A famous fintech startup is setting up its data solution using Azure Synapse analytics.
As part of compliance, the details like credit card numbers shouldn't be exposed, while the frontline support should be able to verify the customer identity using the last 4 digits of the credit card.
Which of the following is best suited in this scenario?
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: D
A very common technique is used to hide PII or give access only to parts of it.
Data masking will help block access to specific fields of data.
In this case, the first 12 characters of credit card numbers can be masked, and the last four can be used for verification.
Option A is incorrect: Firewall block will completely block access to the database.
Option B is incorrect: It will help in limiting access to row only.
Option C is incorrect: It will help in limiting access to a particular column only.
Option D is correct: It is a storage option.
To know more, please refer to the docs below:
In this scenario, the fintech startup wants to ensure compliance and protect sensitive data, such as credit card numbers, while also providing a way for frontline support to verify customer identity using the last 4 digits of the credit card. To achieve this, the best solution would be data masking.
Data masking is a technique used to protect sensitive data by obscuring it with fake data or symbols. In this case, the full credit card number can be masked, while the last 4 digits can remain visible for customer identification purposes. This ensures that the sensitive data is not exposed to unauthorized personnel while still providing necessary information for customer identification.
Firewall rules to block IP addresses would not be effective in this scenario as the issue is with data access rather than network security. Row-level security and column-level security are both useful for limiting data access based on user permissions, but they do not address the need to protect sensitive data. Additionally, they may not be able to provide the necessary information for customer identification.
In summary, data masking is the best solution for this scenario as it protects sensitive data while still allowing for necessary customer identification.