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Google Professional-Data-Engineer Exam Overview:

Certification Vendor:	Google Cloud
Exam Name:	Google Cloud Certified Professional Data Engineer Exam
Exam Number:	Professional Data Engineer
Passing Score:	Not publicly disclosed (scaled scoring system)
Exam Format:	multiple choice, multiple select, case study
Certificate Validity Period:	2 years
Available Languages:	English, French, Portuguese, Japanese, German, Spanish
Exam Price:	$200 USD
Exam Duration:	120 minutes
Real Exam Qty:	Approximately 50–60 multiple choice and multiple select questions
Related Certifications:	Google Cloud Certified - Professional Data Analytics Engineer Google Cloud Certified - Associate Cloud Engineer Google Cloud Certified - Professional Cloud Architect Google Cloud Certified - Professional Machine Learning Engineer
Recommended Training:	Google Cloud Data Engineering Learning Path Google Cloud Professional Data Engineer Course (Coursera)
Exam Registration:	Google Cloud Certification Registration
Sample Questions:	Google Professional-Data-Engineer Sample Questions
Exam Way:	Online proctored exam or onsite test center (Kryterion Webassessor)
Pre Condition:	No formal prerequisites required; recommended experience with data processing and Google Cloud Platform services
Official Syllabus URL:	https://cloud.google.com/learn/certification/data-engineer

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Google Professional-Data-Engineer Exam is a certification exam offered by Google Cloud Platform. It is designed for data professionals who are looking to demonstrate their expertise in designing, building, and managing data processing systems on Google Cloud Platform. Professional-Data-Engineer exam tests the candidate's knowledge of data engineering, data processing, and data analysis techniques using Google Cloud Platform tools and services.

Professional Data Engineer Exam Details

Like other Google exams, this exam also consists of multiple choice and multiple select questions. Consider the fact that you need to pay $200 for the registration. After that, you will access the test for 2 hours which is presented either in English or Japanese. Moreover, you can either take the exam online or have to find a test center near your place to take this test.

There is no formal prerequisite for the exam but it is recommended to have 3-4 years of experience within the data engineering field and to be responsible for the tasks related to data engineering and machine learning. So, on the final test day, you need to have exhaustive knowledge about these domains to perform your best.

Operationalizing machine learning models
Providing solution quality
Building data processing systems
Designing data processing systems

Google Certified Professional Data Engineer Exam Sample Questions (Q97-Q102):

NEW QUESTION # 97
You are preparing an organization-wide dataset. You need to preprocess customer data stored in a restricted bucket in Cloud Storage. The data will be used to create consumer analyses. You need to comply with data privacy requirements. What should you do?

A. Use the Cloud Data Loss Prevention API and Dataflow to detect and remove sensitive fields from the data in Cloud Storage. Write the filtered data in BigQuery.
B. Use customer-managed encryption keys (CMEK) to directly encrypt the data in Cloud Storage.
Use federated queries from BigQuery. Share the encryption key by following the principle of least privilege.
C. Use Dataflow and Cloud KMS to encrypt sensitive fields and write the encrypted data in BigQuery. Share the encryption key by following the principle of least privilege.
D. Use Dataflow and the Cloud Data Loss Prevention API to mask sensitive data. Write the processed data in BigQuery.

Answer: D

NEW QUESTION # 98
You work for a large financial institution that is planning to use Dialogflow to create a chatbot for the company's mobile app You have reviewed old chat logs and lagged each conversation for intent based on each customer's stated intention for contacting customer service About 70% of customer requests are simple requests that are solved within 10 intents The remaining 30% of inquiries require much longer, more complicated requests Which intents should you automate first?

A. Automate the more complicated requests first because those require more of the agents' time
B. Automate the 10 intents that cover 70% of the requests so that live agents can handle more complicated requests
C. Automate a blend of the shortest and longest intents to be representative of all intents
D. Automate intents in places where common words such as "payment" appear only once so the software isn't confused

Answer: B

NEW QUESTION # 99
You operate a database that stores stock trades and an application that retrieves average stock price for a given company over an adjustable window of time. The data is stored in Cloud Bigtable where the datetime of the stock trade is the beginning of the row key. Your application has thousands of concurrent users, and you notice that performance is starting to degrade as more stocks are added. What should you do to improve the performance of your application?

A. Use Cloud Dataflow to write summary of each day's stock trades to an Avro file on Cloud Storage.
Update your application to read from Cloud Storage and Cloud Bigtable to compute the responses.
B. Change the data pipeline to use BigQuery for storing stock trades, and update your application.
C. Change the row key syntax in your Cloud Bigtable table to begin with a random number per second.
D. Change the row key syntax in your Cloud Bigtable table to begin with the stock symbol.

Answer: C

Explanation:
Timestamp at starting of rowkey causes bottleneck issues.

NEW QUESTION # 100
Which is not a valid reason for poor Cloud Bigtable performance?

A. There are issues with the network connection.
B. The Cloud Bigtable cluster has too many nodes.
C. The workload isn't appropriate for Cloud Bigtable.
D. The table's schema is not designed correctly.

Answer: B

Explanation:
The Cloud Bigtable cluster doesn't have enough nodes. If your Cloud Bigtable cluster is overloaded, adding more nodes can improve performance. Use the monitoring tools to check whether the cluster is overloaded.
Reference: https://cloud.google.com/bigtable/docs/performance

NEW QUESTION # 101
Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

A. Spark
B. Hive
C. Pig
D. YARN

Answer: A,B,C

Explanation:
Cloud Dataproc provides out-of-the box and end-to-end support for many of the most popular job types, including Spark, Spark SQL, PySpark, MapReduce, Hive, and Pig jobs.
Reference:
https://cloud.google.com/dataproc/docs/resources/faq#what_type_of_jobs_can_i_run

NEW QUESTION # 102
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