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Professional-Data-Engineer Sample Questions Answers

Questions 4

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?

Options:

A.

Load the data every 30 minutes into a new partitioned table in BigQuery.

B.

Store and update the data in a regional Google Cloud Storage bucket and create a federated data source in BigQuery

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.

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.

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Questions 5

You want to use a database of information about tissue samples to classify future tissue samples as either normal or mutated. You are evaluating an unsupervised anomaly detection method for classifying the tissue samples. Which two characteristic support this method? (Choose two.)

Options:

A.

There are very few occurrences of mutations relative to normal samples.

B.

There are roughly equal occurrences of both normal and mutated samples in the database.

C.

You expect future mutations to have different features from the mutated samples in the database.

D.

You expect future mutations to have similar features to the mutated samples in the database.

E.

You already have labels for which samples are mutated and which are normal in the database.

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Questions 6

You want to automate execution of a multi-step data pipeline running on Google Cloud. The pipeline includes Cloud Dataproc and Cloud Dataflow jobs that have multiple dependencies on each other. You want to use managed services where possible, and the pipeline will run every day. Which tool should you use?

Options:

A.

cron

B.

Cloud Composer

C.

Cloud Scheduler

D.

Workflow Templates on Cloud Dataproc

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Questions 7

You are building new real-time data warehouse for your company and will use Google BigQuery streaming inserts. There is no guarantee that data will only be sent in once but you do have a unique ID for each row of data and an event timestamp. You want to ensure that duplicates are not included while interactively querying data. Which query type should you use?

Options:

A.

Include ORDER BY DESK on timestamp column and LIMIT to 1.

B.

Use GROUP BY on the unique ID column and timestamp column and SUM on the values.

C.

Use the LAG window function with PARTITION by unique ID along with WHERE LAG IS NOT NULL.

D.

Use the ROW_NUMBER window function with PARTITION by unique ID along with WHERE row equals 1.

Questions 8

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?

Options:

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*`

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Questions 9

Your company is in a highly regulated industry. One of your requirements is to ensure individual users have access only to the minimum amount of information required to do their jobs. You want to enforce this requirement with Google BigQuery. Which three approaches can you take? (Choose three.)

Options:

A.

Disable writes to certain tables.

B.

Restrict access to tables by role.

C.

Ensure that the data is encrypted at all times.

D.

Restrict BigQuery API access to approved users.

E.

Segregate data across multiple tables or databases.

F.

Use Google Stackdriver Audit Logging to determine policy violations.

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Questions 10

You are working on a sensitive project involving private user data. You have set up a project on Google Cloud Platform to house your work internally. An external consultant is going to assist with coding a complex transformation in a Google Cloud Dataflow pipeline for your project. How should you maintain users’ privacy?

Options:

A.

Grant the consultant the Viewer role on the project.

B.

Grant the consultant the Cloud Dataflow Developer role on the project.

C.

Create a service account and allow the consultant to log on with it.

D.

Create an anonymized sample of the data for the consultant to work with in a different project.

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Questions 11

You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?

Options:

A.

Deploy a Cloud Dataproc cluster. Use a standard persistent disk and 50% preemptible workers. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://

B.

Deploy a Cloud Dataproc cluster. Use an SSD persistent disk and 50% preemptible workers. Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://

C.

Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instances. Install the Cloud Storage connector, and store the data in Cloud Storage. Change references in scripts from hdfs:// to gs://

D.

Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances. Store data in HDFS. Change references in scripts from hdfs:// to gs://

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Questions 12

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?

Options:

A.

Add capacity (memory and disk space) to the database server by the order of 200.

B.

Shard the tables into smaller ones based on date ranges, and only generate reports with prespecified date ranges.

C.

Normalize the master patient-record table into the patient table and the visits table, and create other necessary tables to avoid self-join.

D.

Partition the table into smaller tables, with one for each clinic. Run queries against the smaller table pairs, and use unions for consolidated reports.

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Questions 13

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 data. How can you adjust your application design?

Options:

A.

Re-write the application to load accumulated data every 2 minutes.

B.

Convert the streaming insert code to batch load for individual messages.

C.

Load the original message to Google Cloud SQL, and export the table every hour to BigQuery via streaming inserts.

D.

Estimate the average latency for data availability after streaming inserts, and always run queries after waiting twice as long.

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Questions 14

You are designing a basket abandonment system for an ecommerce company. The system will send a message to a user based on these rules:

  • No interaction by the user on the site for 1 hour
  • Has added more than $30 worth of products to the basket
  • Has not completed a transaction

You use Google Cloud Dataflow to process the data and decide if a message should be sent. How should you design the pipeline?

Options:

A.

Use a fixed-time window with a duration of 60 minutes.

B.

Use a sliding time window with a duration of 60 minutes.

C.

Use a session window with a gap time duration of 60 minutes.

D.

Use a global window with a time based trigger with a delay of 60 minutes.

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Questions 15

You are designing a pipeline that publishes application events to a Pub/Sub topic. You need to aggregate events across hourly intervals before loading the results to BigQuery for analysis. Your solution must be scalable so it can process and load large volumes of events to BigQuery. What should you do?

Options:

A.

Create a streaming Dataflow job to continually read from the Pub/Sub topic and perform the necessary aggregations using tumbling windows

B.

Schedule a batch Dataflow job to run hourly, pulling all available messages from the Pub-Sub topic and performing the necessary aggregations

C.

Schedule a Cloud Function to run hourly, pulling all avertable messages from the Pub/Sub topic and performing the necessary aggregations

D.

Create a Cloud Function to perform the necessary data processing that executes using the Pub/Sub trigger every time a new message is published to the topic.

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Questions 16

Your company built a TensorFlow neural-network model with a large number of neurons and layers. The model fits well for the training data. However, when tested against new data, it performs poorly. What method can you employ to address this?

Options:

A.

Threading

B.

Serialization

C.

Dropout Methods

D.

Dimensionality Reduction

Questions 17

Your company has recently grown rapidly and now ingesting data at a significantly higher rate than it was previously. You manage the daily batch MapReduce analytics jobs in Apache Hadoop. However, the recent increase in data has meant the batch jobs are falling behind. You were asked to recommend ways the development team could increase the responsiveness of the analytics without increasing costs. What should you recommend they do?

Options:

A.

Rewrite the job in Pig.

B.

Rewrite the job in Apache Spark.

C.

Increase the size of the Hadoop cluster.

D.

Decrease the size of the Hadoop cluster but also rewrite the job in Hive.

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Questions 18

You create an important report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. You notice that visualizations are not showing data that is less than 1 hour old. What should you do?

Options:

A.

Disable caching by editing the report settings.

B.

Disable caching in BigQuery by editing table details.

C.

Refresh your browser tab showing the visualizations.

D.

Clear your browser history for the past hour then reload the tab showing the virtualizations.

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Questions 19

Your company handles data processing for a number of different clients. Each client prefers to use their own suite of analytics tools, with some allowing direct query access via Google BigQuery. You need to secure the data so that clients cannot see each other’s data. You want to ensure appropriate access to the data. Which three steps should you take? (Choose three.)

Options:

A.

Load data into different partitions.

B.

Load data into a different dataset for each client.

C.

Put each client’s BigQuery dataset into a different table.

D.

Restrict a client’s dataset to approved users.

E.

Only allow a service account to access the datasets.

F.

Use the appropriate identity and access management (IAM) roles for each client’s users.

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Questions 20

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= 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?

Options:

A.

Option A

B.

Option B.

C.

Option C

D.

Option D

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Questions 21

You want to process payment transactions in a point-of-sale application that will run on Google Cloud Platform. Your user base could grow exponentially, but you do not want to manage infrastructure scaling.

Which Google database service should you use?

Options:

A.

Cloud SQL

B.

BigQuery

C.

Cloud Bigtable

D.

Cloud Datastore

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Questions 22

Given the record streams MJTelco is interested in ingesting per day, they are concerned about the cost of Google BigQuery increasing. MJTelco asks you to provide a design solution. They require a single large data table called tracking_table. Additionally, they want to minimize the cost of daily queries while performing fine-grained analysis of each day’s events. They also want to use streaming ingestion. What should you do?

Options:

A.

Create a table called tracking_table and include a DATE column.

B.

Create a partitioned table called tracking_table and include a TIMESTAMP column.

C.

Create sharded tables for each day following the pattern tracking_table_YYYYMMDD.

D.

Create a table called tracking_table with a TIMESTAMP column to represent the day.

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Questions 23

You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:

  • The user profile: What the user likes and doesn’t like to eat
  • The user account information: Name, address, preferred meal times
  • The order information: When orders are made, from where, to whom

The database will be used to store all the transactional data of the product. You want to optimize the data schema. Which Google Cloud Platform product should you use?

Options:

A.

BigQuery

B.

Cloud SQL

C.

Cloud Bigtable

D.

Cloud Datastore

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Questions 24

You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of-Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required.

You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)

Options:

A.

Redis

B.

HBase

C.

MySQL

D.

MongoDB

E.

Cassandra

F.

HDFS with Hive

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Questions 25

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?

Options:

A.

Put the data into Google Cloud Storage.

B.

Use preemptible virtual machines (VMs) for the Cloud Dataproc cluster.

C.

Tune the Cloud Dataproc cluster so that there is just enough disk for all data.

D.

Migrate some of the cold data into Google Cloud Storage, and keep only the hot data in Persistent Disk.

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Questions 26

Your company’s customer and order databases are often under heavy load. This makes performing analytics against them difficult without harming operations. The databases are in a MySQL cluster, with nightly backups taken using mysqldump. You want to perform analytics with minimal impact on operations. What should you do?

Options:

A.

Add a node to the MySQL cluster and build an OLAP cube there.

B.

Use an ETL tool to load the data from MySQL into Google BigQuery.

C.

Connect an on-premises Apache Hadoop cluster to MySQL and perform ETL.

D.

Mount the backups to Google Cloud SQL, and then process the data using Google Cloud Dataproc.

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Questions 27

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?

Options:

A.

Cloud Datastore and Cloud Bigtable

B.

Cloud Bigtable and Cloud SQL

C.

BigQuery and Cloud Bigtable

D.

BigQuery and Cloud Storage

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Questions 28

Your company is loading comma-separated values (CSV) files into Google BigQuery. The data is fully imported successfully; however, the imported data is not matching byte-to-byte to the source file. What is the most likely cause of this problem?

Options:

A.

The CSV data loaded in BigQuery is not flagged as CSV.

B.

The CSV data has invalid rows that were skipped on import.

C.

The CSV data loaded in BigQuery is not using BigQuery’s default encoding.

D.

The CSV data has not gone through an ETL phase before loading into BigQuery.

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Questions 29

Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.

You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)

Options:

A.

Introduce data compression for each file to increase the rate file of file transfer.

B.

Contact your internet service provider (ISP) to increase your maximum bandwidth to at least 100 Mbps.

C.

Redesign the data ingestion process to use gsutil tool to send the CSV files to a storage bucket in parallel.

D.

Assemble 1,000 files into a tape archive (TAR) file. Transmit the TAR files instead, and disassemble the CSV files in the cloud upon receiving them.

E.

Create an S3-compatible storage endpoint in your network, and use Google Cloud Storage Transfer Service to transfer on-premices data to the designated storage bucket.

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Questions 30

Your software uses a simple JSON format for all messages. These messages are published to Google Cloud Pub/Sub, then processed with Google Cloud Dataflow to create a real-time dashboard for the CFO. During testing, you notice that some messages are missing in the dashboard. You check the logs, and all messages are being published to Cloud Pub/Sub successfully. What should you do next?

Options:

A.

Check the dashboard application to see if it is not displaying correctly.

B.

Run a fixed dataset through the Cloud Dataflow pipeline and analyze the output.

C.

Use Google Stackdriver Monitoring on Cloud Pub/Sub to find the missing messages.

D.

Switch Cloud Dataflow to pull messages from Cloud Pub/Sub instead of Cloud Pub/Sub pushing messages to Cloud Dataflow.

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Questions 31

Your company has hired a new data scientist who wants to perform complicated analyses across very large datasets stored in Google Cloud Storage and in a Cassandra cluster on Google Compute Engine. The scientist primarily wants to create labelled data sets for machine learning projects, along with some visualization tasks. She reports that her laptop is not powerful enough to perform her tasks and it is slowing her down. You want to help her perform her tasks. What should you do?

Options:

A.

Run a local version of Jupiter on the laptop.

B.

Grant the user access to Google Cloud Shell.

C.

Host a visualization tool on a VM on Google Compute Engine.

D.

Deploy Google Cloud Datalab to a virtual machine (VM) on Google Compute Engine.

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Questions 32

You are creating a model to predict housing prices. Due to budget constraints, you must run it on a single resource-constrained virtual machine. Which learning algorithm should you use?

Options:

A.

Linear regression

B.

Logistic classification

C.

Recurrent neural network

D.

Feedforward neural network

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Questions 33

Which of these rules apply when you add preemptible workers to a Dataproc cluster (select 2 answers)?

Options:

A.

Preemptible workers cannot use persistent disk.

B.

Preemptible workers cannot store data.

C.

If a preemptible worker is reclaimed, then a replacement worker must be added manually.

D.

A Dataproc cluster cannot have only preemptible workers.

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Questions 34

Which of these are examples of a value in a sparse vector? (Select 2 answers.)

Options:

A.

[0, 5, 0, 0, 0, 0]

B.

[0, 0, 0, 1, 0, 0, 1]

C.

[0, 1]

D.

[1, 0, 0, 0, 0, 0, 0]

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Questions 35

Which of the following is not true about Dataflow pipelines?

Options:

A.

Pipelines are a set of operations

B.

Pipelines represent a data processing job

C.

Pipelines represent a directed graph of steps

D.

Pipelines can share data between instances

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Questions 36

Which row keys are likely to cause a disproportionate number of reads and/or writes on a particular node in a Bigtable cluster (select 2 answers)?

Options:

A.

A sequential numeric ID

B.

A timestamp followed by a stock symbol

C.

A non-sequential numeric ID

D.

A stock symbol followed by a timestamp

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Questions 37

If you want to create a machine learning model that predicts the price of a particular stock based on its recent price history, what type of estimator should you use?

Options:

A.

Unsupervised learning

B.

Regressor

C.

Classifier

D.

Clustering estimator

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Questions 38

For the best possible performance, what is the recommended zone for your Compute Engine instance and Cloud Bigtable instance?

Options:

A.

Have the Compute Engine instance in the furthest zone from the Cloud Bigtable instance.

B.

Have both the Compute Engine instance and the Cloud Bigtable instance to be in different zones.

C.

Have both the Compute Engine instance and the Cloud Bigtable instance to be in the same zone.

D.

Have the Cloud Bigtable instance to be in the same zone as all of the consumers of your data.

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Questions 39

MJTelco’s Google Cloud Dataflow pipeline is now ready to start receiving data from the 50,000 installations. You want to allow Cloud Dataflow to scale its compute power up as required. Which Cloud Dataflow pipeline configuration setting should you update?

Options:

A.

The zone

B.

The number of workers

C.

The disk size per worker

D.

The maximum number of workers

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Questions 40

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?

Options:

A.

Look through the current data and compose a series of charts and tables, one for each possible

combination of criteria.

B.

Look through the current data and compose a small set of generalized charts and tables bound to criteria filters that allow value selection.

C.

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.

D.

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.

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Questions 41

MJTelco needs you to create a schema in Google Bigtable that will allow for the historical analysis of the last 2 years of records. Each record that comes in is sent every 15 minutes, and contains a unique identifier of the device and a data record. The most common query is for all the data for a given device for a given day. Which schema should you use?

Options:

A.

Rowkey: date#device_idColumn data: data_point

B.

Rowkey: dateColumn data: device_id, data_point

C.

Rowkey: device_idColumn data: date, data_point

D.

Rowkey: data_pointColumn data: device_id, date

E.

Rowkey: date#data_pointColumn data: device_id

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Questions 42

You need to compose visualizations for operations teams with the following requirements:

Which approach meets the requirements?

Options:

A.

Load the data into Google Sheets, use formulas to calculate a metric, and use filters/sorting to show only suboptimal links in a table.

B.

Load the data into Google BigQuery tables, write Google Apps Script that queries the data, calculates the metric, and shows only suboptimal rows in a table in Google Sheets.

C.

Load the data into Google Cloud Datastore tables, write a Google App Engine Application that queries all rows, applies a function to derive the metric, and then renders results in a table using the Google charts and visualization API.

D.

Load the data into Google BigQuery tables, write a Google Data Studio 360 report that connects to your data, calculates a metric, and then uses a filter expression to show only suboptimal rows in a table.

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Questions 43

You create a new report for your large team in Google Data Studio 360. The report uses Google BigQuery as its data source. It is company policy to ensure employees can view only the data associated with their region, so you create and populate a table for each region. You need to enforce the regional access policy to the data.

Which two actions should you take? (Choose two.)

Options:

A.

Ensure all the tables are included in global dataset.

B.

Ensure each table is included in a dataset for a region.

C.

Adjust the settings for each table to allow a related region-based security group view access.

D.

Adjust the settings for each view to allow a related region-based security group view access.

E.

Adjust the settings for each dataset to allow a related region-based security group view access.

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Questions 44

Flowlogistic wants to use Google BigQuery as their primary analysis system, but they still have Apache Hadoop and Spark workloads that they cannot move to BigQuery. Flowlogistic does not know how to store the data that is common to both workloads. What should they do?

Options:

A.

Store the common data in BigQuery as partitioned tables.

B.

Store the common data in BigQuery and expose authorized views.

C.

Store the common data encoded as Avro in Google Cloud Storage.

D.

Store he common data in the HDFS storage for a Google Cloud Dataproc cluster.

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Questions 45

Flowlogistic’s management has determined that the current Apache Kafka servers cannot handle the data volume for their real-time inventory tracking system. You need to build a new system on Google Cloud Platform (GCP) that will feed the proprietary tracking software. The system must be able to ingest data from a variety of global sources, process and query in real-time, and store the data reliably. Which combination of GCP products should you choose?

Options:

A.

Cloud Pub/Sub, Cloud Dataflow, and Cloud Storage

B.

Cloud Pub/Sub, Cloud Dataflow, and Local SSD

C.

Cloud Pub/Sub, Cloud SQL, and Cloud Storage

D.

Cloud Load Balancing, Cloud Dataflow, and Cloud Storage

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Questions 46

Flowlogistic’s CEO wants to gain rapid insight into their customer base so his sales team can be better informed in the field. This team is not very technical, so they’ve purchased a visualization tool to simplify the creation of BigQuery reports. However, they’ve been overwhelmed by all the data in the table, and are spending a lot of money on queries trying to find the data they need. You want to solve their problem in the most cost-effective way. What should you do?

Options:

A.

Export the data into a Google Sheet for virtualization.

B.

Create an additional table with only the necessary columns.

C.

Create a view on the table to present to the virtualization tool.

D.

Create identity and access management (IAM) roles on the appropriate columns, so only they appear in a query.

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Questions 47

Flowlogistic is rolling out their real-time inventory tracking system. The tracking devices will all send package-tracking messages, which will now go to a single Google Cloud Pub/Sub topic instead of the Apache Kafka cluster. A subscriber application will then process the messages for real-time reporting and store them in Google BigQuery for historical analysis. You want to ensure the package data can be analyzed over time.

Which approach should you take?

Options:

A.

Attach the timestamp on each message in the Cloud Pub/Sub subscriber application as they are received.

B.

Attach the timestamp and Package ID on the outbound message from each publisher device as they are sent to Clod Pub/Sub.

C.

Use the NOW () function in BigQuery to record the event’s time.

D.

Use the automatically generated timestamp from Cloud Pub/Sub to order the data.

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Questions 48

You are on the data governance team and are implementing security requirements to deploy resources. You need to ensure that resources are limited to only the europe-west 3 region You want to follow Google-recommended practices What should you do?

Options:

A.

Deploy resources with Terraform and implement a variable validation rule to ensure that the region is set to the europe-west3 region for all resources.

B.

Set the constraints/gcp. resourceLocations organization policy constraint to in:eu-locations.

C.

Create a Cloud Function to monitor all resources created and automatically destroy the ones created outside the europe-west3 region.

D.

Set the constraints/gcp. resourceLocations organization policy constraint to in: europe-west3-locations.

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Questions 49

You've migrated a Hadoop job from an on-premises cluster to Dataproc and Good Storage. Your Spark job is a complex analytical workload fiat consists of many shuffling operations, and initial data are parquet toes (on average 200-400 MB size each) You see some degradation in performance after the migration to Dataproc so you'd like to optimize for it. Your organization is very cost-sensitive so you'd Idee to continue using Dataproc on preemptibles (with 2 non-preemptibles workers only) for this workload. What should you do?

Options:

A.

Switch from HODs to SSDs override the preemptible VMs configuration to increase the boot disk size

B.

Increase the see of your parquet files to ensure them to be 1 GB minimum

C.

Switch to TFRecords format (appr 200 MB per We) instead of parquet files

D.

Switch from HDDs to SSDs. copy initial data from Cloud Storage to Hadoop Distributed File System (HDFS) run the Spark job and copy results back to Cloud Storage

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Questions 50

You are a retailer that wants to integrate your online sales capabilities with different in-home assistants, such as Google Home. You need to interpret customer voice commands and issue an order to the backend systems. Which solutions should you choose?

Options:

A.

Cloud Speech-to-Text API

B.

Cloud Natural Language API

C.

Dialogflow Enterprise Edition

D.

Cloud AutoML Natural Language

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Questions 51

You have created an external table for Apache Hive partitioned data that resides in a Cloud Storage bucket, which contains a large number of files. You notice that queries against this table are slow You want to improve the performance of these queries What should you do?

Options:

A.

Migrate the Hive partitioned data objects to a multi-region Cloud Storage bucket.

B.

Create an individual external table for each Hive partition by using a common table name prefix Use wildcard table queries to reference the partitioned data.

C.

Change the storage class of the Hive partitioned data objects from Coldline to Standard.

D.

Upgrade the external table to a BigLake table Enable metadata caching for the table.

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Exam Code: Professional-Data-Engineer
Exam Name: Google Professional Data Engineer Exam
Last Update: Jul 10, 2024
Questions: 330
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