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Dynamic Data Masking

Dynamic Data Masking Dynamic data masking feature that Microsoft implemented in SQL Server 2016 version. Dynamic data masking (DDM) limits sensitive data exposure by masking it to non-privileged users. It can be used to greatly simplify the design and coding of security in your application. Dynamic data masking helps prevent unauthorized access to sensitive data by enabling customers to specify how much sensitive data to reveal with minimal impact on the application layer. DDM can be configured on designated database fields to hide sensitive data in the result sets of queries. With DDM the data in the database is not changed. DDM is easy to use with existing applications, since masking rules are applied in the query results. Many applications can mask sensitive data without modifying existing queries. A central data masking policy acts directly on sensitive fields in the database. Designate privileged users or roles that do have access to the sensitive data. DDM...
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How to delete existing embed code in Power BI Services

Navigate to settings Select mange embed codes under settings as shown in bellow   Click on delete icon to delete embed code from Power BI services

How to revoke publish to web permission in Power BI Services

Navigate to Settings > Admin Portal Click on Tenant Settings Go to export and sharing settings section as shown in bellow   Navigate to Publish web section Select only allow existing codes Navigate to settings Select mange embed codes under settings as shown in bellow Embed codes are not showing in mange embed codes page

Incremental refresh in Power BI

Incremental refresh and real-time data for semantic models in Power BI provide efficient ways to handle dynamic data and improve model refresh performance. By automating partition creation and management, incremental refresh reduces the amount of data that needs to be refreshed and allows for the inclusion of real-time data. Incremental refresh extends scheduled refresh operations by providing automated partition creation and management for semantic model tables that frequently load new and updated data. For most models, one or more tables contain transaction data that changes often and can grow exponentially, like a fact table in a relational or star database schema. An incremental refresh policy to partition the table, refreshing only the most recent import partitions, and optionally using another DirectQuery partition for real-time data can significantly reduce the amount of data that has to be refreshed. At the same time, this policy ensures that the latest changes at the data so...