NEW QUESTION 1

You are developing an application on Google Cloud that will automatically generate subject labels for users’ blog posts. You are under competitive pressure to add this feature quickly, and you have no additional developer resources. No one on your team has experience with machine learning. What should you do?

• A. Call the Cloud Natural Language API from your applicatio
• B. Process the generated Entity Analysis as labels.
• C. Call the Cloud Natural Language API from your applicatio
• D. Process the generated Sentiment Analysis as labels.
• E. Build and train a text classification model using TensorFlo
• F. Deploy the model using Cloud Machine Learning Engin
• G. Call the model from your application and process the results as labels.
• H. Build and train a text classification model using TensorFlo
• I. Deploy the model using a KubernetesEngine cluste
• J. Call the model from your application and process the results as labels.

Answer: B

NEW QUESTION 2

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?

• A. Create groups for your users and give those groups access to the dataset
• B. Integrate with a single sign-on (SSO) platform, and pass each user’s credentials along with the query request
• C. Create a service account and grant dataset access to that accoun
• D. Use the service account’s private key to access the dataset
• E. Create a dummy user and grant dataset access to that use
• F. Store the username and password for that user in a file on the files system, and use those credentials to access the BigQuery dataset

Answer: C

NEW QUESTION 3

Cloud Dataproc charges you only for what you really use with billing.

• A. month-by-month
• B. minute-by-minute
• C. week-by-week
• D. hour-by-hour

Answer: B

Explanation:
One of the advantages of Cloud Dataproc is its low cost. Dataproc charges for what you really use with minute-by-minute billing and a low, ten-minute-minimum billing period.
Reference: https://cloud.google.com/dataproc/docs/concepts/overview

NEW QUESTION 4

You want to analyze hundreds of thousands of social media posts daily at the lowest cost and with the fewest steps.
You have the following requirements:
You will batch-load the posts once per day and run them through the Cloud Natural Language API.
You will extract topics and sentiment from the posts.
You must store the raw posts for archiving and reprocessing.
You will create dashboards to be shared with people both inside and outside your organization.
You need to store both the data extracted from the API to perform analysis as well as the raw social media posts for historical archiving. What should you do?

• A. Store the social media posts and the data extracted from the API in BigQuery.
• B. Store the social media posts and the data extracted from the API in Cloud SQL.
• C. Store the raw social media posts in Cloud Storage, and write the data extracted from the API into BigQuery.
• D. Feed to social media posts into the API directly from the source, and write the extracted data from the API into BigQuery.

Answer: D

NEW QUESTION 5

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?

• A. Cloud Speech-to-Text API
• B. Cloud Natural Language API
• C. Dialogflow Enterprise Edition
• D. Cloud AutoML Natural Language

Answer: D

NEW QUESTION 6

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?

• A. BigQuery
• B. Cloud SQL
• C. Cloud Bigtable
• D. Cloud Datastore

Answer: A

NEW QUESTION 7

Which of the following IAM roles does your Compute Engine account require to be able to run pipeline jobs?

• A. dataflow.worker
• B. dataflow.compute
• C. dataflow.developer
• D. dataflow.viewer

Answer: A

Explanation:
The dataflow.worker role provides the permissions necessary for a Compute Engine service account to execute work units for a Dataflow pipeline
Reference: https://cloud.google.com/dataflow/access-control

NEW QUESTION 8

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?

• 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.

Answer: D

NEW QUESTION 9

If a dataset contains rows with individual people and columns for year of birth, country, and income, how many of the columns are continuous and how many are categorical?

• A. 1 continuous and 2 categorical
• B. 3 categorical
• C. 3 continuous
• D. 2 continuous and 1 categorical

Answer: D

Explanation:
The columns can be grouped into two types—categorical and continuous columns:
A column is called categorical if its value can only be one of the categories in a finite set. For example, the native country of a person (U.S., India, Japan, etc.) or the education level (high school, college, etc.) are categorical columns.
A column is called continuous if its value can be any numerical value in a continuous range. For example, the capital gain of a person (e.g. $14,084) is a continuous column.
Year of birth and income are continuous columns. Country is a categorical column.
You could use bucketization to turn year of birth and/or income into categorical features, but the raw columns are continuous.
Reference: https://www.tensorflow.org/tutorials/wide#reading_the_census_data

NEW QUESTION 10

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?

• 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.

Answer: A

Explanation:
Reference https://support.google.com/datastudio/answer/7020039?hl=en

NEW QUESTION 11

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.)

• 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.

Answer: BDF

NEW QUESTION 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?

• 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 othernecessary tables to avoid self-join.
• D. Partition the table into smaller tables, with one for each clini
• E. Run queries against the smaller table pairs, and use unions for consolidated reports.

Answer: B

NEW QUESTION 13

Your company is selecting a system to centralize data ingestion and delivery. You are considering messaging and data integration systems to address the requirements. The key requirements are:
The ability to seek to a particular offset in a topic, possibly back to the start of all data ever captured
Support for publish/subscribe semantics on hundreds of topics
Retain per-key ordering Which system should you choose?

• A. Apache Kafka
• B. Cloud Storage
• C. Cloud Pub/Sub
• D. Firebase Cloud Messaging

Answer: A

NEW QUESTION 14

Which of the following is NOT true about Dataflow pipelines?

• A. Dataflow pipelines are tied to Dataflow, and cannot be run on any other runner
• B. Dataflow pipelines can consume data from other Google Cloud services
• C. Dataflow pipelines can be programmed in Java
• D. Dataflow pipelines use a unified programming model, so can work both with streaming and batch data sources

Answer: A

Explanation:
Dataflow pipelines can also run on alternate runtimes like Spark and Flink, as they are built using the Apache Beam SDKs
Reference: https://cloud.google.com/dataflow/

NEW QUESTION 15

You store historic data in Cloud Storage. You need to perform analytics on the historic data. You want to use a solution to detect invalid data entries and perform data transformations that will not require programming or knowledge of SQL.
What should you do?

• A. Use Cloud Dataflow with Beam to detect errors and perform transformations.
• B. Use Cloud Dataprep with recipes to detect errors and perform transformations.
• C. Use Cloud Dataproc with a Hadoop job to detect errors and perform transformations.
• D. Use federated tables in BigQuery with queries to detect errors and perform transformations.

Answer: A

NEW QUESTION 16

You are operating a streaming Cloud Dataflow pipeline. Your engineers have a new version of the pipeline with a different windowing algorithm and triggering strategy. You want to update the running pipeline with the new version. You want to ensure that no data is lost during the update. What should you do?

• A. Update the Cloud Dataflow pipeline inflight by passing the --update option with the --jobName set to the existing job name
• B. Update the Cloud Dataflow pipeline inflight by passing the --update option with the --jobName set to a new unique job name
• C. Stop the Cloud Dataflow pipeline with the Cancel optio
• D. Create a new Cloud Dataflow job with the updated code
• E. Stop the Cloud Dataflow pipeline with the Drain optio
• F. Create a new Cloud Dataflow job with the updated code

Answer: A

NEW QUESTION 17

You need to move 2 PB of historical data from an on-premises storage appliance to Cloud Storage within six months, and your outbound network capacity is constrained to 20 Mb/sec. How should you migrate this data to Cloud Storage?

• A. Use Transfer Appliance to copy the data to Cloud Storage
• B. Use gsutil cp –J to compress the content being uploaded to Cloud Storage
• C. Create a private URL for the historical data, and then use Storage Transfer Service to copy the data to Cloud Storage
• D. Use trickle or ionice along with gsutil cp to limit the amount of bandwidth gsutil utilizes to less than 20 Mb/sec so it does not interfere with the production traffic

Answer: A

NEW QUESTION 18

You are designing storage for two relational tables that are part of a 10-TB database on Google Cloud. You want to support transactions that scale horizontally. You also want to optimize data for range queries on nonkey columns. What should you do?

• A. Use Cloud SQL for storag
• B. Add secondary indexes to support query patterns.
• C. Use Cloud SQL for storag
• D. Use Cloud Dataflow to transform data to support query patterns.
• E. Use Cloud Spanner for storag
• F. Add secondary indexes to support query patterns.
• G. Use Cloud Spanner for storag
• H. Use Cloud Dataflow to transform data to support query patterns.

Answer: D

Explanation:
Reference: https://cloud.google.com/solutions/data-lifecycle-cloud-platform

NEW QUESTION 19

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?

• 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

Answer: A

Explanation:
When reading from a Dataflow source or writing to a Dataflow sink using DirectPipelineRunner, the Cloud Platform account that you configured with the gcloud executable will need access to the corresponding source/sink
Reference:
https://cloud.google.com/dataflow/java-sdk/JavaDoc/com/google/cloud/dataflow/sdk/runners/DirectPipelineRun

NEW QUESTION 20

Your organization has been collecting and analyzing data in Google BigQuery for 6 months. The majority of the data analyzed is placed in a time-partitioned table named events_partitioned. To reduce the cost of queries, your organization created a view called events, which queries only the last 14 days of data. The view is described in legacy SQL. Next month, existing applications will be connecting to BigQuery to read the events data via an ODBC connection. You need to ensure the applications can connect. Which two actions should you take? (Choose two.)

• A. Create a new view over events using standard SQL
• B. Create a new partitioned table using a standard SQL query
• C. Create a new view over events_partitioned using standard SQL
• D. Create a service account for the ODBC connection to use for authentication
• E. Create a Google Cloud Identity and Access Management (Cloud IAM) role for the ODBC connectionand shared “events”

Answer: AE

NEW QUESTION 21

Which action can a Cloud Dataproc Viewer perform?

• A. Submit a job.
• B. Create a cluster.
• C. Delete a cluster.
• D. List the jobs.

Answer: D

Explanation:
A Cloud Dataproc Viewer is limited in its actions based on its role. A viewer can only list clusters, get cluster details, list jobs, get job details, list operations, and get operation details.
Reference: https://cloud.google.com/dataproc/docs/concepts/iam#iam_roles_and_cloud_dataproc_operations_summary

NEW QUESTION 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?

• 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.

Answer: B

NEW QUESTION 23

You work for a mid-sized enterprise that needs to move its operational system transaction data from an on-premises database to GCP. The database is about 20 TB in size. Which database should you choose?

• A. Cloud SQL
• B. Cloud Bigtable
• C. Cloud Spanner
• D. Cloud Datastore

Answer: A

NEW QUESTION 24
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