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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. You work for an ecommerce company that has a BigQuery dataset that contains customer purchase history, demographics, and website interactions. You need to build a machine learning (ML) model to predict which customers are most likely to make a purchase in the next month. You have limited engineering resources and need to minimize the ML expertise required for the solution. What should you do?

A) Use Vertex Al Workbench to develop a custom model for purchase prediction.
B) Export the data to Cloud Storage, and use AutoML Tables to build a classification model for purchase prediction.
C) Use Colab Enterprise to develop a custom model for purchase prediction.
D) Use BigQuery ML to create a logistic regression model for purchase prediction.

2. 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) Create a Cloud Run function that runs daily and deletes files older than seven days.
C) Configure a Cloud Storage lifecycle rule that automatically deletes objects older than seven days.
D) Set up a Cloud Scheduler job that invokes a weekly Cloud Run function to delete files older than seven days.

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

4. Your organization has decided to move their on-premises Apache Spark-based workload to Google Cloud.
You want to be able to manage the code without needing to provision and manage your own cluster. What should you do?

A) Migrate the Spark jobs to Dataproc on Compute Engine.
B) Configure a Google Kubernetes Engine cluster with Spark operators, and deploy the Spark jobs.
C) Migrate the Spark jobs to Dataproc Serverless.
D) Migrate the Spark jobs to Dataproc on Google Kubernetes Engine.

5. You are working with a large dataset of customer reviews stored in Cloud Storage. The dataset contains several inconsistencies, such as missing values, incorrect data types, and duplicate entries. You need toclean the data to ensure that it is accurate and consistent before using it for analysis. What should you do?

A) Use BigQuery to batch load the data into BigQuery. Use SQL for cleaning and analysis.
B) Use Storage Transfer Service to move the data to a different Cloud Storage bucket. Use event triggers to invoke Cloud Run functions to load the data into BigQuery. Use SQL for analysis.
C) Use Cloud Run functions to clean the data and load it into BigQuery. Use SQL for analysis.
D) Use the PythonOperator in Cloud Composer to clean the data and load it into BigQuery. Use SQL for analysis.

Solutions: