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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q58-Q63):

NEW QUESTION # 58
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 separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
B. Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.
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: B

NEW QUESTION # 59
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 view that filters out rows that are older than one year.
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 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.

Answer: C

NEW QUESTION # 60
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 DATE_DIFF() 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 materialized view in BigQuery that uses the SUM() function and the DATE_SUB() function.
D. Create a BigQuery table that uses the SUM() function and the _PARTITIONDATE filter.

Answer: C

NEW QUESTION # 61
Your organization's ecommerce website collects user activity logs using a Pub/Sub topic. Your organization's leadership team wants a dashboard that contains aggregated user engagement metrics. You need to create a solution that transforms the user activity logs into aggregated metrics, while ensuring that the raw data can be easily queried. What should you do?

A. Create a Dataflow subscription to the Pub/Sub topic, and transform the activity logs. Load the transformed data into a BigQuery table for reporting.
B. Create a BigQuery subscription to the Pub/Sub topic, and load the activity logs into the table. Create a materialized view in BigQuery using SQL to transform the data for reporting
C. Create a Cloud Storage subscription to the Pub/Sub topic. Load the activity logs into a bucket using the Avro file format. Use Dataflow to transform the data, and load it into a BigQuery table for reporting.
D. Create an event-driven Cloud Run function to trigger a data transformation pipeline to run. Load the transformed activity logs into a BigQuery table for reporting.

Answer: A

NEW QUESTION # 62
You are developing a data ingestion pipeline to load small CSV files into BigQuery from Cloud Storage. You want to load these files upon arrival to minimize data latency. You want to accomplish this with minimal cost and maintenance. What should you do?

A. Create a Cloud Composer pipeline to load new files from Cloud Storage to BigQuery and schedule it to run every 10 minutes.
B. Create a Dataproc cluster to pull CSV files from Cloud Storage, process them using Spark, and write the results to BigQuery.
C. Use the bq command-line tool within a Cloud Shell instance to load the data into BigQuery.
D. Create a Cloud Run function to load the data into BigQuery that is triggered when data arrives in Cloud Storage.

Answer: D

NEW QUESTION # 63
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