Microsoft DP-203 Practice Test - Questions Answers

A: You can classify columns manually, as an alternative or in addition to the recommendation-based classification:

Select Add classification in the top menu of the pane.

In the context window that opens, select the schema, table, and column that you want to classify, and the information type and sensitivity label. Select Add classification at the bottom of the context window.

C: An important aspect of the information-protection paradigm is the ability to monitor access to sensitive data. Azure SQL Auditing has been enhanced to include a new field in the audit log called data_sensitivity_information. This field logs the sensitivity classifications (labels) of the data that was returned by a query. Here's an example:

Reference:

https://docs.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview

SQL Database dynamic data masking limits sensitive data exposure by masking it to non-privileged users. The Credit card masking method exposes the last four digits of the designated fields and adds a constant string as a prefix in the form of a credit card. Example: XXXX-XXXX-XXXX-1234

Reference: https://docs.microsoft.com/en-us/azure/sql-database/sql-database-dynamic-data-masking-get-started

AC: Create security groups in Azure Active Directory. Assign users or security groups to Data Lake Storage Gen1 accounts. E: Assign users or security groups as ACLs to the Data Lake Storage Gen1 file system

Reference: https://docs.microsoft.com/en-us/azure/data-lake-store/data-lake-store-secure-data

Linked services are much like connection strings, which define the connection information needed for Data Factory to connect to external resources.

Incorrect Answers:

D: A self-hosted integration runtime copies data between an on-premises store and cloud storage.

Reference: https://docs.microsoft.com/en-us/azure/data-factory/enable-customer-managed-key https://docs.microsoft.com/en-us/azure/data-factory/concepts-linked-services https://docs.microsoft.com/en-us/azure/data-factory/create-self-hosted-integration-runtime

Data Discovery & Classification is built into Azure SQL Database, Azure SQL Managed Instance, and Azure Synapse Analytics. It provides basic capabilities for discovering, classifying, labeling, and reporting the sensitive data in your databases.

Your most sensitive data might include business, financial, healthcare, or personal information. Discovering and classifying this data can play a pivotal role in your organization's information-protection approach. It can serve as infrastructure for:

Helping to meet standards for data privacy and requirements for regulatory compliance. Various security scenarios, such as monitoring (auditing) access to sensitive data. Controlling access to and hardening the security of databases that contain highly sensitive data.

Reference:

https://docs.microsoft.com/en-us/azure/azure-sql/database/data-discovery-and-classification-overview

Azure SQL Database currently supports encryption at rest for Microsoft-managed service side and client-side encryption scenarios. Support for server encryption is currently provided through the SQL feature called Transparent Data Encryption. Client-side encryption of Azure SQL Database data is supported through the Always Encrypted feature.

Reference: https://docs.microsoft.com/en-us/azure/security/fundamentals/encryption-atrest

A replicated table has a full copy of the table available on every Compute node. Queries run fast on replicated tables since joins on replicated tables don't require data movement. Replication requires extra storage, though, and isn't practical for large tables.

Incorrect Answers:

A: A hash distributed table is designed to achieve high performance for queries on large tables. C: A round-robin table distributes table rows evenly across all distributions. The rows are distributed randomly. Loading data into a round-robin table is fast. Keep in mind that queries can require more data movement than the other distribution methods.

Reference:

https://docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-tables-overview

A: Row-Level Security (RLS) enables you to use group membership or execution context to control access to rows in a database table. Implement RLS by using the CREATE SECURITY POLICYTransact-SQL statement. B: Azure Synapse provides a comprehensive and fine-grained access control system, that integrates:

Azure roles for resource management and access to data in storage, Synapse roles for managing live access to code and execution, SQL roles for data plane access to data in SQL pools.

Reference: https://docs.microsoft.com/en-us/sql/relational-databases/security/row-level-security https://docs.microsoft.com/en-us/azure/synapse-analytics/security/synapse-workspace-access-control-overview