[Jan 18, 2023] Professional-Data-Engineer Exam Brain Dumps – Study Notes and Theory [Q39-Q53]

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[Jan 18, 2023] Professional-Data-Engineer Exam Brain Dumps – Study Notes and Theory

Pass Google Professional-Data-Engineer Test Practice Test Questions Exam Dumps

This course will show you how to manage big data including loading, extracting, cleaning, and validating data. At the end of the training, you can easily create machine learning and statistical models as well as visualizing query results. This program is a bit lengthy but you have to practice well to get the knowledge needed on the actual exam. These are the following modules covered in the course:

  • Prebuilt ML Models APIs for Unsaturated Data
  • Cloud Dataflow Streaming Features
  • Custom Model building Using SQL in BigQuery ML
  • Custom Model building Utilizing Cloud AutoML
  • Handling Data Pipelines with Cloud Composer and Cloud Data Fusion
  • Big Data Analytics with Cloud Al Platform Notebook
  • Introduction to Building Batch Data Pipelines
  • Performing Spark on Cloud Dataproc
  • Production ML Pipelines and use of Kubeflow
  • Building a Data Warehouse
  • Bigtable Streaming Features and High-Throughput BigQuery
  • Serverless Messaging Using Cloud Sub/Pub
  • Introduction to Processing Streaming Data
  • Serverless Data Processing with Cloud Dataflow

These modules involve everything the candidate requires for passing the Professional Data Engineer certification exam. Thus, you will not miss anything if you are taking this learning program keenly and apply the required knowledge in an appropriate way. You would end up getting a good score and achieving the Google Professional Data Engineer certification.

 

Q39. You need to choose a database to store time series CPU and memory usage for millions of computers. You need to store this data in one-second interval samples. Analysts will be performing real-time, ad hoc analytics against the database. You want to avoid being charged for every query executed and ensure that the schema design will allow for future growth of the dataset. Which database and data model should you choose?

 
 
 
 

Q40. Your United States-based company has created an application for assessing and responding to user actions. The primary table’s data volume grows by 250,000 records per second. Many third parties use your application’s APIs to build the functionality into their own frontend applications. Your application’s APIs should comply with the following requirements:
* Single global endpoint
* ANSI SQL support
* Consistent access to the most up-to-date data
What should you do?

 
 
 
 

Q41. You are integrating one of your internal IT applications and Google BigQuery, so users can query BigQuery from the application’s interface. You do not want individual users to authenticate to BigQuery and you do not want to give them access to the dataset. You need to securely access BigQuery from your IT application.
What should you do?

 
 
 
 

Q42. An online retailer has built their current application on Google App Engine. A new initiative at the company mandates that they extend their application to allow their customers to transact directly via the application.
They need to manage their shopping transactions and analyze combined data from multiple datasets using a business intelligence (BI) tool. They want to use only a single database for this purpose. Which Google Cloud database should they choose?

 
 
 
 

Q43. When using Cloud Dataproc clusters, you can access the YARN web interface by configuring a browser to connect through a ____ proxy.

 
 
 
 

Q44. Your financial services company is moving to cloud technology and wants to store 50 TB of financial time-series data in the cloud. This data is updated frequently and new data will be streaming in all the time. Your company also wants to move their existing Apache Hadoop jobs to the cloud to get insights into this data. Which product should they use to store the data?

 
 
 
 

Q45. You need to store and analyze social media postings in Google BigQuery at a rate of 10,000 messages per minute in near real-time. Initially, design the application to use streaming inserts for individual postings. Your application also performs data aggregations right after the streaming inserts. You discover that the queries after streaming inserts do not exhibit strong consistency, and reports from the queries might miss in-flight dat
a. How can you adjust your application design?

 
 
 
 

Q46. You set up a streaming data insert into a Redis cluster via a Kafka cluster. Both clusters are running on Compute Engine instances. You need to encrypt data at rest with encryption keys that you can create, rotate, and destroy as needed. What should you do?

 
 
 
 

Q47. The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster ____.

 
 
 
 

Q48. You need to create a new transaction table in Cloud Spanner that stores product sales data. You are deciding what to use as a primary key. From a performance perspective, which strategy should you choose?

 
 
 
 

Q49. You are deploying a new storage system for your mobile application, which is a media streaming service. You decide the best fit is Google Cloud Datastore. You have entities with multiple properties, some of which can take on multiple values. For example, in the entity ‘Movie’ the property ‘actors’ and the property ‘tags’ have multiple values but the property ‘date released’ does not. A typical query would ask for all movies with actor=<actorname> ordered by date_released or all movies with tag=Comedy ordered by date_released. How should you avoid a combinatorial explosion in the number of indexes?

 
 
 
 

Q50. You use a dataset in BigQuery for analysis. You want to provide third-party companies with access to the same dataset. You need to keep the costs of data sharing low and ensure that the data is current. Which solution should you choose?

 
 
 
 

Q51. Which of the following is not possible using primitive roles?

 
 
 
 

Q52. You want to use a BigQuery table as a data sink. In which writing mode(s) can you use BigQuery as a sink?

 
 
 
 

Q53. Your globally distributed auction application allows users to bid on items. Occasionally, users place identical bids at nearly identical times, and different application servers process those bids. Each bid event contains the item, amount, user, and timestamp. You want to collate those bid events into a single location in real time to determine which user bid first. What should you do?

 
 
 
 

Certification Path

The Google Professional Data Engineer Certification is one of the highest level of certification mainly focussing to the professional Data Engineering.

There is no prerequisite for this exam but still it would be best to follow some sequence in order to prove immense knowledge as a Google professional Data Engineer.

You can complete Google Associate Certifications then approach for the professional certification. For more information related to Google cloud certification track Google-certification-path

 

Verified Professional-Data-Engineer dumps Q&As – Professional-Data-Engineer dumps with Correct Answers: https://www.vcedumps.com/Professional-Data-Engineer-examcollection.html


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