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

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

True

False

2 / 20

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

True

False

3 / 20

DDM can be used to mask data based on data sensitivity levels.

False

True

4 / 20

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

False

True

5 / 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, HASH(ssn) AS masked_ssn FROM customer_data;

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, TOKENIZE(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;

6 / 20

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

False

True

7 / 20

DDM can be used to mask data in external tables.

False

True

8 / 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', 4, 12);

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');

9 / 20

What is the difference between a masked view and a normal view?

A. A masked view applies masking policies to the underlying data.
B. A masked view is encrypted at rest.
C. A masked view is only accessible to specific users.
D. A masked view is a materialized view.

A masked view applies masking policies to the underlying data.

A masked view is a materialized view.

A masked view is only accessible to specific users.

A masked view is encrypted at rest.

10 / 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?

Apply a row-level security policy to the view.

All of the options

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

Encrypt the view using a strong encryption algorithm.

11 / 20

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

False

True

12 / 20

DDM can be applied to both tables and views.

False

True

13 / 20

DDM can be used to mask data in real-time.

False

True

14 / 20

How can you define a masking policy in Snowflake?

Modifying the table definition.

Using the ALTER TABLE statement.

Configuring the user roles and privileges.

Using the CREATE MASKING POLICY statement.

15 / 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.

16 / 20

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

False

True

17 / 20

What are some best practices for implementing DDM in Snowflake?

Regularly review and update masking policies.

Identify sensitive data and classify it appropriately.

All options are correct

Create granular masking policies to control access to sensitive data.

18 / 20

What is Dynamic Data Masking (DDM)?

A tool to anonymize data for analytics purposes.

A process to redact personal information from logs.

A method to obfuscate sensitive data on the fly.

A technique to encrypt sensitive data at rest.

19 / 20

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

All options are correct

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

By using a vulnerability scanner to identify potential security risks.

By querying the masked data and verifying the masked values.

20 / 20

How does DDM work in Snowflake?

By encrypting the sensitive columns in the underlying tables.

By creating a separate masked view of the data.

By using a combination of encryption and tokenization.

By applying masking policies to specific columns and rows.

Your score is

The average score is 66%

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.