OmgzlookのGoogleのProfessional-Data-Engineer的中関連問題問題集を購入するなら、君がGoogleのProfessional-Data-Engineer的中関連問題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的中関連問題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。 あなたは自信満々にGoogleのProfessional-Data-Engineer的中関連問題試験に参加することができます。やってみて購入します。 弊社のGoogleのProfessional-Data-Engineer的中関連問題ソフトを購入するのを決めるとき、我々は各方面であなたに保障を提供します。
また、Professional-Data-Engineer的中関連問題問題集は的中率が高いです。
そして、Professional-Data-Engineer - Google Certified Professional Data Engineer Exam的中関連問題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。 Omgzlookを選られば、成功しましょう。わずか数年の中に、Google Professional-Data-Engineer ウェブトレーニング認定試験がたくさんの人の日常生活にとても大きい影響を与えています。
GoogleのProfessional-Data-Engineer的中関連問題の認定試験に合格すれば、就職機会が多くなります。この試験に合格すれば君の専門知識がとても強いを証明し得ます。GoogleのProfessional-Data-Engineer的中関連問題の認定試験は君の実力を考察するテストでございます。
Google Professional-Data-Engineer的中関連問題 - きっと君に失望させないと信じています。
今あなたが無料でOmgzlookが提供したGoogleのProfessional-Data-Engineer的中関連問題認定試験の学習ガイドをダウンロードできます。それは受験者にとって重要な情報です。
我々は受験生の皆様により高いスピードを持っているかつ効率的なサービスを提供することにずっと力を尽くしていますから、あなたが貴重な時間を節約することに助けを差し上げます。Omgzlook GoogleのProfessional-Data-Engineer的中関連問題試験問題集はあなたに問題と解答に含まれている大量なテストガイドを提供しています。
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
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: 2
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: 3
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: 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 are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
* The user profile: What the user likes and doesn't like to eat
* The user account information: Name, address, preferred meal times
* The order information: When orders are made, from where, to whom
The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?
A. BigQuery
B. Cloud Datastore
C. Cloud SQL
D. Cloud Bigtable
Answer: A
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Updated: May 27, 2022