Quiz Google - Authoritative ADP - Associate Data Practitioner Practice Test Fee

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Visualization and Insights	20-30%	- Create dashboards and reports - Build visualizations using Looker Studio - Interpret and communicate findings - Choose appropriate visualization types - Present data insights to stakeholders
Topic 2: Data-Driven Decision Making	10-20%	- Assess data quality and completeness - Define success metrics - Identify stakeholders and requirements - Translate business requirements into data solutions
Topic 3: Data Preparation and Exploration	20-30%	- Ingest and acquire data - Identify data quality issues - Explore data through visualization and queries - Transform and prepare data for analysis - Perform exploratory data analysis (EDA)
Topic 4: Data Processing and Analytics	20-30%	- Use BigQuery and SQL for analytics - Apply statistical methods for analysis - Build and maintain data pipelines - Query and analyze datasets - Aggregate and summarize data

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Google Associate Data Practitioner Sample Questions (Q14-Q19):

NEW QUESTION # 14
You manage a Cloud Storage bucket that stores temporary files created during data processing. These temporary files are only needed for seven days, after which they are no longer needed. To reduce storage costs and keep your bucket organized, you want to automatically delete these files once they are older than seven days. What should you do?

A. Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.
B. Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
C. Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
D. Create a Cloud Run function that runs daily and deletes files older than seven days.

Answer: B

NEW QUESTION # 15
Your company wants to implement a data transformation (ETL) pipeline for their BigQuery data warehouse.
You need to identify a managed transformation solution that allows users to develop with SQL and JavaScript, has version control, allows for modular code, and has data quality checks. What should you do?

A. Create BigQuery scheduled queries to define the transformations in SQL.
B. Create a Cloud Composer environment, and orchestrate the transformations by using the BigQueryinsertJob operator.
C. Use Dataproc to create an Apache Spark cluster and implement the transformations by using PySpark SQL.
D. Use Dataform to define the transformations in SQLX.

Answer: D

NEW QUESTION # 16
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?

A. Create a temporary table.
B. Create an object table.
C. Create a native table.
D. Create an external table.

Answer: B

NEW QUESTION # 17
You are migrating data from a legacy on-premises MySQL database to Google Cloud. The database contains various tables with different data types and sizes, including large tables with millions of rows and transactional dat a. You need to migrate this data while maintaining data integrity, and minimizing downtime and cost. What should you do?

A. Use Cloud Data Fusion to migrate the MySQL database to MySQL on Compute Engine.
B. Use Database Migration Service to replicate the MySQL database to a Cloud SQL for MySQL instance.
C. Set up a Cloud Composer environment to orchestrate a custom data pipeline. Use a Python script to extract data from the MySQL database and load it to MySQL on Compute Engine.
D. Export the MySQL database to CSV files, transfer the files to Cloud Storage by using Storage Transfer Service, and load the files into a Cloud SQL for MySQL instance.

Answer: B

NEW QUESTION # 18
Your organization's ecommerce website collects user activity logs using a Pub/Sub topic. Your organization's leadership team wants a dashboard that contains aggregated user engagement metrics. You need to create a solution that transforms the user activity logs into aggregated metrics, while ensuring that the raw data can be easily queried. What should you do?

A. Create a Dataflow subscription to the Pub/Sub topic, and transform the activity logs. Load the transformed data into a BigQuery table for reporting.
B. Create a Cloud Storage subscription to the Pub/Sub topic. Load the activity logs into a bucket using the Avro file format. Use Dataflow to transform the data, and load it into a BigQuery table for reporting.
C. Create a BigQuery subscription to the Pub/Sub topic, and load the activity logs into the table. Create a materialized view in BigQuery using SQL to transform the data for reporting
D. Create an event-driven Cloud Run function to trigger a data transformation pipeline to run. Load the transformed activity logs into a BigQuery table for reporting.

Answer: A

NEW QUESTION # 19
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