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Associate-Data-Practitioner Exam Dumps : Google Cloud Associate Data Practitioner (ADP Exam)

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Google Cloud Associate Data Practitioner (ADP Exam) Questions and Answers

Question 1

Your company’s customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files’ metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?

Options:

A.

Create an external table.

B.

Create a temporary table.

C.

Create a native table.

D.

Create an object table.

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Question 2

You are working with a large dataset of customer reviews stored in Cloud Storage. The dataset contains several inconsistencies, such as missing values, incorrect data types, and duplicate entries. You need toclean the data to ensure that it is accurate and consistent before using it for analysis. What should you do?

Options:

A.

Use the PythonOperator in Cloud Composer to clean the data and load it into BigQuery. Use SQL for analysis.

B.

Use BigQuery to batch load the data into BigQuery. Use SQL for cleaning and analysis.

C.

Use Storage Transfer Service to move the data to a different Cloud Storage bucket. Use event triggers to invoke Cloud Run functions to load the data into BigQuery. Use SQL for analysis.

D.

Use Cloud Run functions to clean the data and load it into BigQuery. Use SQL for analysis.

Question 3

Your retail company collects customer data from various sources:

Online transactions: Stored in a MySQL database

Customer feedback: Stored as text files on a company server

Social media activity: Streamed in real-time from social media platforms

You are designing a data pipeline to extract this data. Which Google Cloud storage system(s) should you select for further analysis and ML model training?

Options:

A.

1. Online transactions: Cloud Storage

2. Customer feedback: Cloud Storage

3. Social media activity: Cloud Storage

B.

1. Online transactions: BigQuery

2. Customer feedback: Cloud Storage

3. Social media activity: BigQuery

C.

1. Online transactions: Bigtable

2. Customer feedback: Cloud Storage

3. Social media activity: CloudSQL for MySQL

D.

1. Online transactions: Cloud SQL for MySQL

2. Customer feedback: BigQuery

3. Social media activity: Cloud Storage