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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q64-Q69):

NEW QUESTION # 64
Your team wants to create a monthly report to analyze inventory data that is updated daily. You need to aggregate the inventory counts by using only the most recent month of data, and save the results to be used in a Looker Studio dashboard. What should you do?

A. Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.
B. Create a materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
C. Create a saved query in the BigQuery console that uses the SUM() function and the DATE_SUB() function. Re-run the saved query every month, and save the results to a BigQuery table.
D. Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.

Answer: B

NEW QUESTION # 65
You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?

A. Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.
B. Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
C. Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
D. Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.

Answer: A

NEW QUESTION # 66
You work for a healthcare company. You have a daily ETL pipeline that extracts patient data from a legacy system, transforms it, and loads it into BigQuery for analysis. The pipeline currently runs manually using a shell script. You want to automate this process and add monitoring to ensure pipeline observability and troubleshooting insights. You want one centralized solution, using open-source tooling, without rewriting the ETL code. What should you do?

A. Configure Cloud Dataflow to implement the ETL pipeline, and use Cloud Scheduler to trigger the Dataflow pipeline daily. Monitor the pipelines execution using the Dataflow job monitoring interface and Cloud Monitoring.
B. Use Cloud Scheduler to trigger a Dataproc job to execute the pipeline daily. Monitor the job's progress using the Dataproc job web interface and Cloud Monitoring.
C. Create a direct acyclic graph (DAG) in Cloud Composer to orchestrate a pipeline trigger daily. Monitor the pipeline's execution using the Apache Airflow web interface and Cloud Monitoring.
D. Create a Cloud Run function that runs the pipeline daily. Monitor the functions execution using Cloud Monitoring.

Answer: C

NEW QUESTION # 67
Your organization needs to store historical customer order dat
a. The data will only be accessed once a month for analysis and must be readily available within a few seconds when it is accessed. You need to choose a storage class that minimizes storage costs while ensuring that the data can be retrieved quickly. What should you do?

A. Store the data in Cloud Storage using Archive storage.
B. Store the data in Cloud Storage using Standard storage.
C. Store the data in Cloud Storage using Nearline storage.
D. Store the data in Cloud Storage using Coldline storage.

Answer: C

NEW QUESTION # 68
Following a recent company acquisition, you inherited an on- premises data infrastructure that needs to move to Google Cloud. The acquired system has 250 Apache Airflow directed acyclic graphs (DAGs) orchestrating data pipelines. You need to migrate the pipelines to a Google Cloud managed service with minimal effort. What should you do?

A. Create a Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
B. Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.
C. Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.
D. Create a Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.

Answer: B

NEW QUESTION # 69
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