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Google Professional Data Engineer Exam Question and Answers

Google Professional Data Engineer Exam

Last Update Mar 28, 2024
Total Questions : 330

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Questions 1

You want to use Google Stackdriver Logging to monitor Google BigQuery usage. You need an instant notification to be sent to your monitoring tool when new data is appended to a certain table using an insert job, but you do not want to receive notifications for other tables. What should you do?

Options:

A.  

Make a call to the Stackdriver API to list all logs, and apply an advanced filter.

B.  

In the Stackdriver logging admin interface, and enable a log sink export to BigQuery.

C.  

In the Stackdriver logging admin interface, enable a log sink export to Google Cloud Pub/Sub, and subscribe to the topic from your monitoring tool.

D.  

Using the Stackdriver API, create a project sink with advanced log filter to export to Pub/Sub, and subscribe to the topic from your monitoring tool.

Discussion 0
Questions 2

You are building a model to predict whether or not it will rain on a given day. You have thousands of input features and want to see if you can improve training speed by removing some features while having a minimum effect on model accuracy. What can you do?

Options:

A.  

Eliminate features that are highly correlated to the output labels.

B.  

Combine highly co-dependent features into one representative feature.

C.  

Instead of feeding in each feature individually, average their values in batches of 3.

D.  

Remove the features that have null values for more than 50% of the training records.

Discussion 0
Questions 3

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

Discussion 0
Questions 4

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.

Discussion 0
Questions 5

Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow. Numerous data logs are being are being generated during this step, and the team wants to analyze them. Due to the dynamic nature of the campaign, the data is growing exponentially every hour.

The data scientists have written the following code to read the data for a new key features in the logs.

BigQueryIO.Read

.named(“ReadLogData”)

.from(“clouddataflow-readonly:samples.log_data”)

You want to improve the performance of this data read. What should you do?

Options:

A.  

Specify the TableReference object in the code.

B.  

Use .fromQuery operation to read specific fields from the table.

C.  

Use of both the Google BigQuery TableSchema and TableFieldSchema classes.

D.  

Call a transform that returns TableRow objects, where each element in the PCollexction represents a single row in the table.

Discussion 0
Questions 6

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*`

Discussion 0
Questions 7

You work for a car manufacturer and have set up a data pipeline using Google Cloud Pub/Sub to capture anomalous sensor events. You are using a push subscription in Cloud Pub/Sub that calls a custom HTTPS endpoint that you have created to take action of these anomalous events as they occur. Your custom HTTPS endpoint keeps getting an inordinate amount of duplicate messages. What is the most likely cause of these duplicate messages?

Options:

A.  

The message body for the sensor event is too large.

B.  

Your custom endpoint has an out-of-date SSL certificate.

C.  

The Cloud Pub/Sub topic has too many messages published to it.

D.  

Your custom endpoint is not acknowledging messages within the acknowledgement deadline.

Discussion 0
Questions 8

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.

Discussion 0
Questions 9

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.

Discussion 0
Questions 10

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.

Discussion 0
Questions 11

Your startup has never implemented a formal security policy. Currently, everyone in the company has access to the datasets stored in Google BigQuery. Teams have freedom to use the service as they see fit, and they have not documented their use cases. You have been asked to secure the data warehouse. You need to discover what everyone is doing. What should you do first?

Options:

A.  

Use Google Stackdriver Audit Logs to review data access.

B.  

Get the identity and access management IIAM) policy of each table

C.  

Use Stackdriver Monitoring to see the usage of BigQuery query slots.

D.  

Use the Google Cloud Billing API to see what account the warehouse is being billed to.

Discussion 0
Questions 12

You have Google Cloud Dataflow streaming pipeline running with a Google Cloud Pub/Sub subscription as the source. You need to make an update to the code that will make the new Cloud Dataflow pipeline incompatible with the current version. You do not want to lose any data when making this update. What should you do?

Options:

A.  

Update the current pipeline and use the drain flag.

B.  

Update the current pipeline and provide the transform mapping JSON object.

C.  

Create a new pipeline that has the same Cloud Pub/Sub subscription and cancel the old pipeline.

D.  

Create a new pipeline that has a new Cloud Pub/Sub subscription and cancel the old pipeline.

Discussion 0
Questions 13

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.

Discussion 0
Questions 14

Your company uses a proprietary system to send inventory data every 6 hours to a data ingestion service in the cloud. Transmitted data includes a payload of several fields and the timestamp of the transmission. If there are any concerns about a transmission, the system re-transmits the data. How should you deduplicate the data most efficiency?

Options:

A.  

Assign global unique identifiers (GUID) to each data entry.

B.  

Compute the hash value of each data entry, and compare it with all historical data.

C.  

Store each data entry as the primary key in a separate database and apply an index.

D.  

Maintain a database table to store the hash value and other metadata for each data entry.

Discussion 0
Questions 15

Your weather app queries a database every 15 minutes to get the current temperature. The frontend is powered by Google App Engine and server millions of users. How should you design the frontend to respond to a database failure?

Options:

A.  

Issue a command to restart the database servers.

B.  

Retry the query with exponential backoff, up to a cap of 15 minutes.

C.  

Retry the query every second until it comes back online to minimize staleness of data.

D.  

Reduce the query frequency to once every hour until the database comes back online.

Discussion 0
Questions 16

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.

Discussion 0
Questions 17

You have uploaded 5 years of log data to Cloud Storage A user reported that some data points in the log data are outside of their expected ranges, which indicates errors You need to address this issue and be able to run the process again in the future while keeping the original data for compliance reasons. What should you do?

Options:

A.  

Import the data from Cloud Storage into BigQuery Create a new BigQuery table, and skip the rows with errors.

B.  

Create a Compute Engine instance and create a new copy of the data in Cloud Storage Skip the rows with errors

C.  

Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to a new dataset in

Cloud Storage

D.  

Create a Cloud Dataflow workflow that reads the data from Cloud Storage, checks for values outside the expected range, sets the value to an appropriate default, and writes the updated records to the same dataset in Cloud Storage

Discussion 0
Questions 18

Your new customer has requested daily reports that show their net consumption of Google Cloud compute resources and who used the resources. You need to quickly and efficiently generate these daily reports. What should you do?

Options:

A.  

Do daily exports of Cloud Logging data to BigQuery. Create views filtering by project, log type, resource, and user.

B.  

Filter data in Cloud Logging by project, resource, and user; then export the data in CSV format.

C.  

Filter data in Cloud Logging by project, log type, resource, and user, then import the data into BigQuery.

D.  

Export Cloud Logging data to Cloud Storage in CSV format. Cleanse the data using Dataprep, filtering by project, resource, and user.

Discussion 0
Questions 19

You are designing storage for 20 TB of text files as part of deploying a data pipeline on Google Cloud. Your input data is in CSV format. You want to minimize the cost of querying aggregate values for multiple users who will query the data in Cloud Storage with multiple engines. Which storage service and schema design should you use?

Options:

A.  

Use Cloud Bigtable for storage. Install the HBase shell on a Compute Engine instance to query the Cloud Bigtable data.

B.  

Use Cloud Bigtable for storage. Link as permanent tables in BigQuery for query.

C.  

Use Cloud Storage for storage. Link as permanent tables in BigQuery for query.

D.  

Use Cloud Storage for storage. Link as temporary tables in BigQuery for query.

Discussion 0
Questions 20

You are migrating a large number of files from a public HTTPS endpoint to Cloud Storage. The files are protected from unauthorized access using signed URLs. You created a TSV file that contains the list of object URLs and started a transfer job by using Storage Transfer Service. You notice that the job has run for a long time and eventually failed Checking the logs of the transfer job reveals that the job was running fine until one point, and then it failed due to HTTP 403 errors on the remaining files You verified that there were no changes to the source system You need to fix the problem to resume the migration process. What should you do?

Options:

A.  

Set up Cloud Storage FUSE, and mount the Cloud Storage bucket on a Compute Engine Instance Remove the completed files from the TSV file Use a shell script to iterate through the TSV file and download the remaining URLs to the FUSE mount point.

B.  

Update the file checksums in the TSV file from using MD5 to SHA256. Remove the completed files from the TSV file and rerun the Storage Transfer Service job.

C.  

Renew the TLS certificate of the HTTPS endpoint Remove the completed files from the TSV file and rerun the Storage Transfer Service job.

D.  

Create a new TSV file for the remaining files by generating signed URLs with a longer validity period. Split the TSV file into multiple smaller files and submit them as separate Storage Transfer Service jobs in parallel.

Discussion 0
Questions 21

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.

Discussion 0
Questions 22

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

Discussion 0
Questions 23

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.

Discussion 0
Questions 24

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.

Discussion 0
Questions 25

You work for a manufacturing plant that batches application log files together into a single log file once a day at 2:00 AM. You have written a Google Cloud Dataflow job to process that log file. You need to make sure the log file in processed once per day as inexpensively as possible. What should you do?

Options:

A.  

Change the processing job to use Google Cloud Dataproc instead.

B.  

Manually start the Cloud Dataflow job each morning when you get into the office.

C.  

Create a cron job with Google App Engine Cron Service to run the Cloud Dataflow job.

D.  

Configure the Cloud Dataflow job as a streaming job so that it processes the log data immediately.

Discussion 0
Questions 26

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.

Discussion 0
Questions 27

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

Discussion 0
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.

Discussion 0
Questions 29

You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

Options:

A.  

Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.

B.  

Add a new column called FullName to the Users table. Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.

C.  

Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.

D.  

Use BigQuery to export the data for the table to a CSV file. Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullName. Run a BigQuery load job to load the new CSV file into BigQuery.

Discussion 0
Questions 30

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.

Discussion 0
Questions 31

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

Discussion 0
Questions 32

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.

Discussion 0
Questions 33

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

Discussion 0
Questions 34

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.

Discussion 0
Questions 35

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.

Discussion 0
Questions 36

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.

Discussion 0
Questions 37

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

Discussion 0
Questions 38

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.

Discussion 0
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

Discussion 0
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.

Discussion 0
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

Discussion 0
Questions 42

Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.

SELECT person FROM `project1.example.table1` WHERE city = "London"

How would you correct the error?

Options:

A.  

Add ", UNNEST(person)" before the WHERE clause.

B.  

Change "person" to "person.city".

C.  

Change "person" to "city.person".

D.  

Add ", UNNEST(city)" before the WHERE clause.

Discussion 0
Questions 43

What are two methods that can be used to denormalize tables in BigQuery?

Options:

A.  

1) Split table into multiple tables; 2) Use a partitioned table

B.  

1) Join tables into one table; 2) Use nested repeated fields

C.  

1) Use a partitioned table; 2) Join tables into one table

D.  

1) Use nested repeated fields; 2) Use a partitioned table

Discussion 0
Questions 44

You have a job that you want to cancel. It is a streaming pipeline, and you want to ensure that any data that is in-flight is processed and written to the output. Which of the following commands can you use on the Dataflow monitoring console to stop the pipeline job?

Options:

A.  

Cancel

B.  

Drain

C.  

Stop

D.  

Finish

Discussion 0
Questions 45

What are the minimum permissions needed for a service account used with Google Dataproc?

Options:

A.  

Execute to Google Cloud Storage; write to Google Cloud Logging

B.  

Write to Google Cloud Storage; read to Google Cloud Logging

C.  

Execute to Google Cloud Storage; execute to Google Cloud Logging

D.  

Read and write to Google Cloud Storage; write to Google Cloud Logging

Discussion 0
Questions 46

What are two of the characteristics of using online prediction rather than batch prediction?

Options:

A.  

It is optimized to handle a high volume of data instances in a job and to run more complex models.

B.  

Predictions are returned in the response message.

C.  

Predictions are written to output files in a Cloud Storage location that you specify.

D.  

It is optimized to minimize the latency of serving predictions.

Discussion 0
Questions 47

To run a TensorFlow training job on your own computer using Cloud Machine Learning Engine, what would your command start with?

Options:

A.  

gcloud ml-engine local train

B.  

gcloud ml-engine jobs submit training

C.  

gcloud ml-engine jobs submit training local

D.  

You can't run a TensorFlow program on your own computer using Cloud ML Engine .

Discussion 0
Questions 48

When running a pipeline that has a BigQuery source, on your local machine, you continue to get permission denied errors. What could be the reason for that?

Options:

A.  

Your gcloud does not have access to the BigQuery resources

B.  

BigQuery cannot be accessed from local machines

C.  

You are missing gcloud on your machine

D.  

Pipelines cannot be run locally

Discussion 0
Questions 49

You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name from the data source and then write to an output PCollection.

Tom,555 X street

Tim,553 Y street

Sam, 111 Z street

Which operation is best suited for the above data processing requirement?

Options:

A.  

ParDo

B.  

Sink API

C.  

Source API

D.  

Data extraction

Discussion 0
Questions 50

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

Discussion 0
Questions 51

Which software libraries are supported by Cloud Machine Learning Engine?

Options:

A.  

Theano and TensorFlow

B.  

Theano and Torch

C.  

TensorFlow

D.  

TensorFlow and Torch

Discussion 0