NEW PROFESSIONAL-DATA-ENGINEER STUDY PLAN - PROFESSIONAL-DATA-ENGINEER TEST VCE FREE

New Professional-Data-Engineer Study Plan - Professional-Data-Engineer Test Vce Free

New Professional-Data-Engineer Study Plan - Professional-Data-Engineer Test Vce Free

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Preparing for the exam requires a combination of hands-on experience with Google Cloud Platform, as well as studying relevant documentation and training materials. Google offers a variety of resources for exam preparation, including online courses, hands-on labs, and practice exams.

Earning the Google Professional-Data-Engineer Certification demonstrates that an individual has the skills and knowledge required to design and maintain robust data processing systems using Google Cloud Platform services. Google Certified Professional Data Engineer Exam certification is recognized globally and is highly valued by organizations that use Google Cloud Platform for their data processing needs. With the increasing demand for data engineering professionals in the industry, earning this certification can help individuals stand out and advance their careers in this field.

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Google Certified Professional Data Engineer Exam Sample Questions (Q269-Q274):

NEW QUESTION # 269
You need ads data to serve Al models and historical data tor analytics longtail and outlier data points need to be identified You want to cleanse the data n near-reel time before running it through Al models What should you do?

  • A. Use Cloud Composer to identify longtail and outlier data points, and then output a usable dataset to BigQuery
  • B. Use Dataflow to identity longtail and outber data points programmatically with BigQuery as a sink
  • C. Use Cloud Storage as a data warehouse shell scripts tor processing, and BigQuery to create views tor desired datasets
  • D. Use BigQuery to ingest prepare and then analyze the data and then run queries to create views

Answer: D


NEW QUESTION # 270
You need to compose visualization for operations teams with the following requirements:
Telemetry must include data from all 50,000 installations for the most recent 6 weeks (sampling once every minute) The report must not be more than 3 hours delayed from live data.
The actionable report should only show suboptimal links.
Most suboptimal links should be sorted to the top.
Suboptimal links can be grouped and filtered by regional geography.
User response time to load the report must be <5 seconds.
You create a data source to store the last 6 weeks of data, and create visualizations that allow viewers to see multiple date ranges, distinct geographic regions, and unique installation types. You always show the latest data without any changes to your visualizations. You want to avoid creating and updating new visualizations each month. What should you do?

  • A. Load the data into relational database tables, write a Google App Engine application that queries all rows, summarizes the data across each criteria, and then renders results using the Google Charts and visualization API.
  • B. Export the data to a spreadsheet, compose a series of charts and tables, one for each possible combination of criteria, and spread them across multiple tabs.
  • C. Look through the current data and compose a series of charts and tables, one for each possible combination of criteria.
  • D. Look through the current data and compose a small set of generalized charts and tables bound to criteria filters that allow value selection.

Answer: D


NEW QUESTION # 271
Your company's on-premises Apache Hadoop servers are approaching end-of-life, and IT has decided to migrate the cluster to Google Cloud Dataproc. A like-for-like migration of the cluster would require 50 TB of Google Persistent Disk per node. The CIO is concerned about the cost of using that much block storage. You want to minimize the storage cost of the migration. What should you do?

  • A. Tune the Cloud Dataproc cluster so that there is just enough disk for all data.
  • B. Use preemptible virtual machines (VMs) for the Cloud Dataproc cluster.
  • C. Migrate some of the cold data into Google Cloud Storage, and keep only the hot data in Persistent Disk.
  • D. Put the data into Google Cloud Storage.

Answer: B

Explanation:
References:


NEW QUESTION # 272
If you're running a performance test that depends upon Cloud Bigtable, all the choices except one below are recommended steps. Which is NOT a recommended step to follow?

  • A. Use at least 300 GB of data.
  • B. Do not use a production instance.
  • C. Run your test for at least 10 minutes.
  • D. Before you test, run a heavy pre-test for several minutes.

Answer: B

Explanation:
If you're running a performance test that depends upon Cloud Bigtable, be sure to follow these steps as you plan and execute your test:
Use a production instance. A development instance will not give you an accurate sense of how a production instance performs under load.
Use at least 300 GB of data. Cloud Bigtable performs best with 1 TB or more of data. However, 300 GB of data is enough to provide reasonable results in a performance test on a 3-node cluster. On larger clusters, use
100 GB of data per node.
Before you test, run a heavy pre-test for several minutes. This step gives Cloud Bigtable a chance to balance data across your nodes based on the access patterns it observes.
Run your test for at least 10 minutes. This step lets Cloud Bigtable further optimize your data, and it helps ensure that you will test reads from disk as well as cached reads from memory.
Reference: https://cloud.google.com/bigtable/docs/performance


NEW QUESTION # 273
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 # 274
......

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