Omgzlookの専門家チームがGoogleのProfessional-Data-Engineerミシュレーション問題認証試験に対して最新の短期有効なトレーニングプログラムを研究しました。GoogleのProfessional-Data-Engineerミシュレーション問題「Google Certified Professional Data Engineer Exam」認証試験に参加者に対して30時間ぐらいの短期の育成訓練でらくらくに勉強しているうちに多くの知識を身につけられます。 あなたは無料でProfessional-Data-Engineerミシュレーション問題復習教材をダウンロードしたいですか？もちろん、回答ははいです。だから、あなたはコンピューターでGoogleのウエブサイトを訪問してください。 試験の準備は時間とエネルギーがかかります。
Google Cloud Certified Professional-Data-Engineer ショートカットは一つしかないです。
Google Cloud Certified Professional-Data-Engineerミシュレーション問題 - Google Certified Professional Data Engineer Exam その夢は私にとってはるか遠いです。 心配する必要がないでしょう。Omgzlookは自分の資料に十分な自信を持っていますから、あなたもOmgzlookを信じたほうがいいです。
IT業種で仕事しているあなたは、夢を達成するためにどんな方法を利用するつもりですか。実際には、IT認定試験を受験して認証資格を取るのは一つの良い方法です。最近、GoogleのProfessional-Data-Engineerミシュレーション問題試験は非常に人気のある認定試験です。
Google Professional-Data-Engineerミシュレーション問題 - この重要な認証資格をもうすでに手に入れましたか。
OmgzlookのProfessional-Data-Engineerミシュレーション問題教材を購入したら、あなたは一年間の無料アップデートサービスを取得しました。試験問題集が更新されると、Omgzlookは直ちにあなたのメールボックスにProfessional-Data-Engineerミシュレーション問題問題集の最新版を送ります。あなたは試験の最新バージョンを提供することを要求することもできます。最新のProfessional-Data-Engineerミシュレーション問題試験問題を知りたい場合、試験に合格したとしてもOmgzlookは無料で問題集を更新してあげます。
Omgzlookの知名度が高くて、IT認定試験に関連するいろいろな優秀な問題集を持っています。それに、すべてのProfessional-Data-Engineerミシュレーション問題試験問題集に対する無料なdemoがあります。
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 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: 3
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: 4
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: 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
SAP C_THR82_2405 - ところで、受験生の皆さんを簡単にIT認定試験に合格させられる方法がないですか。 Juniper JN0-452 - 早速買いに行きましょう。 OmgzlookのGoogleのFortinet FCSS_ADA_AR-6.7試験トレーニング資料は豊富な経験を持っているIT専門家が研究したものです。 一回だけでGoogleのMicrosoft PL-400認定試験に合格したいか。 SAP C_THR94_2405 - これも弊社が自信的にあなたに商品を薦める原因です。
Updated: May 27, 2022