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Grant different UNMASK permissions to users: --Grant column level UNMASK permission to ServiceAttendant Dynamic Data Masking is applied when running SQL Server Import and Export. A database containing masked columns results in an exported data file with masked data (assuming it's exported by a user without UNMASK privileges), and the imported database will contain statically masked data. Creating a mask on a column doesn't prevent updates to that column. So although users receive masked data when querying the masked column, the same users can update the data if they have write permissions. A proper access control policy should still be used to limit update permissions.

Users with CONTROL SERVER or CONTROL at the database level could view masked data in its original form. This includes admin users or roles such as sysadmin, serveradmin, db_owner etc.For string data types, use XXXX (or fewer) if the size of the field is fewer than 4 characters ( char, nchar, varchar, nvarchar, text, ntext). Dynamic data masking is designed to simplify application development by limiting data exposure in a set of predefined queries used by the application. While Dynamic Data Masking can also be useful to prevent accidental exposure of sensitive data when accessing a production database directly, it's important to note that unprivileged users with ad hoc query permissions can apply techniques to gain access to the actual data. If there's a need to grant such ad hoc access, Auditing should be used to monitor all database activity and mitigate this scenario. As an example, consider a database principal that has sufficient privileges to run ad hoc queries on the database, and tries to 'guess' the underlying data and ultimately infer the actual values. Assume that we have a mask defined on the [Employee].[Salary] column, and this user connects directly to the database and starts guessing values, eventually inferring the [Salary] value in the Employees table: SELECT ID, Name, Salary FROM Employees The following statement drops the mask on the LastName column created in the previous example: ALTER TABLE Data.Membership where the number in DiscountCode is random for every query result. Add or editing a mask on an existing column

Since the entire features of this free XNX Video Player app are available for free, there is no harm giving it a try and explore the features for yourself. Just open the video file you wish to watch and leave the rest to this powerful video player. Example definition syntax: Account_Number bigint MASKED WITH (FUNCTION = 'random([start range], [end range])')Using SELECT INTO or INSERT INTO to copy data from a masked column into another table results in masked data in the target table (assuming it's exported by a user without UNMASK privileges). You don't need any special permission to create a table with a dynamic data mask, only the standard CREATE TABLE and ALTER on schema permissions.

Grant read permissions to the users in the database: ALTER ROLE db_datareader ADD MEMBER ServiceAttendant;Masking method for column defined with data type datetime, datetime2, date, time, datetimeoffset, smalldatetime. It helps masking the year => datetime("Y"), month=> datetime("M") , day=>datetime("D"), hour=>datetime("h"), minute=>datetime("m"), or seconds=>datetime("s") portion of the day. Example of alter syntax: ALTER COLUMN [Phone Number] ADD MASKED WITH (FUNCTION = 'partial(1,"XXXXXXX",0)') SQL Server 2016 (13.x) and later Azure SQL Database Azure SQL Managed Instance Azure Synapse Analytics A random masking function for use on any numeric type to mask the original value with a random value within a specified range. If the original value is too short to complete the entire mask, part of the prefix or suffix isn't exposed.

Example definition syntax: FirstName varchar(100) MASKED WITH (FUNCTION = 'partial(prefix,[padding],suffix)') NULL The following example creates a table with three different types of dynamic data masks. The example populates the table, and selects to show the result. -- schema to contain user tablesA new user is created and granted the SELECT permission on the schema where the table resides. Queries executed as the MaskingTestUser view masked data. CREATE USER MaskingTestUser WITHOUT LOGIN; Masking method that exposes the first and last letters and adds a custom padding string in the middle. prefix,[padding],suffix The following example changes a masking function on the LastName column: ALTER TABLE Data.Membership For date and time data types, use 1900-01-01 00:00:00.0000000 ( date, datetime2, datetime, datetimeoffset, smalldatetime, time). For users without the UNMASK permission, the deprecated READTEXT, UPDATETEXT, and WRITETEXT statements don't function properly on a column configured for Dynamic Data Masking.