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Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Analysis and Presentation	27%	- Data visualization and reporting 1. Visualization best practices 2. Looker dashboards and reports - Data exploration and analysis 1. Jupyter notebooks for analysis 2. Identify trends, patterns, insights 3. BigQuery SQL queries - Business intelligence and decision support 1. Communicate findings effectively 2. Answer business questions with data
Topic 2: Data Preparation and Ingestion	30%	- Data loading methods 1. Batch and streaming ingestion 2. gcloud, BQ CLI, client libraries - Data extraction and transfer tools 1. Cloud Data Fusion, Storage Transfer Service 2. Dataflow, BigQuery Data Transfer Service, Database Migration Service - Storage solutions selection 1. Cloud Storage, BigQuery, Cloud SQL, Firestore, Bigtable, Spanner 2. Storage location types: regional, dual-regional, multi-regional, zonal - Data formats and classification 1. Formats: CSV, JSON, Parquet, Avro, database tables 2. Structured, semi-structured, unstructured data
Topic 3: Data Pipeline Orchestration	18%	- Data transformation concepts 1. ETL vs ELT processes 2. Data transformation requirements - 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
Topic 4: Data Management and Governance	25%	- Compliance and governance 1. Data stewardship and cataloging 2. Data privacy and regulatory requirements - Data security and access control 1. IAM roles and permissions 2. Data encryption and protection - Data quality and maintenance 1. Data lifecycle management 2. Data validation and cleaning

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Google Associate Data Practitioner ADP Prüfungsfragen mit Lösungen (Q39-Q44):

39. Frage
Your company currently uses an on-premises network file system (NFS) and is migrating data to Google Cloud. You want to be able to control how much bandwidth is used by the data migration while capturing detailed reporting on the migration status. What should you do?

A. Use Cloud Storage FUSE.
B. Use Storage Transfer Service.
C. Use a Transfer Appliance.
D. Use gcloud storage commands.

Antwort: B

40. Frage
You manage a Cloud Storage bucket that stores temporary files created during data processing. These temporary files are only needed for seven days, after which they are no longer needed. To reduce storage costs and keep your bucket organized, you want to automatically delete these files once they are older than seven days. What should you do?

A. Develop a batch process using Dataflow that runs weekly and deletes files based on their age.
B. Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
C. Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.
D. Create a Cloud Run function that runs daily and deletes files older than seven days.

Antwort: B

41. Frage
Your organization uses scheduled queries to perform transformations on data stored in BigQuery. You discover that one of your scheduled queries has failed. You need to troubleshoot the issue as quickly as possible. What should you do?

A. Request access from your admin to the BigQuery information_schema. Query the jobs view with the failed job ID, and analyze error details.
B. Navigate to the Logs Explorer page in Cloud Logging. Use filters to find the failed job, and analyze the error details.
C. Set up a log sink using the gcloud CLI to export BigQuery audit logs to BigQuery. Query those logs to identify the error associated with the failed job I
D. Navigate to the Scheduled queries page in the Google Cloud console. Select the failed job, and analyze the error details.

Antwort: D

42. Frage
Your company wants to implement a data transformation (ETL) pipeline for their BigQuery data warehouse.
You need to identify a managed transformation solution that allows users to develop with SQL and JavaScript, has version control, allows for modular code, and has data quality checks. What should you do?

A. Create a Cloud Composer environment, and orchestrate the transformations by using the BigQueryinsertJob operator.
B. Use Dataform to define the transformations in SQLX.
C. Use Dataproc to create an Apache Spark cluster and implement the transformations by using PySpark SQL.
D. Create BigQuery scheduled queries to define the transformations in SQL.

Antwort: B

43. Frage
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 a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
C. Use a Pub/Sub to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.
D. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write the results to BigQuery.

Antwort: D

44. Frage
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