Google - Authoritative ADP Dumps

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data Management	25%	- Storage and data organization 1. Cloud Storage lifecycle policies 2. BigQuery datasets and tables management - Data governance and security 1. Data lifecycle management 2. IAM and access control
Data Analysis and Presentation	27%	- Data visualization 1. Looker / Looker Studio reporting - Querying and analyzing data 1. Data aggregation and transformation 2. BigQuery SQL usage
Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Streaming ingestion with Pub/Sub concepts 2. Cloud Storage ingestion patterns
Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Workflow orchestration concepts (e.g., Cloud Composer) 2. Dataflow pipelines

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

NEW QUESTION # 14
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. Use Dataform to define the transformations in SQLX.
B. Use Dataproc to create an Apache Spark cluster and implement the transformations by using PySpark SQL.
C. Create BigQuery scheduled queries to define the transformations in SQL.
D. Create a Cloud Composer environment, and orchestrate the transformations by using the BigQueryinsertJob operator.

Answer: A

NEW QUESTION # 15
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 an object table.
B. Create a native table.
C. Create a temporary table.
D. Create an external table.

Answer: A

NEW QUESTION # 16
You are working on a data pipeline that will validate and clean incoming data before loading it into BigQuery for real-time analysis. You want to ensure that the data validation and cleaning is performed efficiently and can handle high volumes of dat a. What should you do?

A. Use Cloud Run functions to trigger data validation and cleaning routines when new data arrives in Cloud Storage.
B. Use Dataflow to create a streaming pipeline that includes validation and transformation steps.
C. Write custom scripts in Python to validate and clean the data outside of Google Cloud. Load the cleaned data into BigQuery.
D. Load the raw data into BigQuery using Cloud Storage as a staging area, and use SQL queries in BigQuery to validate and clean the data.

Answer: B

NEW QUESTION # 17
Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?

A. Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.
B. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
C. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.
D. Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.

Answer: C

NEW QUESTION # 18
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. Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
B. Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
C. Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.
D. Create a Cloud Run function that runs daily and deletes files older than seven days.

Answer: B

NEW QUESTION # 19
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