GCP-ADP Google Cloud Associate Data Practitioner Practice Questions
Prepare for GCP-ADP with more than an answer.
Unlock the full exam and previous versions
- v1Google Cloud Associate Data Practitioner 135 questions Current
- ADPLegacy Associate Data Practitioner 307 questions Locked
- Exam fee
- $125 USD
- Level
- Associate
- Valid for
- 3 years
Domains covered on the exam 4
- Data Preparation and Ingestion30%
- Data Analysis and Presentation27%
- Data Pipeline Orchestration18%
- Data Management25%
- 1
You need to automate a daily data transformation workflow. The workflow involves executing a SQL query in BigQuery, checking the results, and then triggering a Cloud Function if the data quality check passes. You prefer a serverless, low-code orchestration solution. Which service should you use?
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Correct answer: B
Cloud Workflows is a fully managed, serverless orchestration service that allows you to combine Google Cloud services and APIs. It is ideal for chaining steps like BigQuery jobs and Cloud Functions with conditional logic, without the overhead of managing an Airflow environment (Cloud Composer).
- 2
A global retail company wants to use machine learning to predict customer churn. They have petabytes of transaction data stored in BigQuery. The data science team is proficient in SQL but has limited experience with Python or R. Which solution allows them to build and deploy a churn prediction model directly within their data warehouse?
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Correct answer: B
BigQuery ML allows users to create and execute machine learning models in BigQuery using standard SQL queries. This democratizes ML by enabling data analysts who know SQL to build models without moving data or learning new languages like Python.
- 3
You are migrating an existing Hadoop and Spark workload from an on-premises cluster to Google Cloud. You want to minimize changes to the existing jobs and leverage a managed service that allows you to scale clusters up and down as needed. Which service is best suited for this migration?
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Correct answer: B
Cloud Dataproc is a fully managed and highly scalable service for running Apache Spark, Apache Hadoop, and other open-source tools. It is the lift-and-shift destination for existing Hadoop/Spark workloads, allowing you to use existing code with minimal changes while benefiting from cloud scaling.
- 4
A retail company collects clickstream data from its e-commerce website. The data is currently stored in on-premises servers as JSON files. You need to migrate this historical data (approximately 50 TB) to Google Cloud for analysis in BigQuery. The company has a limited network bandwidth of 100 Mbps and requires the data to be available in Google Cloud within one week. Which approach should you take?
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Correct answer: C
At 100 Mbps, uploading 50 TB of data would theoretically take over 46 days (50TB * 8000000 Mb / 100 Mbps / 60 / 60 / 24). This far exceeds the one-week requirement. The Transfer Appliance is a high-capacity storage server that you rent, fill with data on-premises, and ship to an ingestion center, which is the only viable option for this volume and bandwidth constraint.
- 5
You are designing a data ingestion pipeline for a financial services application. The application generates high-throughput transactional data that must be stored with strong consistency and high availability across a global user base. You need to select a storage solution that supports SQL queries and horizontal scalability. Which service should you choose?
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Correct answer: C
Cloud Spanner is a fully managed, mission-critical, relational database service that offers transactional consistency at a global scale, schemas, SQL (ANSI 2011 with extensions), and automatic, synchronous replication for high availability. Cloud SQL is regional and scales vertically. BigQuery is for analytics (OLAP), not transactional (OLTP) workloads.
- 6
You are building a data warehouse in BigQuery. You have a requirement to load daily batch files from Cloud Storage into BigQuery. The source data is in CSV format, but the schema of the files might evolve over time (e.g., new columns added). You want to ensure that the loading process handles these schema changes automatically without manual intervention. What should you do?
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Correct answer: A
While BigQuery supports schema updates for CSVs, Avro is the preferred format for handling schema evolution because the schema is embedded in the file itself. Using
ALLOW_FIELD_ADDITIONallows the load job to add new columns found in the source data to the destination table schema.
