Snowflake Dynamic Data Masking: Intermediate-Level Quiz

Dynamic Data Masking in Snowflake: Intermediate Quiz

This quiz tests your understanding of Dynamic Data Masking in Snowflake, an advanced data security feature that allows you to mask sensitive data on the fly. It covers a range of topics, from basic concepts to practical implementation.

1 / 20

How can you define a masking policy in Snowflake?

Using the CREATE MASKING POLICY statement.

Modifying the table definition.

Configuring the user roles and privileges.

Using the ALTER TABLE statement.

2 / 20

DDM can be used to mask data based on data usage patterns.

True

False

3 / 20

How can you apply a masking policy to a table or view?

By granting specific privileges to users.

By configuring the Snowflake security policies.

By modifying the table or view definition.

By creating a masked view.

4 / 20

You want to create a masking policy to mask the credit_card_number column in the orders table. The masking function should replace the first 12 digits with 'X' and keep the last 4 digits. Which of the following SQL statements would you use to create the masking policy?

CREATE MASKING POLICY credit_card_mask AS DEFAULT FUNCTION MASK_PARTIAL('X', 12, 4);

CREATE MASKING POLICY credit_card_mask AS DEFAULT FUNCTION MASK_ALL('X');

CREATE MASKING POLICY credit_card_mask AS DEFAULT FUNCTION MASK_HASH('SHA256');

CREATE MASKING POLICY credit_card_mask AS DEFAULT FUNCTION MASK_PARTIAL('X', 4, 12);

5 / 20

DDM can be used to mask data based on data retention policies.

True

False

6 / 20

How can you test the effectiveness of DDM in your Snowflake environment?

By reviewing the audit logs to track access to masked data.

By using a vulnerability scanner to identify potential security risks.

All options are correct

By querying the masked data and verifying the masked values.

7 / 20

DDM can be used to mask data based on IP address.

False

True

8 / 20

You have a table named customer_data with columns first_name, last_name, and ssn. You want to mask the ssncolumn using a masking function that replaces the digits with 'X'. Which of the following SQL statements would you use to create a masked view?

CREATE MASKED VIEW masked_customer_data AS SELECT first_name, last_name, ENCRYPT(ssn) AS masked_ssn FROM customer_data;

CREATE MASKED VIEW masked_customer_data AS SELECT first_name, last_name, MASK(ssn) AS masked_ssn FROM customer_data;

CREATE MASKED VIEW masked_customer_data AS SELECT first_name, last_name, TOKENIZE(ssn) AS masked_ssn FROM customer_data;

CREATE MASKED VIEW masked_customer_data AS SELECT first_name, last_name, HASH(ssn) AS masked_ssn FROM customer_data;

9 / 20

DDM can be used to mask data in stored procedures and functions.

False

True

10 / 20

DDM can be used to mask data in external tables.

False

True

11 / 20

How does DDM work in Snowflake?

By using a combination of encryption and tokenization.

By applying masking policies to specific columns and rows.

By encrypting the sensitive columns in the underlying tables.

By creating a separate masked view of the data.

12 / 20

DDM can be applied to both tables and views.

False

True

13 / 20

DDM can be used to mask data in semi-structured data formats like JSON and XML.

True

False

14 / 20

DDM can be used to mask data based on client applications.

True

False

15 / 20

DDM can be used to mask data based on time of day.

True

False

16 / 20

DDM can be used to mask data based on data lineage.

False

True

17 / 20

You have a view named sales_report that contains sensitive customer information. You want to restrict access to this view to only authorized users. Which of the following methods would you use to achieve this?

Create a role for authorized users and grant them access to the view.

Encrypt the view using a strong encryption algorithm.

Apply a row-level security policy to the view.

All of the options

18 / 20

What is the role of a masking policy in DDM?

To specify the columns and rows to be masked.

To define the specific masking functions to apply.

All options are correct

To determine which users can access the masked data.

19 / 20

What are the different masking functions available in Snowflake?

Hashing, masking, and tokenization.

Masking, obfuscation, and encryption.

Hashing, salting, and key stretching.

Masking, redaction, and anonymization.

20 / 20

DDM can be used to mask data based on data quality metrics.

False

True

Your score is

The average score is 0%

Are you confident in your Snowflake Dynamic Data Masking (DDM) skills? This intermediate-level quiz will challenge your knowledge of this powerful security feature.

With this quiz, you will grasp the fundamental principles of DDM, including its purpose, benefits, and limitations. In addition, it tests how to apply DDM to real-world scenarios, such as masking sensitive data in tables, views, and stored procedures.

Take this quiz to gauge your expertise and identify areas for improvement.

Good luck.