Professional-Data-Engineer시험덤프공부 - Google Certified Professional-Data-Engineer Exam인기시험 - Omgzlook

Omgzlook의Google인증 Professional-Data-Engineer시험덤프공부덤프와의 근사한 만남이Google인증 Professional-Data-Engineer시험덤프공부패스에 화이팅을 불러드립니다. 덤프에 있는 문제만 공부하면 되기에 시험일이 며칠뒤라도 시험패스는 문제없습니다. 더는 공부하지 않은 자신을 원망하지 마시고 결단성있게Omgzlook의Google인증 Professional-Data-Engineer시험덤프공부덤프로 시험패스에 고고싱하세요. 학원다니면서 많은 지식을 장악한후Google Professional-Data-Engineer시험덤프공부시험보시는것도 좋지만 회사다니느랴 야근하랴 시간이 부족한 분들은Google Professional-Data-Engineer시험덤프공부덤프만 있으면 엄청난 학원수강료 필요없이 20~30시간의 독학만으로도Google Professional-Data-Engineer시험덤프공부시험패스가 충분합니다. 또한 취업생분들은 우선 자격증으로 취업문을 두드리고 일하면서 실무를 익혀가는방법도 좋지 않을가 생각됩니다. Omgzlook덤프를 IT국제인증자격증 시험대비자료중 가장 퍼펙트한 자료로 거듭날수 있도록 최선을 다하고 있습니다.

Google Cloud Certified Professional-Data-Engineer 체험 후 우리의Omgzlook에 신뢰감을 느끼게 됩니다.

Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam시험덤프공부덤프의 무료샘플을 원하신다면 우의 PDF Version Demo 버튼을 클릭하고 메일주소를 입력하시면 바로 다운받아Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam시험덤프공부덤프의 일부분 문제를 체험해 보실수 있습니다. 그리고 중요한 건 시험과 매우 유사한 시험문제와 답도 제공해드립니다. Omgzlook 을 선택하면 Omgzlook 는 여러분을 빠른시일내에 시험관련지식을 터득하게 할 것이고Google Professional-Data-Engineer 시험유효자료인증시험도 고득점으로 패스하게 해드릴 것입니다.

만약 시험만 응시하고 싶으시다면 우리의 최신Google Professional-Data-Engineer시험덤프공부자료로 시험 패스하실 수 있습니다. Omgzlook 의 학습가이드에는Google Professional-Data-Engineer시험덤프공부인증시험의 예상문제, 시험문제와 답 임으로 100% 시험을 패스할 수 있습니다.우리의Google Professional-Data-Engineer시험덤프공부시험자료로 충분한 시험준비하시는것이 좋을것 같습니다. 그리고 우리는 일년무료 업데이트를 제공합니다.

Google Professional-Data-Engineer시험덤프공부 - 만약 여러분이 시험에서 떨어졌다면 우리는 덤프비용전액을 환불해드립니다.

Google Professional-Data-Engineer시험덤프공부인증시험패스에는 많은 방법이 있습니다. 먼저 많은 시간을 투자하고 신경을 써서 전문적으로 과련 지식을 터득한다거나; 아니면 적은 시간투자와 적은 돈을 들여 Omgzlook의 인증시험덤프를 구매하는 방법 등이 있습니다.

Omgzlook연구한 전문Google Professional-Data-Engineer시험덤프공부인증시험을 겨냥한 덤프가 아주 많은 인기를 누리고 있습니다. Omgzlook제공되는 자료는 지식을 장악할 수 있는 반면 많은 경험도 쌓을 수 있습니다.

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
You are building a model to make clothing recommendations. You know a user's fashion preference is likely to change over time, so you build a data pipeline to stream new data back to the model as it becomes available.
How should you use this data to train the model?
A. Continuously retrain the model on just the new data.
B. Continuously retrain the model on a combination of existing data and the new data.
C. Train on the new data while using the existing data as your test set.
D. Train on the existing data while using the new data as your test set.
Answer: C

QUESTION NO: 2
For the best possible performance, what is the recommended zone for your Compute Engine instance and Cloud Bigtable instance?
A. Have both the Compute Engine instance and the Cloud Bigtable instance to be in different zones.
B. Have the Compute Engine instance in the furthest zone from the Cloud Bigtable instance.
C. Have the Cloud Bigtable instance to be in the same zone as all of the consumers of your data.
D. Have both the Compute Engine instance and the Cloud Bigtable instance to be in the same zone.
Answer: D
Explanation
It is recommended to create your Compute Engine instance in the same zone as your Cloud Bigtable instance for the best possible performance, If it's not possible to create a instance in the same zone, you should create your instance in another zone within the same region. For example, if your Cloud
Bigtable instance is located in us-central1-b, you could create your instance in us-central1-f. This change may result in several milliseconds of additional latency for each Cloud Bigtable request.
It is recommended to avoid creating your Compute Engine instance in a different region from your
Cloud Bigtable instance, which can add hundreds of milliseconds of latency to each Cloud Bigtable request.
Reference: https://cloud.google.com/bigtable/docs/creating-compute-instance

QUESTION NO: 3
You have an Apache Kafka Cluster on-prem with topics containing web application logs. You need to replicate the data to Google Cloud for analysis in BigQuery and Cloud Storage. The preferred replication method is mirroring to avoid deployment of Kafka Connect plugins.
What should you do?
A. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a Sink connector. Use a Dataflow job to read fron PubSub and write to GCS.
B. Deploy a Kafka cluster on GCE VM Instances. Configure your on-prem cluster to mirror your topics to the cluster running in GCE. Use a Dataproc cluster or Dataflow job to read from Kafka and write to
GCS.
C. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a
Source connector. Use a Dataflow job to read fron PubSub and write to GCS.
D. Deploy a Kafka cluster on GCE VM Instances with the PubSub Kafka connector configured as a Sink connector. Use a Dataproc cluster or Dataflow job to read from Kafka and write to GCS.
Answer: B

QUESTION NO: 4
Which Google Cloud Platform service is an alternative to Hadoop with Hive?
A. Cloud Datastore
B. Cloud Bigtable
C. BigQuery
D. Cloud Dataflow
Answer: C
Explanation
Apache Hive is a data warehouse software project built on top of Apache Hadoop for providing data summarization, query, and analysis.
Google BigQuery is an enterprise data warehouse.
Reference: https://en.wikipedia.org/wiki/Apache_Hive

QUESTION NO: 5
You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need an instant notification to be sent to your monitoring tool when new data is appended to a certain table using an insert job, but you do not want to receive notifications for other tables. What should you do?
A. Using the Stackdriver API, create a project sink with advanced log filter to export to Pub/Sub, and subscribe to the topic from your monitoring tool.
B. In the Stackdriver logging admin interface, enable a log sink export to Google Cloud Pub/Sub, and subscribe to the topic from your monitoring tool.
C. In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.
D. Make a call to the Stackdriver API to list all logs, and apply an advanced filter.
Answer: C

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Updated: May 27, 2022