GCP-DE유효한공부문제 & GCP-DE최신기출자료

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Google GCP-DE Exam Syllabus Topics:

Section	Weight	Objectives
Managing and optimizing solutions	20%-25%	- Managing resources and costs 1. Tune query and pipeline performance 2. Control operational costs 3. Optimize storage and compute usage - Reliability and scalability 1. Design highly available systems 2. Implement disaster recovery strategies 3. Scale data workloads efficiently
Ensuring solution quality	20%-25%	- Data quality management 1. Maintain metadata and lineage 2. Implement data governance 3. Validate and clean data - Security and compliance 1. Implement encryption and compliance controls 2. Protect sensitive data 3. Manage IAM and access control
Building and operationalizing data processing systems	28%-33%	- Operationalizing systems 1. Manage logging and alerting 2. Monitor data pipelines and workloads 3. Implement fault tolerance and recovery - Building data processing systems 1. Use BigQuery, Dataflow, Pub/Sub, Dataproc and related services 2. Implement batch processing systems 3. Implement streaming data systems
Designing data processing systems	22%-27%	- Designing for data ingestion 1. Select appropriate storage systems 2. Design batch and streaming ingestion solutions 3. Design scalable and reliable ingestion architecture - Designing data pipelines 1. Design orchestration workflows 2. Build ETL and ELT pipelines 3. Optimize pipeline performance and cost

>> GCP-DE유효한 공부문제 <<

GCP-DE유효한 공부문제 인증시험 덤프자료

Google GCP-DE덤프구매에 관심이 있는데 선뜻 구매결정을 하지 못하는 분이라면 사이트에 있는 demo를 다운받아 보시면Google GCP-DE시험패스에 믿음이 생길것입니다. Google GCP-DE덤프는 시험문제변경에 따라 업데이트하여 항상 가장 최선버전이도록 유지하기 위해 최선을 다하고 있습니다.

최신 Google Cloud Certified GCP-DE 무료샘플문제 (Q14-Q19):

질문 # 14
You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

A. Set the BigQuery dataset to be regiona
B. In the event of an emergency, use the backup copy of the table.
C. In the event of an emergency, use a point-in-time snapshot to recover the data.
D. Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
E. Set the BigQuery dataset to be regiona
F. Set the BigQuery dataset to be multi-regional
G. Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
H. Set the BigQuery dataset to be multi-regional
I. In the event of an emergency, use the backup copy of the table.
J. In the event of an emergency, use a point-in-time snapshot to recover the data.

정답：J

질문 # 15
You are building a new application that you need to collect data from in a scalable way. Data arrives continuously from the application throughout the day, and you expect to generate approximately 150 GB of JSON data per day by the end of the year. Your requirements are: Decoupling producer from consumer Space and cost-efficient storage of the raw ingested data, which is to be stored indefinitely Near real-time SQL query Maintain at least 2 years of historical data, which will be queried with SQ Which pipeline should you use to meet these requirements?

A. Create an application that publishes events to Cloud Pub/Sub, and create a Cloud Dataflow pipeline that transforms the JSON event payloads to Avro, writing the data to Cloud Storage and BigQuery.
B. Create an application that publishes events to Cloud Pub/Sub, and create Spark jobs on Cloud Dataproc to convert the JSON data to Avro format, stored on HDFS on Persistent Disk.
C. Write a tool to poll the API and write data to Cloud Storage as gzipped JSON files.
D. Create an application that provides an AP
E. Set up periodic exports of the database to write to Cloud Storage and load into BigQuery.
F. Create an application that writes to a Cloud SQL database to store the dat

정답：D

질문 # 16
What is the general recommendation when designing your row keys for a Cloud Bigtable schema?

A. Keep your row key as long as the field permits
B. Include multiple time series values within the row key
C. Keep the row keep as an 8 bit integer
D. Keep your row key reasonably short

정답：D

설명：
A general guide is to, keep your row keys reasonably short. Long row keys take up additional memory and storage and increase the time it takes to get responses from the Cloud Bigtable server.
Reference: https://cloud.google.com/bigtable/docs/schema-design#row-keys

질문 # 17
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?

A. Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.
B. Write an Apache Beam pipeline that creates a BigQuery table per data
C. Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.
D. Partition the tables by a column containing a TIMESTAMP or DATE Type.
E. Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.
F. Re-create the tables using DD

정답：C

질문 # 18
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?

A. Cloud Bigtable and Cloud SQL
B. BigQuery and Cloud Bigtable
C. Cloud Datastore and Cloud Bigtable
D. BigQuery and Cloud Storage

정답：B

질문 # 19
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