Quiz Updated ADP - Associate Data Practitioner Test Pattern

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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Cloud Storage ingestion patterns 2. Streaming ingestion with Pub/Sub concepts
Topic 2: Data Management	25%	- Storage and data organization 1. BigQuery datasets and tables management 2. Cloud Storage lifecycle policies - Data governance and security 1. Data lifecycle management 2. IAM and access control
Topic 3: Data Analysis and Presentation	27%	- Querying and analyzing data 1. Data aggregation and transformation 2. BigQuery SQL usage - Data visualization 1. Looker / Looker Studio reporting
Topic 4: Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Dataflow pipelines 2. Workflow orchestration concepts (e.g., Cloud Composer)

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Google Associate Data Practitioner Sample Questions (Q52-Q57):

NEW QUESTION # 52
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. Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
B. Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
C. Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
D. Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.

Answer: D

NEW QUESTION # 53
You manage data at an ecommerce company. You have a Dataflow pipeline that processes order data from Pub/Sub, enriches the data with product information from Bigtable, and writes the processed data to BigQuery for analysis. The pipeline runs continuously and processes thousands of orders every minute. You need to monitor the pipeline's performance and be alerted if errors occur. What should you do?

A. Use Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.
B. Use Cloud Monitoring to track key metrics. Create alerting policies in Cloud Monitoring to trigger notifications when metrics exceed thresholds or when errors occur.
C. Use BigQuery to analyze the processed data in Cloud Storage and identify anomalies or inconsistencies. Set up scheduled alerts based when anomalies or inconsistencies occur.
D. Use the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.

Answer: B

NEW QUESTION # 54
Your organization's website uses an on-premises MySQL as a backend database. You need to migrate the on-premises MySQL database to Google Cloud while maintaining MySQL features. You want to minimize administrative overhead and downtime. What should you do?

A. Export the database tables to CSV files, and upload the files to Cloud Storage. Convert the MySQL schema to a Spanner schema, create a JSON manifest file, and run a Google-provided Dataflow template to load the data into Spanner.
B. Install MySQL on a Compute Engine virtual machine. Export the database files using the mysqldump command. Upload the files to Cloud Storage, and import them into the MySQL instance on Compute Engine.
C. Use a Google-provided Dataflow template to replicate the MySQL database in BigQuery.
D. Use Database Migration Service to transfer the data to Cloud SQL for MySQL, and configure the on premises MySQL database as the source.

Answer: D

NEW QUESTION # 55
You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?

A. Use Cloud Client Libraries to transfer the data over the internet.
B. Use the gcloud storage command to transfer the data over the internet.
C. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
D. Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.

Answer: C

NEW QUESTION # 56
Your retail company wants to predict customer churn using historical purchase data stored in BigQuery. The dataset includes customer demographics, purchase history, and a label indicating whether the customer churned or not. You want to build a machine learning model to identify customers at risk of churning. You need to create and train a logistic regression model for predicting customer churn, using the customer_data table with the churned column as the target label. Which BigQuery ML query should you use?

A. CREATE OR REPLACE MODEL churn_prediction_model OPTIONS (rr.odel_type=' logisric_reg *) AS select * except(churned), churned AS label FROM customer_data;
B. CREATE OR REPLACE MODEL churn_prediction_model options(model_type='logistic_reg*) as select ' except(churned) FROM customer data;
C. CREATE OR REPLACE MODEL churn_prediction_model options (model type='logistic_reg') AS select churned as label FROM customer_data;
D. CREATE OR REPLACE MODEL churn_prediction_model OPTIONS(model_uype='logisric_reg') AS SELECT * from cusromer_data;

Answer: A

NEW QUESTION # 57
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