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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q54-Q59):

NEW QUESTION # 54
Your organization is conducting analysis on regional sales metrics. Data from each regional sales team is stored as separate tables in BigQuery and updated monthly. You need to create a solution that identifies the top three regions with the highest monthly sales for the next three months. You want the solution to automatically provide up-to-date results. What should you do?

A. Create a BigQuery materialized view that performs a cross join across all of the regional sales tables. Use the row_number() window function to query the new materialized view.
B. Create a BigQuery table that performs a cross join across all of the regional sales tables. Use the rank() window function to query the new table.
C. Create a BigQuery materialized view that performs a union across all of the regional sales tables. Use the rank() window function to query the new materialized view.
D. Create a BigQuery table that performs a union across all of the regional sales tables. Use the row_number() window function to query the new table.

Answer: C

NEW QUESTION # 55
Your company is migrating their batch transformation pipelines to Google Cloud. You need to choose a solution that supports programmatic transformations using only SQL. You also want the technology to support Git integration for version control of your pipelines. What should you do?

A. Use Cloud Data Fusion pipelines.
B. Use Dataflow pipelines.
C. Use Dataform workflows.
D. Use Cloud Composer operators.

Answer: C

NEW QUESTION # 56
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 Run functions to trigger the Spark job and email the report.
B. Use Dataproc workflow templates to define and schedule the Spark job, and to 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: B

NEW QUESTION # 57
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. 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.
B. Require users to specify a partition filter using the alter table statement in SQL.
C. Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.
D. Create a view that filters out rows that are older than one year.

Answer: C

NEW QUESTION # 58
You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?

A. Use Vertex Al Workbench to develop a custom model for purchase prediction.
B. Use Colab Enterprise to develop a custom model for purchase prediction.
C. Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.
D. Use BigQuery ML to create a logistic regression model for purchase prediction.

Answer: D

NEW QUESTION # 59
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