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Question 358 - Professional Data Engineer discussion

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You have one BigQuery dataset which includes customers' street addresses. You want to retrieve all occurrences of street addresses from the dataset. What should you do?

A.
Create a deep inspection job on each table in your dataset with Cloud Data Loss Prevention and create an inspection template that includes the STREET_ADDRESS infoType.
Answers
A.
Create a deep inspection job on each table in your dataset with Cloud Data Loss Prevention and create an inspection template that includes the STREET_ADDRESS infoType.
B.
Create a de-identification job in Cloud Data Loss Prevention and use the masking transformation.
Answers
B.
Create a de-identification job in Cloud Data Loss Prevention and use the masking transformation.
C.
Write a SQL query in BigQuery by using REGEXP_CONTAINS on all tables in your dataset to find rows where the word 'street' appears.
Answers
C.
Write a SQL query in BigQuery by using REGEXP_CONTAINS on all tables in your dataset to find rows where the word 'street' appears.
D.
Create a discovery scan configuration on your organization with Cloud Data Loss Prevention and create an inspection template that includes the STREET_ADDRESS infoType.
Answers
D.
Create a discovery scan configuration on your organization with Cloud Data Loss Prevention and create an inspection template that includes the STREET_ADDRESS infoType.
Suggested answer: A

Explanation:

To retrieve all occurrences of street addresses from a BigQuery dataset, the most effective and comprehensive method is to use Cloud Data Loss Prevention (DLP). Here's why option A is the best choice:

Cloud Data Loss Prevention (DLP):

Cloud DLP is designed to discover, classify, and protect sensitive information. It includes pre-defined infoTypes for various kinds of sensitive data, including street addresses.

Using Cloud DLP ensures thorough and accurate detection of street addresses based on advanced pattern recognition and contextual analysis.

Deep Inspection Job:

A deep inspection job allows you to scan entire tables for sensitive information.

By creating an inspection template that includes the STREET_ADDRESS infoType, you can ensure that all instances of street addresses are detected across your dataset.

Scalability and Accuracy:

Cloud DLP is scalable and can handle large datasets efficiently.

It provides a high level of accuracy in identifying sensitive data, reducing the risk of missing any occurrences.

Steps to Implement:

Set Up Cloud DLP:

Enable the Cloud DLP API in your Google Cloud project.

Create an Inspection Template:

Create an inspection template in Cloud DLP that includes the STREET_ADDRESS infoType.

Run Deep Inspection Jobs:

Create and run a deep inspection job for each table in your dataset using the inspection template.

Review the inspection job results to retrieve all occurrences of street addresses.

Cloud DLP Documentation

Creating Inspection Jobs

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asked 18/09/2024
Maxime SELLY
43 questions
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