GCP-DE模試エンジン & GCP-DE専門知識内容

このインターネット時代において、社会の発展とともに、コストがより低くて内容が完全な情報が不可欠です。弊社のGCP-DE問題集は他のサイトに比べて、試験の範囲をカバーすることはより広くて、合理的な価格があります。しかしも、品質はもっと高くて一度GCP-DE試験に合格したい客様に対して、我が社のGCP-DEはあなたの最高選択かつ成功のショートカットであると思われます。

Google GCP-DE Exam Syllabus Topics:

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

>> GCP-DE模試エンジン <<

GCP-DE試験の準備方法｜権威のあるGCP-DE模試エンジン試験｜完璧なData Engineer専門知識内容

今の競争が激しい社会にあたり、あなたは努力して所有したいことがあります。IT職員にとって、GCP-DE試験認定書はあなたの実力を証明できる重要なツールです。だから、Google GCP-DE試験に合格する必要があります。それで、弊社の質高いGCP-DE試験資料を薦めさせてください。

Google Data Engineer 認定 GCP-DE 試験問題 (Q58-Q63):

質問 # 58
You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

A. Add secondary indexes to support query patterns.
B. Use Cloud Dataflow to transform data to support query patterns.
C. Use Cloud Dataflow to transform data to support query patterns.
D. Use Cloud SQL for storag
E. Use Cloud Spanner for storag
F. Use Cloud Spanner for storag
G. Add secondary indexes to support query patterns.
H. Use Cloud SQL for storag

正解：B

解説：
Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform

質問 # 59
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. In the event of an emergency, use the backup copy of the table.
B. Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
C. Set the BigQuery dataset to be multi-regional
D. Set the BigQuery dataset to be regiona
E. Set the BigQuery dataset to be multi-regional
F. Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
G. In the event of an emergency, use a point-in-time snapshot to recover the data.
H. In the event of an emergency, use the backup copy of the table.
I. Set the BigQuery dataset to be regiona
J. In the event of an emergency, use a point-in-time snapshot to recover the data.

正解：G

質問 # 60
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)?

A. A sequential numeric ID
B. A non-sequential numeric ID
C. A timestamp followed by a stock symbol
D. A stock symbol followed by a timestamp

正解：A、C

解説：
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

質問 # 61
You have enabled the free integration between Firebase Analytics and Google BigQuery. Firebase now automatically creates a new table daily in BigQuery in the format app_events_YYYYMMDD. You want to query all of the tables for the past 30 days in legacy SQL. What should you do?

A. Use the TABLE_DATE_RANGE function
B. Use WHERE date BETWEEN YYYY-MM-DD AND YYYY-MM-DD
C. Use the WHERE_PARTITIONTIME pseudo column
D. Use SELECT IF.(date >= YYYY-MM-DD AND date <= YYYY-MM-DD

正解：A

解説：
Reference:
https://cloud.google.com/blog/products/gcp/using-bigquery-and-firebase-analytics-to-understandyour-mobile-ap

質問 # 62
When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a proxy.

A. SOCKS
B. HTTP
C. VPN
D. HTTPS

正解：A

解説：
When using Cloud Dataproc clusters, configure your browser to use the SOCKS proxy. The SOCKS proxy routes data intended for the Cloud Dataproc cluster through an SSH tunnel.
Reference: https://cloud.google.com/dataproc/docs/concepts/cluster-web-interfaces#interfaces

質問 # 63
......

数年以来の整理と分析によって開発されたGCP-DE問題集は権威的で全面的です。GCP-DE問題集を利用して試験に合格できます。この問題集の合格率は高いので、多くのお客様からGCP-DE問題集への好評をもらいました。GCP-DE問題集のカーバー率が高いので、勉強した問題は試験に出ることが多いです。だから、弊社の提供するGCP-DE問題集を暗記すれば、きっと試験に合格できます。

GCP-DE専門知識内容: https://www.it-passports.com/GCP-DE.html