ハイパスレートのADPテキスト一回合格-有難いADP問題数

最近多くの人はIT資格認定試験という悩みがあるようですが、実は、この時代では、Google資格は難しくないです。我々JpexamはIT資格認定試験資料の販売者のリーダーとして、信頼できるADP問題集を提供します。躊躇われずに我々の模擬試験を利用してください。
Google ADP Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|
| Topic 1: Data Analysis and Presentation | 27% | - Data visualization
- 1. Looker / Looker Studio reporting
- Querying and analyzing data
- 1. Data aggregation and transformation
- 2. BigQuery SQL usage
|
| Topic 2: Data Preparation and Ingestion | 30% | - Data ingestion into Google Cloud services
- 1. Cloud Storage ingestion patterns
- 2. Streaming ingestion with Pub/Sub concepts
|
| Topic 3: Data Pipeline Orchestration | 18% | - Pipeline design and automation
- 1. Dataflow pipelines
- 2. Workflow orchestration concepts (e.g., Cloud Composer)
|
| Topic 4: Data Management | 25% | - Data governance and security
- 1. IAM and access control
- 2. Data lifecycle management
- Storage and data organization
- 1. BigQuery datasets and tables management
- 2. Cloud Storage lifecycle policies
|
>> ADPテキスト <<
更新のGoogle ADP: Associate Data Practitionerテキスト - 正確的なJpexam ADP問題数
Jpexamの参考資料に疑問があって、躊躇うなら、あなたは我々のサイトで問題集のサンプルをダウンロードして無料で試すことができます。ADP資料のサンプルによって、この問題集はあなたにふさわしいなら、あなたは安心で問題集を購入することができます。ADP資料を使用したら、あなたは後悔しませんと信じています。
Google Associate Data Practitioner 認定 ADP 試験問題 (Q45-Q50):
質問 # 45
Your organization's ecommerce website collects user activity logs using a Pub/Sub topic. Your organization's leadership team wants a dashboard that contains aggregated user engagement metrics. You need to create a solution that transforms the user activity logs into aggregated metrics, while ensuring that the raw data can be easily queried. What should you do?
- A. Create an event-driven Cloud Run function to trigger a data transformation pipeline to run. Load the transformed activity logs into a BigQuery table for reporting.
- B. Create a BigQuery subscription to the Pub/Sub topic, and load the activity logs into the table. Create a materialized view in BigQuery using SQL to transform the data for reporting
- C. Create a Dataflow subscription to the Pub/Sub topic, and transform the activity logs. Load the transformed data into a BigQuery table for reporting.
- D. Create a Cloud Storage subscription to the Pub/Sub topic. Load the activity logs into a bucket using the Avro file format. Use Dataflow to transform the data, and load it into a BigQuery table for reporting.
正解:C
質問 # 46
Your organization is building a new application on Google Cloud. Several data files will need to be stored in Cloud Storage. Your organization has approved only two specific cloud regions where these data files can reside. You need to determine a Cloud Storage bucket strategy that includes automated high availability.
What should you do?
- A. Create a dual-region bucket, and upload the files to this bucket.
- B. Create a single-region bucket in each of the two regions, and use Storage Transfer Service to replicate the data across the buckets in both regions.
- C. Create a single-region bucket in each of the two regions, and use the gcloud storage command to replicate the data across the buckets in both regions.
- D. Create a multi-region bucket, and upload the files to this bucket.
正解:A
質問 # 47
Your team is building several data pipelines that contain a collection of complex tasks and dependencies that you want to execute on a schedule, in a specific order. The tasks and dependencies consist of files in Cloud Storage, Apache Spark jobs, and data in BigQuery. You need to design a system that can schedule and automate these data processing tasks using a fully managed approach. What should you do?
- A. Use Cloud Scheduler to schedule the jobs to run.
- B. Create directed acyclic graphs (DAGS) in Cloud Composer. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.
- C. Use Cloud Tasks to schedule and run the jobs asynchronously.
- D. Create directed acyclic graphs (DAGS) in Apache Airflow deployed on Google Kubernetes Engine. Use the appropriate operators to connect to Cloud Storage, Spark, and BigQuery.
正解:B
質問 # 48
You have a BigQuery dataset containing sales dat
a. This data is actively queried for the first 6 months. After that, the data is not queried but needs to be retained for 3 years for compliance reasons. You need to implement a data management strategy that meets access and compliance requirements, while keeping cost and administrative overhead to a minimum. What should you do?
- A. Use BigQuery long-term storage for the entire dataset. Set up a Cloud Run function to delete the data from BigQuery after 3 years.
- B. Store all data in a single BigQuery table without partitioning or lifecycle policies.
- C. Set up a scheduled query to export the data to Cloud Storage after 6 months. Write a stored procedure to delete the data from BigQuery after 3 years.
- D. Partition a BigQuery table by month. After 6 months, export the data to Coldline storage. Implement a lifecycle policy to delete the data from Cloud Storage after 3 years.
正解:D
質問 # 49
Your company's customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files' metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?
- A. Create a temporary table.
- B. Create an external table.
- C. Create an object table.
- D. Create a native table.
正解:C
質問 # 50
......
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