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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Data Pipeline Orchestration	18%	- Pipeline automation and scheduling 1. Schedule and monitor data jobs 2. Error handling and monitoring - Data transformation concepts 1. ETL vs ELT processes 2. Data transformation requirements - Transformation tools selection 1. Dataproc, Dataflow, Cloud Data Fusion, Cloud Composer, Dataform
Data Management and Governance	25%	- Data quality and maintenance 1. Data validation and cleaning 2. Data lifecycle management - Data security and access control 1. Data encryption and protection 2. IAM roles and permissions - Compliance and governance 1. Data stewardship and cataloging 2. Data privacy and regulatory requirements
Data Preparation and Ingestion	30%	- Storage solutions selection 1. Storage location types: regional, dual-regional, multi-regional, zonal 2. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner - Data extraction and transfer tools 1. Dataflow, BigQuery Data Transfer Service, Database Migration Service 2. Cloud Data Fusion, Storage Transfer Service - Data formats and classification 1. Structured, semi-structured, unstructured data 2. Formats: CSV, JSON, Parquet, Avro, database tables - Data loading methods 1. Batch and streaming ingestion 2. gcloud, BQ CLI, client libraries
Data Analysis and Presentation	27%	- Business intelligence and decision support 1. Answer business questions with data 2. Communicate findings effectively - Data exploration and analysis 1. Jupyter notebooks for analysis 2. Identify trends, patterns, insights 3. BigQuery SQL queries - Data visualization and reporting 1. Looker dashboards and reports 2. Visualization best practices

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Google Associate Data Practitioner Sample Questions (Q50-Q55):

NEW QUESTION # 50
You need to design a data pipeline to process large volumes of raw server log data stored in Cloud Storage.
The data needs to be cleaned, transformed, and aggregated before being loaded into BigQuery for analysis.
The transformation involves complex data manipulation using Spark scripts that your team developed. You need to implement a solution that leverages your team's existing skillset, processes data at scale, and minimizes cost. What should you do?

A. Use Dataform to define the transformations in SQLX.
B. Use Cloud Data Fusion to visually design and manage the pipeline.
C. Use Dataflow with a custom template for the transformation logic.
D. Use Dataproc to run the transformations on a cluster.

Answer: D

NEW QUESTION # 51
You recently inherited a task for managing Dataflow streaming pipelines in your organization and noticed that proper access had not been provisioned to you. You need to request a Google-provided IAM role so you can restart the pipelines. You need to follow the principle of least privilege. What should you do?

A. Request the Dataflow Developer role.
B. Request the Dataflow Viewer role.
C. Request the Dataflow Admin role.
D. Request the Dataflow Worker role.

Answer: A

NEW QUESTION # 52
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 the Dataflow job monitoring interface to visually inspect the pipeline graph, check for errors, and configure notifications when critical errors occur.
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 Cloud Logging to view the pipeline logs and check for errors. Set up alerts based on specific keywords in the logs.

Answer: B

NEW QUESTION # 53
Your company's customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files' metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?

A. Create a native table.
B. Create an external table.
C. Create an object table.
D. Create a temporary table.

Answer: C

NEW QUESTION # 54
Your company has an on-premises file server with 5 TB of data that needs to be migrated to Google Cloud.
The network operations team has mandated that you can only use up to 250 Mbps of the total available bandwidth for the migration. You need to perform an online migration to Cloud Storage. What should you do?

A. Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google Cloud.
B. Use Storage Transfer Service to configure an agent-based transfer. Set the appropriate bandwidth limit for the agent pool.
C. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the --no- clobber option.
D. Use the gcloud storage cp command to copy all files from on- premises to Cloud Storage using the -- daisy-chain option.

Answer: B

NEW QUESTION # 55
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