現在IT技術会社に通勤しているあなたは、GoogleのProfessional-Data-Engineer合格体験談試験認定を取得しましたか？Professional-Data-Engineer合格体験談試験認定は給料の増加とジョブのプロモーションに役立ちます。短時間でProfessional-Data-Engineer合格体験談試験に一発合格したいなら、我々社のGoogleのProfessional-Data-Engineer合格体験談資料を参考しましょう。また、Professional-Data-Engineer合格体験談問題集に疑問があると、メールで問い合わせてください。 弊社の信頼できるProfessional-Data-Engineer合格体験談問題集を使用したお客様はほとんど試験に合格しました。弊社はお客様の皆様の利益を保証するために、あなたに高いクオリティのサービスを提供できて努力しています。 だから、我々社は力の限りで弊社のGoogle　Professional-Data-Engineer合格体験談試験資料を改善し、改革の変更に応じて更新します。

Google Cloud Certified Professional-Data-Engineer 早くShobhadoshiの問題集を君の手に入れましょう。

Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam合格体験談試験に合格することは簡単ではなくて、適切な訓练を選ぶのはあなたの成功の第一歩です。 君が後悔しないようにもっと少ないお金を使って大きな良い成果を取得するためにShobhadoshiを選択してください。Shobhadoshiはまた一年間に無料なサービスを更新いたします。

Shobhadoshiは君の試験に合格させるだけでなく本当の知識を学ばれます。Shobhadoshiはあなたが100% でProfessional-Data-Engineer合格体験談試験に合格させるの保証することができてまたあなたのために一年の無料の試験の練習問題と解答の更新サービス提供して、もし試験に失敗したら、弊社はすぐ全額で返金を保証いたします。

Google Professional-Data-Engineer合格体験談 - Shobhadoshiには専門的なエリート団体があります。

あなたのGoogleのProfessional-Data-Engineer合格体験談認証試験に合格させるのはShobhadoshiが賢明な選択で購入する前にインターネットで無料な問題集をダウンロードしてください。そうしたらあなたがGoogleのProfessional-Data-Engineer合格体験談認定試験にもっと自信を増加して、もし失敗したら、全額で返金いたします。

試験の目標が変わる限り、あるいは我々の勉強資料が変わる限り、すぐに更新して差し上げます。あなたのニーズをよく知っていていますから、あなたに試験に合格する自信を与えます。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
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: 4
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

QUESTION NO: 5
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

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Updated: May 27, 2022