現在IT技術会社に通勤しているあなたは、GoogleのProfessional-Data-Engineer試験関連赤本試験認定を取得しましたか？Professional-Data-Engineer試験関連赤本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試験関連赤本試験に一発合格したいなら、我々社のGoogleのProfessional-Data-Engineer試験関連赤本資料を参考しましょう。また、Professional-Data-Engineer試験関連赤本問題集に疑問があると、メールで問い合わせてください。 Omgzlookは先輩の経験を生かして暦年の試験の材料を編集することを通して、最高のProfessional-Data-Engineer試験関連赤本問題集を作成しました。問題集に含まれているものは実際試験の問題を全部カバーすることができますから、あなたが一回で成功することを保証できます。 人によって目標が違いますが、あなたにGoogle Professional-Data-Engineer試験関連赤本試験に順調に合格できるのは我々の共同の目標です。
Google Cloud Certified Professional-Data-Engineer 暇の時間を利用して勉強します。
Google Cloud Certified Professional-Data-Engineer試験関連赤本 - Google Certified Professional Data Engineer Exam Omgzlookを利用したら分かります。 そして、Professional-Data-Engineer 日本語認定試験参考書の問題は本当の試験問題とだいたい同じことであるとわかります。Professional-Data-Engineer 日本語認定試験参考書があれば,ほかの試験参考書を勉強する必要がないです。
この試験に受かるのは難しいですが、大丈夫です。私はOmgzlookのGoogleのProfessional-Data-Engineer試験関連赤本試験トレーニング資料を選びましたから。私が自分の夢を実現することを助けられますから。
Google Professional-Data-Engineer試験関連赤本 - 迷ってないください。
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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