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Google Associate Data Practitioner Sample Questions:

1. You need to design a data pipeline to process large volumes of raw server log data stored in Cloud Storage.
The data needs to be cleaned, transformed, and aggregated before being loaded into BigQuery for analysis.
The transformation involves complex data manipulation using Spark scripts that your team developed. You need to implement a solution that leverages your team's existing skillset, processes data at scale, and minimizes cost. What should you do?

A) Use Dataflow with a custom template for the transformation logic.
B) Use Dataform to define the transformations in SQLX.
C) Use Dataproc to run the transformations on a cluster.
D) Use Cloud Data Fusion to visually design and manage the pipeline.

2. 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 separate Looker dashboards for each regional manager. Set the default dashboard filter to the corresponding region for each manager.
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 asales_regionuser attribute, and assign each manager's region as the value of their user attribute.

3. You need to transfer approximately 300 TB of data from your company's on-premises data center to Cloud Storage. You have 100 Mbps internet bandwidth, and the transfer needs to be completed as quickly as possible. What should you do?

A) Use the gcloud storage command to transfer the data over the internet.
B) Request a Transfer Appliance, copy the data to the appliance, and ship it back to Google.
C) Use Cloud Client Libraries to transfer the data over the internet.
D) Compress the data, upload it to multiple cloud storage providers, and then transfer the data to CloudStorage.

4. Your organization has highly sensitive data that gets updated once a day and is stored across multiple datasets in BigQuery. You need to provide a new data analyst access to query specific data in BigQuery while preventing access to sensitive dat a. What should you do?

A) Grant the data analyst the BigQuery Job User IAM role in the Google Cloud project.
B) Create a new Google Cloud project, and copy the limited data into a BigQuery table. Grant the data analyst the BigQuery Data Owner IAM role in the new Google Cloud project.
C) Create a materialized view with the limited data in a new dataset. Grant the data analyst BigQuery Data Viewer IAM role in the dataset and the BigQuery Job User IAM role in the Google Cloud project.
D) Grant the data analyst the BigQuery Data Viewer IAM role in the Google Cloud project.

5. Your company uses Looker as its primary business intelligence platform. You want to use LookML to visualize the profit margin for each of your company's products in your Looker Explores and dashboards.
You need to implement a solution quickly and efficiently. What should you do?

A) Create a new dimension that categorizes products based on their profit margin ranges (e.g., high, medium, low).
B) Define a new measure that calculates the profit margin by using the existing revenue and cost fields.
C) Create a derived table that pre-calculates the profit margin for each product, and include it in the Looker model.
D) Apply a filter to only show products with a positive profit margin.

Solutions: