ADP New Study Questions & Pass ADP Test Guide

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Streaming ingestion with Pub/Sub concepts 2. Cloud Storage ingestion patterns
Topic 2: Data Analysis and Presentation	27%	- Querying and analyzing data 1. Data aggregation and transformation 2. BigQuery SQL usage - Data visualization 1. Looker / Looker Studio reporting
Topic 3: Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Workflow orchestration concepts (e.g., Cloud Composer) 2. Dataflow pipelines
Topic 4: 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

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Google Associate Data Practitioner Sample Questions (Q47-Q52):

NEW QUESTION # 47
Your organization uses a BigQuery table that is partitioned by ingestion time. You need to remove data that is older than one year to reduce your organization's storage costs. You want to use the most efficient approach while minimizing cost. What should you do?

A. Require users to specify a partition filter using the alter table statement in SQL.
B. Create a scheduled query that periodically runs an update statement in SQL that sets the "deleted" column to "yes" for data that is more than one year old. Create a view that filters out rows that have been marked deleted.
C. Create a view that filters out rows that are older than one year.
D. Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.

Answer: D

NEW QUESTION # 48
Your organization has a petabyte of application logs stored as Parquet files in Cloud Storage. You need to quickly perform a one- time SQL-based analysis of the files and join them to data that already resides in BigQuery. What should you do?

A. Launch a Cloud Data Fusion environment, use plugins to connect to BigQuery and Cloud Storage, and use the SQL join operation to analyze the data.
B. Create a Dataproc cluster, and write a PySpark job to join the data from BigQuery to the files in Cloud Storage.
C. Use the bq load command to load the Parquet files into BigQuery, and perform SQL joins to analyze the data.
D. Create external tables over the files in Cloud Storage, and perform SQL joins to tables in BigQuery to analyze the data.

Answer: D

NEW QUESTION # 49
Your organization is building a new application on Google Cloud. Several data files will need to be stored in Cloud Storage. Your organization has approved only two specific cloud regions where these data files can reside. You need to determine a Cloud Storage bucket strategy that includes automated high availability.
What should you do?

A. Create a single-region bucket in each of the two regions, and use Storage Transfer Service to replicate the data across the buckets in both regions.
B. Create a dual-region bucket, and upload the files to this bucket.
C. Create a single-region bucket in each of the two regions, and use the gcloud storage command to replicate the data across the buckets in both regions.
D. Create a multi-region bucket, and upload the files to this bucket.

Answer: B

NEW QUESTION # 50
You have a Dataproc cluster that performs batch processing on data stored in Cloud Storage. You need to schedule a daily Spark job to generate a report that will be emailed to stakeholders. You need a fully-managed solution that is easy to implement and minimizes complexity. What should you do?

A. Use Dataproc workflow templates to define and schedule the Spark job, and to email the report.
B. Use Cloud Run functions to trigger the Spark job and email the report.
C. Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.
D. Use Cloud Composer to orchestrate the Spark job and email the report.

Answer: A

NEW QUESTION # 51
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. Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.
C. Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the error details.
D. Navigate to the Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.

Answer: D

NEW QUESTION # 52
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