これをよくできるために、我々は全日24時間のサービスを提供します。GoogleのProfessional-Data-Engineer受験資料更新版ソフトを購入してから一年間の無料更新サービスも提供します。試験に失敗したら、全額で返金する承諾があります。 OmgzlookのGoogleのProfessional-Data-Engineer受験資料更新版テストの問題と解答は本物の試験の挑戦で、あなたのいつもの考え方を変換しなければなりません。OmgzlookのGoogleのProfessional-Data-Engineer受験資料更新版「Google Certified Professional Data Engineer Exam」試験トレーニング資料はPDFぼ形式とソフトウェアの形式で提供して、OmgzlookのGoogleのProfessional-Data-Engineer受験資料更新版試験問題と解答に含まれています。 暇な時間だけでGoogleのProfessional-Data-Engineer受験資料更新版試験に合格したいのですか。
Professional-Data-Engineer受験資料更新版問題集を利用して試験に合格できます。
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Professional-Data-Engineer PDF DEMO:
QUESTION NO: 1
Your company is using WHILECARD tables to query data across multiple tables with similar names. The SQL statement is currently failing with the following error:
# Syntax error : Expected end of statement but got "-" at [4:11]
SELECT age
FROM
bigquery-public-data.noaa_gsod.gsod
WHERE
age != 99
AND_TABLE_SUFFIX = '1929'
ORDER BY
age DESC
Which table name will make the SQL statement work correctly?
A. 'bigquery-public-data.noaa_gsod.gsod*`
B. 'bigquery-public-data.noaa_gsod.gsod'*
C. 'bigquery-public-data.noaa_gsod.gsod'
D. bigquery-public-data.noaa_gsod.gsod*
Answer: A
QUESTION NO: 2
You are developing an application on Google Cloud that will automatically generate subject labels for users' blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning.
What should you do?
A. Build and train a text classification model using TensorFlow. Deploy the model using Cloud
Machine Learning Engine. Call the model from your application and process the results as labels.
B. Call the Cloud Natural Language API from your application. Process the generated Entity Analysis as labels.
C. Build and train a text classification model using TensorFlow. Deploy the model using a Kubernetes
Engine cluster. Call the model from your application and process the results as labels.
D. Call the Cloud Natural Language API from your application. Process the generated Sentiment
Analysis as labels.
Answer: D
QUESTION NO: 3
MJTelco is building a custom interface to share data. They have these requirements:
* They need to do aggregations over their petabyte-scale datasets.
* They need to scan specific time range rows with a very fast response time (milliseconds).
Which combination of Google Cloud Platform products should you recommend?
A. Cloud Datastore and Cloud Bigtable
B. Cloud Bigtable and Cloud SQL
C. BigQuery and Cloud Bigtable
D. BigQuery and Cloud Storage
Answer: C
QUESTION NO: 4
You have Cloud Functions written in Node.js that pull messages from Cloud Pub/Sub and send the data to BigQuery. You observe that the message processing rate on the Pub/Sub topic is orders of magnitude higher than anticipated, but there is no error logged in Stackdriver Log Viewer. What are the two most likely causes of this problem? Choose 2 answers.
A. Publisher throughput quota is too small.
B. The subscriber code cannot keep up with the messages.
C. The subscriber code does not acknowledge the messages that it pulls.
D. Error handling in the subscriber code is not handling run-time errors properly.
E. Total outstanding messages exceed the 10-MB maximum.
Answer: B,D
QUESTION NO: 5
You work for an economic consulting firm that helps companies identify economic trends as they happen. As part of your analysis, you use Google BigQuery to correlate customer data with the average prices of the 100 most common goods sold, including bread, gasoline, milk, and others. The average prices of these goods are updated every 30 minutes. You want to make sure this data stays up to date so you can combine it with other data in BigQuery as cheaply as possible. What should you do?
A. Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery
B. Store the data in a file in a regional Google Cloud Storage bucket. Use Cloud Dataflow to query
BigQuery and combine the data programmatically with the data stored in Google Cloud Storage.
C. Store the data in Google Cloud Datastore. Use Google Cloud Dataflow to query BigQuery and combine the data programmatically with the data stored in Cloud Datastore
D. Load the data every 30 minutes into a new partitioned table in BigQuery.
Answer: D
Splunk SPLK-1002 - 数年間の発展で我々Omgzlookはもっと多くの資源と経験を得ています。 Microsoft AI-900-CN - これは試験の準備をするために非常に効率的なツールですから。 IBM C1000-172 - 早めによりよい仕事を探しできて、長閑な万元以上の月給がある生活を楽しみます。 いまCisco 300-730J試験に合格するショートカットを教えてあげますから。 どのようにすばらしい人になれますか？ここで、あなたに我々のGoogle IBM C1000-173試験問題集をお勧めください。
Updated: May 27, 2022