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

2. You need to design a data pipeline that ingests data from CSV, Avro, and Parquet files into Cloud Storage.
The data includes raw user input. You need to remove all malicious SQL injections before storing the data in BigQuery. Which data manipulation methodology should you choose?

A) ETL
B) EL
C) ELT
D) ETLT

3. Your organization is building a new application on Google Cloud. Several data files will need to be stored in Cloud Storage. Your organization has approved only two specific cloud regions where these data files can reside. You need to determine a Cloud Storage bucket strategy that includes automated high availability.
What should you do?

A) Create a multi-region bucket, and upload the files to this bucket.
B) Create a single-region bucket in each of the two regions, and use the gcloud storage command to replicate the data across the buckets in both regions.
C) Create a single-region bucket in each of the two regions, and use Storage Transfer Service to replicate the data across the buckets in both regions.
D) Create a dual-region bucket, and upload the files to this bucket.

4. Your company's customer support audio files are stored in a Cloud Storage bucket. You plan to analyze the audio files' metadata and file content within BigQuery to create inference by using BigQuery ML. You need to create a corresponding table in BigQuery that represents the bucket containing the audio files. What should you do?

A) Create an external table.
B) Create an object table.
C) Create a native table.
D) Create a temporary table.

5. Your company uses Looker to visualize and analyze sales dat
a. You need to create a dashboard that displays sales metrics, such as sales by region, product category, and time period. Each metric relies on its own set of attributes distributed across several tables. You need to provide users the ability to filter the data by specific sales representatives and view individual transactions. You want to follow the Google-recommended approach. What should you do?

A) Use BigQuery to create multiple materialized views, each focusing on a specific sales metric. Build the dashboard using these views.
B) Create a single Explore with all sales metrics. Build the dashboard using this Explore.
C) Use Looker's custom visualization capabilities to create a single visualization that displays all the sales metrics with filtering and drill-down functionality.
D) Create multiple Explores, each focusing on each sales metric. Link the Explores together in a dashboard using drill-down functionality.

Solutions: