PASS GUARANTEED QUIZ EFFICIENT GOOGLE - PROFESSIONAL-DATA-ENGINEER VALID PRACTICE MATERIALS

Pass Guaranteed Quiz Efficient Google - Professional-Data-Engineer Valid Practice Materials

Pass Guaranteed Quiz Efficient Google - Professional-Data-Engineer Valid Practice Materials

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Tags: Professional-Data-Engineer Valid Practice Materials, Professional-Data-Engineer Demo Test, Professional-Data-Engineer Exam Voucher, Professional-Data-Engineer Actual Braindumps, Passing Professional-Data-Engineer Score

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You can use this format of Google Certified Professional Data Engineer Exam (Professional-Data-Engineer) actual questions on your smart devices. In addition to the Google Certified Professional Data Engineer Exam (Professional-Data-Engineer) PDF dumps, we also offer Google Certified Professional Data Engineer Exam (Professional-Data-Engineer) practice exam software. You will find the same ambiance and atmosphere when you attempt the real Google Professional-Data-Engineer exam.

Who should take the Google Professional Data Engineer exam

Individuals should pursue the exam if they want to demonstrate their expertise and ability to design and develop Data Engineering. Following professional get benefited from Google Professional Data Engineer Certification

  • Data engineers
  • Data architects
  • Developers responsible for managing big data transformation initiatives
  • Data analysts
  • Business analysts

To be eligible for the Google Professional-Data-Engineer exam, candidates must have experience in data engineering, data analytics, and data warehousing. They must also have experience in designing and implementing solutions using Google Cloud Platform's data processing technologies, such as Cloud Dataflow, BigQuery, and Cloud Dataproc. Furthermore, candidates must have excellent knowledge of SQL, Python, and Java programming languages, as well as experience in data modeling and data visualization.

To become a Google Certified Professional Data Engineer, candidates need to pass the Professional-Data-Engineer Exam. Professional-Data-Engineer exam consists of multiple-choice and multiple-select questions, and it is intended for professionals who have a minimum of three years of industry experience in data engineering. Professional-Data-Engineer exam duration is 2 hours, and the passing score is 70%. Professional-Data-Engineer exam fee is $200, and it can be taken at a testing center or remotely online.

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Google Certified Professional Data Engineer Exam Sample Questions (Q180-Q185):

NEW QUESTION # 180
Data Analysts in your company have the Cloud IAM Owner role assigned to them in their projects to allow them to work with multiple GCP products in their projects. Your organization requires that all BigQuery data access logs be retained for 6 months. You need to ensure that only audit personnel in your company can access the data access logs for all projects. What should you do?

  • A. Export the data access logs via a project-level export sink to a Cloud Storage bucket in a newly created projects for audit logs. Restrict access to the project with the exported logs.
  • B. Export the data access logs via a project-level export sink to a Cloud Storage bucket in the Data Analysts' projects. Restrict access to the Cloud Storage bucket.
  • C. Export the data access logs via an aggregated export sink to a Cloud Storage bucket in a newly created project for audit logs. Restrict access to the project that contains the exported logs.
  • D. Enable data access logs in each Data Analyst's project. Restrict access to Stackdriver Logging via Cloud IAM roles.

Answer: C

Explanation:
https://cloud.google.com/iam/docs/roles-audit-logging#scenario_external_auditors


NEW QUESTION # 181
You are creating a new pipeline in Google Cloud to stream IoT data from Cloud Pub/Sub through Cloud Dataflow to BigQuery. While previewing the data, you notice that roughly 2% of the data appears to be corrupt.
You need to modify the Cloud Dataflow pipeline to filter out this corrupt data. What should you do?

  • A. Add a SideInput that returns a Boolean if the element is corrupt.
  • B. Add a GroupByKey transform in Cloud Dataflow to group all of the valid data together and discard the rest.
  • C. Add a ParDo transform in Cloud Dataflow to discard corrupt elements.
  • D. Add a Partition transform in Cloud Dataflow to separate valid data from corrupt data.

Answer: C

Explanation:
Explanation


NEW QUESTION # 182
You are working on a linear regression model on BigQuery ML to predict a customer's likelihood of purchasing your company's products. Your model uses a city name variable as a key predictive component in order to train and serve the model your data must be organized in columns. You want to prepare your data using the least amount of coding while maintaining the predictable variables. What should you do?

  • A. Use TensorFlow to create a categorical variable with a vocabulary list. Create the vocabulary file and upload that as part of your model to BigQuery ML.
  • B. Use SQL in BigQuery to transform the stale column using a one-hot encoding method, and make each city a column with binary values.
  • C. Cloud Data Fusion to assign each city to a region that is labeled as 1, 2 3, 4, or 5, and then use that number to represent the city in the model.
  • D. Create a new view with BigQuery that does not include a column which city information.

Answer: C


NEW QUESTION # 183
Which of these operations can you perform from the BigQuery Web UI?

  • A. Load data with nested and repeated fields.
  • B. Upload a file in SQL format.
  • C. Upload a 20 MB file.
  • D. Upload multiple files using a wildcard.

Answer: A

Explanation:
You can load data with nested and repeated fields using the Web UI.
You cannot use the Web UI to:
- Upload a file greater than 10 MB in size
- Upload multiple files at the same time
- Upload a file in SQL format
All three of the above operations can be performed using the "bq" command.


NEW QUESTION # 184
You designed a database for patient records as a pilot project to cover a few hundred patients in three clinics. Your design used a single database table to represent all patients and their visits, and you used self-joins to generate reports. The server resource utilization was at 50%. Since then, the scope of the project has expanded. The database must now store 100 times more patient records. You can no longer run the reports, because they either take too long or they encounter errors with insufficient compute resources. How should you adjust the database design?

  • A. Shard the tables into smaller ones based on date ranges, and only generate reports with prespecified date ranges.
  • B. Partition the table into smaller tables, with one for each clinic. Run queries against the smaller table pairs, and use unions for consolidated reports.
  • C. Add capacity (memory and disk space) to the database server by the order of 200.
  • D. Normalize the master patient-record table into the patient table and the visits table, and create other necessary tables to avoid self-join.

Answer: D


NEW QUESTION # 185
......

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