많은 시간과 돈이 필요 없습니다. 30분이란 특별학습가이드로 여러분은Google Professional-Data-Engineer참고자료인증시험을 한번에 통과할 수 있습니다, Goldmile-Infobiz에서Google Professional-Data-Engineer참고자료시험자료의 문제와 답이 실제시험의 문제와 답과 아주 비슷한 덤프만 제공합니다. 우리는 고객이 첫 번째 시도에서Google Professional-Data-Engineer참고자료 자격증시험을 합격할수있다는 것을 약속드립니다. Google Professional-Data-Engineer참고자료 시험을 합격하여 자격증을 손에 넣는다면 취직 혹은 연봉인상 혹은 승진이나 이직에 확실한 가산점이 될것입니다. Google 인증 Professional-Data-Engineer참고자료시험이 너무 어려워서 시험 볼 엄두도 나지 않는다구요? Goldmile-Infobiz 덤프만 공부하신다면 IT인증시험공부고민은 이젠 그만 하셔도 됩니다.
Google Cloud Certified Professional-Data-Engineer 하지만 난이도난 전혀 낮아지지 않고 이지도 어려운 시험입니다.
Google Professional-Data-Engineer - Google Certified Professional Data Engineer Exam참고자료덤프가 업데이트되면 업데이트된 최신버전을 무료로 제공해드립니다. 많은 애용 바랍니다. Google 인증 Professional-Data-Engineer 최신버전자료시험이 너무 어려워서 시험 볼 엄두도 나지 않는다구요? Goldmile-Infobiz 덤프만 공부하신다면 IT인증시험공부고민은 이젠 그만 하셔도 됩니다.
우리의Google Professional-Data-Engineer참고자료자료로 자신만만한 시험 준비하시기를 바랍니다. 우리를 선택함으로 자신의 시간을 아끼는 셈이라고 생각하시면 됩니다.Google Professional-Data-Engineer참고자료로 빠른시일내에 자격증 취득하시고GoogleIT업계중에 엘리트한 전문가되시기를 바랍니다. 우리Goldmile-Infobiz 에서 여러분은 아주 간단히Google Professional-Data-Engineer참고자료시험을 패스할 수 있습니다.
Google인증Google Professional-Data-Engineer참고자료시험은 국제적으로 승인해주는 IT인증시험의 한과목입니다.
성공을 위해 길을 찾고 실패를 위해 구실을 찾지 않는다는 말이 있습니다. Google인증 Professional-Data-Engineer참고자료시험이 영어로 출제되어 시험패스가 너무 어렵다 혹은 회사다니느라 공부할 시간이 없다는 등등은 모두 공부하기싫은 구실에 불과합니다. Goldmile-Infobiz의 Google인증 Professional-Data-Engineer참고자료덤프만 마련하면 실패를 성공으로 바꿀수 있는 기적을 체험할수 있습니다.
Goldmile-Infobiz의 Google인증 Professional-Data-Engineer참고자료덤프가 있으면 시험패스가 한결 간편해집니다. Goldmile-Infobiz의 Google인증 Professional-Data-Engineer참고자료시험덤프는 고객님의 IT자격증을 취득하는 꿈을 실현시켜 드리는 시험패스의 지름길입니다.
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
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: 5
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
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Updated: May 27, 2022