Quiz 2026 ADP: Associate Data Practitioner High Hit-Rate New Exam Objectives

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Google ADP Exam Syllabus Topics:

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

>> New ADP Exam Objectives <<

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Google Associate Data Practitioner Sample Questions (Q33-Q38):

NEW QUESTION # 33
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. Create a Cloud Run function that runs daily and deletes files older than seven days.
C. Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
D. Develop a batch process using Dataflow that runs weekly and deletes files based on their age.

Answer: C

NEW QUESTION # 34
You have a Dataflow pipeline that processes website traffic logs stored in Cloud Storage and writes the processed data to BigQuery. You noticed that the pipeline is failing intermittently. You need to troubleshoot the issue. What should you do?

A. Use Cloud Logging to create a chart displaying the pipeline's error logs. Use Metrics Explorer to validate the findings from the chart.
B. Use Cloud Logging to identify error groups in the pipeline's logs. Use Cloud Monitoring to create a dashboard that tracks the number of errors in each group.
C. Use the Dataflow job monitoring interface to check the pipeline's status every hour. Use Cloud Profiler to analyze the pipeline's metrics, such as CPU utilization and memory usage.
D. Use Cloud Logging to view error messages in the pipeline's logs. Use Cloud Monitoring to analyze the pipeline's metrics, such as CPU utilization and memory usage.

Answer: D

NEW QUESTION # 35
Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards.
You need to implement a solution quickly and efficiently. What should you do?

A. Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
B. Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
C. Apply a filter to only show products with a positive profit margin.
D. Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.

Answer: B

NEW QUESTION # 36
Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.
B. Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.
C. Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.
D. Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.

Answer: B

NEW QUESTION # 37
You need to design a data pipeline to process large volumes of raw server log data stored in Cloud Storage.
The data needs to be cleaned, transformed, and aggregated before being loaded into BigQuery for analysis.
The transformation involves complex data manipulation using Spark scripts that your team developed. You need to implement a solution that leverages your team's existing skillset, processes data at scale, and minimizes cost. What should you do?

A. Use Dataflow with a custom template for the transformation logic.
B. Use Dataform to define the transformations in SQLX.
C. Use Cloud Data Fusion to visually design and manage the pipeline.
D. Use Dataproc to run the transformations on a cluster.

Answer: D

NEW QUESTION # 38
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