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Google Associate-Data-Practitioner Exam Overview:
| Certification Vendor: | Google Cloud |
|---|---|
| Exam Name: | Google Cloud Certified - Associate Data Practitioner |
| Exam Number: | Associate Data Practitioner |
| Real Exam Qty: | 50-60 |
| Exam Format: | Multiple choice, Multiple select |
| Related Certifications: | Google Cloud Certified - Associate Data Practitioner |
| Available Languages: | Japanese, English |
| Certificate Validity Period: | 2 years |
| Exam Price: | $120 USD |
| Exam Duration: | 120 minutes |
| Passing Score: | Not publicly disclosed by Google Cloud |
| Sample Questions: | DOWNLOAD DEMO |
| Exam Way: | Online proctored exam or Onsite at a testing center |
| Pre Condition: | No formal prerequisites, but Google recommends hands-on experience with Google Cloud data services and foundational cloud knowledge. |
| Official Syllabus URL: | https://cloud.google.com/learn/certification/data-practitioner |
Google Associate-Data-Practitioner Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Topic 1: Data Preparation and Data Processing | - Ingesting data
|
| Topic 2: Data Analysis and Data Visualization | - Analyzing data
|
| Topic 3: Machine Learning | - Implementing ML solutions
|
| Topic 4: Data Management and Governance | - Data governance and quality
|
Google Cloud Associate Data Practitioner Exam: Common Questions Answered
The Google Cloud Associate Data Practitioner exam includes 50-60 questions and gives you 120 minutes to finish. That works out to a tight per-question pace, so flagging a hard item and moving on is usually smarter than getting stuck. Before test day, sit at least one full timed session with the PracticeVCE test engine — practicing under the clock is the fastest way to build the rhythm the real Associate-Data-Practitioner exam demands.
The Associate-Data-Practitioner exam is the official Google exam that leads to the Google Cloud Platform certification, positioned at the Associate level. It validates the skills employers expect from certified professionals, and passing it is a concrete step forward in an IT career. It is also connected with other credentials in the same track, including Google Cloud Certified - Associate Data Practitioner.
Yes. PracticeVCE offers a free PDF demo of the Google Cloud Associate Data Practitioner material, so you can check the question style and answer quality before paying. After purchase, your product includes 365 days of free updates; once that period expires, you can extend the update service at a 50% discount from your member zone.
The passing score for the Google Cloud Associate Data Practitioner exam is Not publicly disclosed by Google Cloud, and the official registration fee is $120 USD. Keep in mind that a failed attempt means paying the full fee again to retake it. A sensible approach is to test yourself first with PracticeVCE practice questions and only book your seat once your mock scores sit comfortably above Not publicly disclosed by Google Cloud.
The Google Cloud Associate Data Practitioner exam is organized into 4 domains. The main ones include Data Management and Governance; Data Preparation and Data Processing; Data Analysis and Data Visualization. Weightings tell you where to spend most of your study time, and the full topic breakdown is listed in the exam outline section above on this page.
If you take the Google Cloud Associate Data Practitioner exam within 60 days of your purchase and do not pass, you can apply for a full refund under the PracticeVCE refund policy. The claim requires a scanned enrollment slip and your official Score Report in PDF, submitted within 2 days after the exam; claims are processed within 7 days. Note that the guarantee applies only to the corresponding exam — attempts taken within 3 days of purchase, downloaded-but-never-taken exams, free materials, and expired orders are not covered, and the candidate name must match the payer name. Prefer new material instead of a refund? You can swap for two free exam products of equal value and keep the update service on your original purchase. As for delivery, everything is instant: the download link reaches your mailbox within one minute of payment (contact support if nothing arrives within 2 hours), and there is no limit on how many computers you can install it on.
No formal prerequisites, but Google recommends hands-on experience with Google Cloud data services and foundational cloud knowledge. Requirements like these can change, so before you book, confirm the current eligibility rules on the official page: https://cloud.google.com/learn/certification/data-practitioner.
Google Cloud Associate Data Practitioner Sample Questions:
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 the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write 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 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.
Correct Answer: A 🗳️
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Your organization stores highly personal data in BigQuery and needs to comply with strict data privacy regulations. You need to ensure that sensitive data values are rendered unreadable whenever an employee leaves the organization. What should you do?
- A. Use customer-managed encryption keys (CMEK) and delete keys when employees leave the organization.
- B. Use column-level access controls with policy tags and revoke viewer permissions when employees leave the organization.
- C. Use dynamic data masking and revoke viewer permissions when employees leave the organization.
- D. Use AEAD functions and delete keys when employees leave the organization.
Correct Answer: A 🗳️
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Your organization has decided to migrate their existing enterprise data warehouse to BigQuery. The existing data pipeline tools already support connectors to BigQuery. You need to identify a data migration approach that optimizes migration speed. What should you do?
- A. Use the BigQuery Data Transfer Service to recreate the data pipeline and migrate the data into BigQuery.
- B. Use the existing data pipeline tool's BigQuery connector to reconfigure the data mapping.
- C. Use the Cloud Data Fusion web interface to build data pipelines. Create a directed acyclic graph (DAG) that facilitates pipeline orchestration.
- D. Create a temporary file system to facilitate data transfer from the existing environment to Cloud Storage. Use Storage Transfer Service to migrate the data into BigQuery.
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
Your organization uses a BigQuery table that is partitioned by ingestion time. You need to remove data that is older than one year to reduce your organization's storage costs. You want to use the most efficient approach while minimizing cost. What should you do?
- A. Create a view that filters out rows that are older than one year.
- B. Set the table partition expiration period to one year using the ALTER TABLE statement in SQL.
- C. Require users to specify a partition filter using the alter table statement in SQL.
- D. Create a scheduled query that periodically runs an update statement in SQL that sets the "deleted" column to "yes" for data that is more than one year old. Create a view that filters out rows that have been marked deleted.
Correct Answer: B 🗳️
Explanation: Only visible for PracticeVCE members. You can sign-up / login (it's free).
You need to create a data pipeline for a new application. Your application will stream data that needs to be enriched and cleaned. Eventually, the data will be used to train machine learning models. You need to determine the appropriate data manipulation methodology and which Google Cloud services to use in this pipeline. What should you choose?
- A. ELT; Cloud SQL -> Analytics Hub
- B. ETL; Dataflow -> BigQuery
- C. ETL; Cloud Data Fusion -> Cloud Storage
- D. ELT; Cloud Storage -> Bigtable
Correct Answer: B 🗳️
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