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Google ADP Exam Syllabus Topics:

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

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Valid ADP Vce - Exam ADP Objectives Pdf

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

NEW QUESTION # 33
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 materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
B. 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.
C. Create a BigQuery table that uses the SUM() function and the DATE_DIFF() function.
D. Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.

Answer: A

NEW QUESTION # 34
You manage a large amount of data in Cloud Storage, including raw data, processed data, and backups. Your organization is subject to strict compliance regulations that mandate data immutability for specific data types.
You want to use an efficient process to reduce storage costs while ensuring that your storage strategy meets retention requirements. What should you do?

A. Move objects to different storage classes based on their age and access patterns. Use Cloud Key Management Service (Cloud KMS) to encrypt specific objects with customer-managed encryption keys (CMEK) to meet immutability requirements.
B. Create a Cloud Run function to periodically check object metadata, and move objects to the appropriate storage class based on age and access patterns. Use object holds to enforce immutability for specific objects.
C. Configure lifecycle management rules to transition objects to appropriate storage classes based on access patterns. Set up Object Versioning for all objects to meet immutability requirements.
D. Use object holds to enforce immutability for specific objects, and configure lifecycle management rules to transition objects to appropriate storage classes based on age and access patterns.

Answer: D

NEW QUESTION # 35
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 Cloud Composer to orchestrate the Spark job and email the report.
B. Use Cloud Run functions to trigger the Spark job and email the report.
C. Use Dataproc workflow templates to define and schedule the Spark job, and to email the report.
D. Use Cloud Scheduler to trigger the Spark job. and use Cloud Run functions to email the report.

Answer: C

NEW QUESTION # 36
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 Cloud Data Fusion instance. For each DAG, create a Cloud Data Fusion pipeline.
B. Convert each DAG to a Cloud Workflow and automate the execution with Cloud Scheduler.
C. Create a Google Kubernetes Engine (GKE) standard cluster and deploy Airflow as a workload. Migrate all DAGs to the new Airflow environment.
D. Create a new Cloud Composer environment and copy DAGS to the Cloud Composer dags/folder.

Answer: D

NEW QUESTION # 37
You are a data analyst working with sensitive customer data in BigQuery. You need to ensure that only authorized personnel within your organization can query this data, while following the principle of least privilege. What should you do?

A. Export the data to Cloud Storage, and use signed URLs to authorize access.
B. Encrypt the data by using customer-managed encryption keys (CMEK).
C. Update dataset privileges by using the SQL GRANT statement.
D. Enable access control by using IAM roles.

Answer: D

NEW QUESTION # 38
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