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Google Associate Data Practitioner Sample Questions (Q30-Q35):

NEW QUESTION # 30
You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?

A. Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.
B. Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.
C. Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.
D. Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.

Answer: C

NEW QUESTION # 31
You need to create a new data pipeline. You want a serverless solution that meets the following requirements:
* Data is streamed from Pub/Sub and is processed in real-time.
* Data is transformed before being stored.
* Data is stored in a location that will allow it to be analyzed with SQL using Looker.
Which Google Cloud services should you recommend for the pipeline?

A. Dataproc Serverless Bigtable
B. Cloud Composer Cloud SQL for MySQL
C. Dataflow BigQuery
D. BigQuery Analytics Hub

Answer: C

NEW QUESTION # 32
Your retail company wants to analyze customer reviews to understand sentiment and identify areas for improvement. Your company has a large dataset of customer feedback text stored in BigQuery that includes diverse language patterns, emojis, and slang. You want to build a solution to classify customer sentiment from the feedback text. What should you do?

A. Develop a custom sentiment analysis model using TensorFlow. Deploy it on a Compute Engine instance.
B. Preprocess the text data in BigQuery using SQL functions. Export the processed data to AutoML Natural Language for model training and deployment.
C. Use Dataproc to create a Spark cluster, perform text preprocessing using Spark NLP, and build a sentiment analysis model with Spark MLlib.
D. Export the raw data from BigQuery. Use AutoML Natural Language to train a custom sentiment analysis model.

Answer: D

NEW QUESTION # 33
You are storing data in Cloud Storage for a machine learning project. The data is frequently accessed during the model training phase, minimally accessed after 30 days, and unlikely to be accessed after 90 days. You need to choose the appropriate storage class for the different stages of the project to minimize cost. What should you do?

A. Store the data in Standard storage during the model training phase. Transition the data to Durable Reduced Availability (DRA) storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.
B. Store the data in Nearline storage during the model training phase. Transition the data to Coldline storage 30 days after model deployment, and to Archive storage 90 days after model deployment.
C. Store the data in Standard storage during the model training phase. Transition the data to Nearline storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.
D. Store the data in Nearline storage during the model training phase. Transition the data to Archive storage 30 days after model deployment, and to Coldline storage 90 days after model deployment.

Answer: C

NEW QUESTION # 34
Your organization uses scheduled queries to perform transformations on data stored in BigQuery. You discover that one of your scheduled queries has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Set up a log sink using the gcloud CLI to export BigQuery audit logs to BigQuery. Query those logs to identify the error associated with the failed job I
B. Navigate to the Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.
C. Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.
D. Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the error details.

Answer: B

NEW QUESTION # 35
......

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Test ADP Centres - ADP Certificate Exam

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Valid ADP - Test Associate Data Practitioner Centres

Google Associate Data Practitioner Sample Questions (Q30-Q35):

Google ADP Desktop & Practice Test Software By Prep4pass

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