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

What is Dynamic Data Masking (DDM)?

A method to obfuscate sensitive data on the fly.

A process to redact personal information from logs.

A tool to anonymize data for analytics purposes.

A technique to encrypt sensitive data at rest.

2 / 20

What is the role of a masking policy in DDM?

To determine which users can access the masked data.

All options are correct

To specify the columns and rows to be masked.

To define the specific masking functions to apply.

3 / 20

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

False

True

4 / 20

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

By modifying the table or view definition.

By configuring the Snowflake security policies.

By creating a masked view.

By granting specific privileges to users.

5 / 20

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

True

False

6 / 20

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

All options are correct

By querying the masked data and verifying the masked values.

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

By using a vulnerability scanner to identify potential security risks.

7 / 20

How can you define a masking policy in Snowflake?

Using the ALTER TABLE statement.

Configuring the user roles and privileges.

Modifying the table definition.

Using the CREATE MASKING POLICY statement.

8 / 20

DDM can be used to mask data based on user roles and privileges.

False

True

9 / 20

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

False

True

10 / 20

How does DDM work in Snowflake?

By creating a separate masked view of the data.

By applying masking policies to specific columns and rows.

By using a combination of encryption and tokenization.

By encrypting the sensitive columns in the underlying tables.

11 / 20

What are the different masking functions available in Snowflake?

Hashing, salting, and key stretching.

Masking, obfuscation, and encryption.

Hashing, masking, and tokenization.

Masking, redaction, and anonymization.

12 / 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 is a materialized view.

A masked view is encrypted at rest.

A masked view is only accessible to specific users.

A masked view applies masking policies to the underlying data.

13 / 20

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

True

False

14 / 20

DDM can be used to mask data based on specific conditions.

False

True

15 / 20

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

False

True

16 / 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;

17 / 20

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

True

False

18 / 20

DDM can be applied to both tables and views.

False

True

19 / 20

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

False

True

20 / 20

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

False

True

Your score is

The average score is 53%

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.