Omgzlookを利用するのは君の合格率を１００％保証いたします。Omgzlookは多種なIT認証試験を受ける方を正確な資料を提供者でございます。弊社の無料なサンプルを遠慮なくダウンロードしてください。 Professional-Data-Engineer模擬練習問題集を利用して試験に合格できます。この問題集の合格率は高いので、多くのお客様からProfessional-Data-Engineer模擬練習問題集への好評をもらいました。 Professional-Data-Engineer模擬練習認定試験の準備をするために、Omgzlook の専門家たちは彼らの豊富な知識と実践を生かして特別なトレーニング資料を研究しました。
Google Cloud Certified Professional-Data-Engineer 近年、IT領域で競争がますます激しくなります。
「OmgzlookのProfessional-Data-Engineer - Google Certified Professional Data Engineer Exam模擬練習問題集は本当に良い教材です。 OmgzlookのGoogleのProfessional-Data-Engineer 受験記対策試験トレーニング資料は豊富な知識と経験を持っているIT専門家に研究された成果で、正確度がとても高いです。Omgzlookに会ったら、最高のトレーニング資料を見つけました。
それはきっと君のGoogleのProfessional-Data-Engineer模擬練習試験に合格することの良い参考資料です。もし不合格になる場合は、ご心配なく、私たちは資料の費用を全部返金します。OmgzlookのGoogleのProfessional-Data-Engineer模擬練習試験トレーニング資料はPDF形式とソフトウェアの形式で提供します。
Google Professional-Data-Engineer模擬練習認定試験に合格することは難しいようですね。
IT業種が新しい業種で、経済発展を促進するチェーンですから、極めて重要な存在だということを良く知っています。Omgzlookの GoogleのProfessional-Data-Engineer模擬練習試験トレーニング資料は高度に認証されたIT領域の専門家の経験と創造を含めているものです。その権威性は言うまでもありません。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。
OmgzlookのGoogleのProfessional-Data-Engineer模擬練習問題集を購入したら、私たちは君のために、一年間無料で更新サービスを提供することができます。もし不合格になったら、私たちは全額返金することを保証します。
Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
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: 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
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
QUESTION NO: 4
You have a query that filters a BigQuery table using a WHERE clause on timestamp and ID columns. By using bq query - -dry_run you learn that the query triggers a full scan of the table, even though the filter on timestamp and ID select a tiny fraction of the overall data. You want to reduce the amount of data scanned by BigQuery with minimal changes to existing SQL queries. What should you do?
A. Recreate the table with a partitioning column and clustering column.
B. Create a separate table for each I
C. Use the LIMIT keyword to reduce the number of rows returned.
D. Use the bq query - -maximum_bytes_billed flag to restrict the number of bytes billed.
Answer: C
QUESTION NO: 5
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
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Updated: May 27, 2022