Professional-Data-Engineer試験関連情報 & Professional-Data-Engineer模擬対策 - Professional-Data-Engineer試験対応 - Omgzlook

今のインタネット時代に当たり、IT人材としてGoogleのProfessional-Data-Engineer試験関連情報資格証明書を取得できないと、大変なことではないなのか?ここで、我が社Omgzlookは一連のProfessional-Data-Engineer試験関連情報問題集を提供します。あなたはProfessional-Data-Engineer試験関連情報問題集を購入するかどうかと確認したい、OmgzlookのProfessional-Data-Engineer試験関連情報デーモ版を使用して購入するかと判断します。 人生にはあまりにも多くの変化および未知の誘惑がありますから、まだ若いときに自分自身のために強固な基盤を築くべきです。あなた準備しましたか。 受験生のあなたを助けて時間とお金を節約したり、Professional-Data-Engineer試験関連情報試験に速く合格すると保証します。

Google Cloud Certified Professional-Data-Engineer ローマは一日に建てられませんでした。

Google Cloud Certified Professional-Data-Engineer試験関連情報 - Google Certified Professional Data Engineer Exam なぜ受験生のほとんどはOmgzlookを選んだのですか。 だから、Professional-Data-Engineer 受験対策試験参考書に関連して、何か質問がありましたら、遠慮無く私たちとご連絡致します。私たちのサービスは24時間で、短い時間で回答できます。

OmgzlookのGoogleのProfessional-Data-Engineer試験関連情報問題集を購入するなら、君がGoogleのProfessional-Data-Engineer試験関連情報認定試験に合格する率は100パーセントです。あなたはOmgzlookの学習教材を購入した後、私たちは一年間で無料更新サービスを提供することができます。GoogleのProfessional-Data-Engineer試験関連情報認定試験に合格することはきっと君の職業生涯の輝い将来に大変役に立ちます。

Google Professional-Data-Engineer試験関連情報 - 常々、時間とお金ばかり効果がないです。

Professional-Data-Engineer試験関連情報「Google Certified Professional Data Engineer Exam」はGoogleの一つ認証試験として、もしGoogle認証試験に合格してIT業界にとても人気があってので、ますます多くの人がProfessional-Data-Engineer試験関連情報試験に申し込んで、Professional-Data-Engineer試験関連情報試験は簡単ではなくて、時間とエネルギーがかかって用意しなければなりません。

Omgzlookは多くの受験生を助けて彼らにGoogleのProfessional-Data-Engineer試験関連情報試験に合格させることができるのは我々専門的なチームがGoogleのProfessional-Data-Engineer試験関連情報試験を研究して解答を詳しく分析しますから。試験が更新されているうちに、我々はGoogleのProfessional-Data-Engineer試験関連情報試験の資料を更新し続けています。

Professional-Data-Engineer PDF DEMO:

QUESTION NO: 1
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: 2
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: 3
You need to create a near real-time inventory dashboard that reads the main inventory tables in your BigQuery data warehouse. Historical inventory data is stored as inventory balances by item and location. You have several thousand updates to inventory every hour. You want to maximize performance of the dashboard and ensure that the data is accurate. What should you do?
A. Use the BigQuery streaming the stream changes into a daily inventory movement table. Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
B. Use the BigQuery bulk loader to batch load inventory changes into a daily inventory movement table.
Calculate balances in a view that joins it to the historical inventory balance table. Update the inventory balance table nightly.
C. Leverage BigQuery UPDATE statements to update the inventory balances as they are changing.
D. Partition the inventory balance table by item to reduce the amount of data scanned with each inventory update.
Answer: C

QUESTION NO: 4
Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?
A. Use the Google Cloud Billing API to see what account the warehouse is being billed to.
B. Use Stackdriver Monitoring to see the usage of BigQuery query slots.
C. Get the identity and access management IIAM) policy of each table
D. Use Google Stackdriver Audit Logs to review data access.
Answer: B

QUESTION NO: 5
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

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Updated: May 27, 2022