Download Real Google ADP Practice Test Questions And Start Preparation

Getting the Associate Data Practitioner (ADP) certification exam is necessary in order to get a job in your desired tech company. Success in the Associate Data Practitioner certification exam gives you an edge over the others because you will have certified skills. The Associate Data Practitioner (ADP) certification exam badge will make a good impression on the interviewer. Most of the people planning to attempt the Associate Data Practitioner (ADP) exam are confused that how will they prepare and pass Associate Data Practitioner (ADP) exam with good grades.

Google ADP Exam Syllabus Topics:

Section	Weight	Objectives
Topic 1: Data Preparation and Ingestion	30%	- Data ingestion into Google Cloud services 1. Cloud Storage ingestion patterns 2. Streaming ingestion with Pub/Sub concepts
Topic 2: Data Management	25%	- Data governance and security 1. IAM and access control 2. Data lifecycle management - Storage and data organization 1. BigQuery datasets and tables management 2. Cloud Storage lifecycle policies
Topic 3: Data Analysis and Presentation	27%	- Querying and analyzing data 1. BigQuery SQL usage 2. Data aggregation and transformation - Data visualization 1. Looker / Looker Studio reporting
Topic 4: Data Pipeline Orchestration	18%	- Pipeline design and automation 1. Dataflow pipelines 2. Workflow orchestration concepts (e.g., Cloud Composer)

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

NEW QUESTION # 50
You are working with a small dataset in Cloud Storage that needs to be transformed and loaded into BigQuery for analysis. The transformation involves simple filtering and aggregation operations. You want to use the most efficient and cost-effective data manipulation approach. What should you do?

A. Use BigQuery's SQL capabilities to load the data from Cloud Storage, transform it, and store the results in a new BigQuery table.
B. Create a Cloud Data Fusion instance and visually design an ETL pipeline that reads data from Cloud Storage, transforms it using built-in transformations, and loads the results into BigQuery.
C. Use Dataproc to create an Apache Hadoop cluster, perform the ETL process using Apache Spark, and load the results into BigQuery.
D. Use Dataflow to perform the ETL process that reads the data from Cloud Storage, transforms it using Apache Beam, and writes the results to BigQuery.

Answer: A

NEW QUESTION # 51
You have created a LookML model and dashboard that shows daily sales metrics for five regional managers to use. You want to ensure that the regional managers can only see sales metrics specific to their region. You need an easy-to-implement solution. What should you do?

A. Add anaccess_filterExplore filter on theregion_namedimension by using thesales_regionuser attribute.
B. Create asales_regionuser attribute, and assign each manager's region as the value of their user attribute.
C. Create five different Explores with thesql_always_filterExplore filter applied on theregion_namedimension. Set eachregion_namevalue to the corresponding region for each manager.
D. Create separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.

Answer: B

NEW QUESTION # 52
You are a data analyst working with sensitive customer data in BigQuery. You need to ensure that only authorized personnel within your organization can query this data, while following the principle of least privilege. What should you do?

A. Encrypt the data by using customer-managed encryption keys (CMEK).
B. Update dataset privileges by using the SQL GRANT statement.
C. Enable access control by using IAM roles.
D. Export the data to Cloud Storage, and use signed URLs to authorize access.

Answer: C

NEW QUESTION # 53
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 push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.
B. 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.
C. Use the "Pub/Sub to BigQuery" Dataflow template with a UDF, and write 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: C

NEW QUESTION # 54
You are designing a BigQuery data warehouse with a team of experienced SQL developers. You need to recommend a cost- effective, fully-managed, serverless solution to build ELT processes with SQL pipelines.
Your solution must include source code control, environment parameterization, and data quality checks. What should you do?

A. Use Cloud Composer to orchestrate and run data workflows.
B. Use Dataproc to run MapReduce jobs for distributed data processing.
C. Use Dataform to build, orchestrate, and monitor the pipelines.
D. Use Cloud Data Fusion to visually design and manage the pipelines.

Answer: C

NEW QUESTION # 55
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