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Google ADP Exam Syllabus Topics:

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

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Google Associate Data Practitioner Sample Questions (Q26-Q31):

NEW QUESTION # 26
Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards.
You need to implement a solution quickly and efficiently. What should you do?

A. Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
B. Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
C. Apply a filter to only show products with a positive profit margin.
D. Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.

Answer: A

NEW QUESTION # 27
You created a curated dataset of market trends in BigQuery that you want to share with multiple external partners. You want to control the rows and columns that each partner has access to. You want to follow Google-recommended practices. What should you do?

A. Create a separate project for each partner and copy the dataset into each project. Publish each dataset in Analytics Hub. Grant dataset-level access to each partner by using subscriptions.
B. Publish the dataset in Analytics Hub. Grant dataset-level access to each partner by using subscriptions.
C. Grant each partner read access to the BigQuery dataset by using 1AM roles.
D. Create a separate Cloud Storage bucket for each partner. Export the dataset to each bucket and assign each partner to their respective bucket. Grant bucket-level access by using 1AM roles.

Answer: B

NEW QUESTION # 28
Your company is building a near real-time streaming pipeline to process JSON telemetry data from small appliances. You need to process messages arriving at a Pub/Sub topic, capitalize letters in the serial number field, and write results to BigQuery. You want to use a managed service and write a minimal amount of code for underlying transformations. What should you do?

A. Use a Pub/Sub to Cloud Storage subscription, write a Cloud Run service that is triggered when objects arrive in the bucket, performs the transformations, and writes the results to BigQuery.
B. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write the results to BigQuery.
C. Use a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
D. Use a Pub/Sub to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.

Answer: B

NEW QUESTION # 29
Your organization plans to move their on-premises environment to Google Cloud. Your organization's network bandwidth is less than 1 Gbps. You need to move over 500 ## of data to Cloud Storage securely, and only have a few days to move the dat a. What should you do?

A. Request multiple Transfer Appliances, copy the data to the appliances, and ship the appliances back to Google Cloud to upload the data to Cloud Storage.
B. Connect to Google Cloud using VPN. Use Storage Transfer Service to move the data to Cloud Storage.
C. Connect to Google Cloud using VPN. Use the gcloud storage command to move the data to Cloud Storage.
D. Connect to Google Cloud using Dedicated Interconnect. Use the gcloud storage command to move the data to Cloud Storage.

Answer: A

NEW QUESTION # 30
Your organization uses Dataflow pipelines to process real-time financial transactions. You discover that one of your Dataflow jobs has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Create a custom script to periodically poll the Dataflow API for job status updates, and send email alerts if any errors are identified.
B. Use the gcloud CLI tool to retrieve job metrics and logs, and analyze them for errors and performance bottlenecks.
C. Navigate to the Dataflow Jobs page in the Google Cloud console. Use the job logs and worker logs to identify the error.
D. Set up a Cloud Monitoring dashboard to track key Dataflow metrics, such as data throughput, error rates, and resource utilization.

Answer: C

NEW QUESTION # 31
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