
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


質問 # 31
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