Google ADP : Associate Data Practitioner

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Google ADP Exam Syllabus Topics:

Google Associate Data Practitioner Sample Questions:

1. 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) Enable access control by using IAM roles.
C) Update dataset privileges by using the SQL GRANT statement.
D) Export the data to Cloud Storage, and use signed URLs to authorize access.

2. You need to create a new data pipeline. You want a serverless solution that meets the following requirements:
* Data is streamed from Pub/Sub and is processed in real-time.
* Data is transformed before being stored.
* Data is stored in a location that will allow it to be analyzed with SQL using Looker.
Which Google Cloud services should you recommend for the pipeline?

A) Dataflow BigQuery
B) Cloud Composer Cloud SQL for MySQL
C) Dataproc Serverless Bigtable
D) BigQuery Analytics Hub

3. Your data science team needs to collaboratively analyze a 25 TB BigQuery dataset to support the development of a machine learning model. You want to use Colab Enterprise notebooks while ensuring efficient data access and minimizing cost. What should you do?

A) Create a Dataproc cluster connected to a Colab Enterprise notebook, and use Spark to process the data in BigQuery.
B) Use BigQuery magic commands within a Colab Enterprise notebook to query and analyze the data.
C) Copy the BigQuery dataset to the local storage of the Colab Enterprise runtime, and analyze the data using Pandas.
D) Export the BigQuery dataset to Google Drive. Load the dataset into the Colab Enterprise notebook using Pandas.

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

5. 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 Dataproc to run the transformations on a cluster.
C) Use Cloud Data Fusion to visually design and manage the pipeline.
D) Use Dataform to define the transformations in SQLX.

Solutions: