SQL-Server Users Group-Costa Rica

Transcripción

1 SQL-Server Users Group-Costa Rica

2 Expositores Víctor Zúñiga Lobo Microsoft MVP en SQL-Server. Consultor especialista en soluciones de Inteligencia de Negocios durante 12 años, con amplio dominio de Tecnologías de DataWareHouse y Cubos multidimensionales de información así como de Balanced ScoreCard, Reportería avanzada y minería de datos. Experiencia como líder de departamento de consultoría Regional y cómo profesor en cursos de especialización de BI (8 años). Con proyectos exitosos desarrollados en 9 países, y sobre tecnología Microsoft (SQL Server 2000,2005,2008, 2008 R2, 2012 y 2014), Oracle 10G, Cognos y BO. Actualmente cuenta con la certificación SQL Server 2008, Business Intelligence Development and Maintenance Carlos Rojas Vargas Microsoft MVP en SQL-Server desde el año 2001 y trabaja con SQL-Server desde el año En este momento entre otras cuenta con las certificaciones MCSA(SQL-Server 2012), MCSA(SQL-Server 2008), MCITPro (Database Administrator SQL-Server 2008), MCTS(Sharepoint 2010), MCTS(SQL-Server 2008), MCTS(SQL Server 2008, Business Intelligence Development and Maintenance), MCITPro (SQL-Server 2005), MCTS(SQL-Server 2005), MCDBA, MCSD.NET, MCAD, MCSE, MCSA, MCDST, MCT, A+, N+, IC3 y CIW-CI. Fundador del Grupo de Usuarios de SQL-Server de Costa Rica( Participó como Expositor en el Primer, Tercer y Sétimo Simposio Latinoamericano de Sharepoint y como Expositor en los SQL-Saturday patrocinados por PASS. Fuera de Costa Rica ha impartido capacitación de SQL-Server y Visual Studio en Honduras, Nicaragua, Panamá y México.

3 Professional Association for SQL Server PASS Spanish Virtual Chapter

4 SQL-Server 2016 Dynamic Data Masking

5 Dynamic Data Masking Prevent abuse of sensitive data by hiding it from users Configuration made easy in new Azure portal Policy-driven at table and column level for defined set of users Table.CreditCardNo Dynamic Data Masking applied in real time to query results based on policy SQL Database SQL Server 2016 Real-time data masking; partial masking Multiple masking functions available (full, partial) for various sensitive data categories (like credit card numbers, SSN)

6 Dynamic Data Masking Types

7 Benefits of Dynamic Data Masking Regulatory compliance Strong demand for applications to meet privacy standards recommended by regulating authorities Sensitive data protection Protection against unauthorized access to sensitive data in application, and against exposure to developers or DBAs who need access to production database Agility and transparency Data is masked anytime, anywhere, with underlying data in database remaining intact Transparent to application and applied according to user privilege maintenance and complexity Limit access to sensitive data by defining policies to obfuscate specific database fields, without affecting database integrity

8 Dynamic Data Masking walkthrough 1 ) Security officer defines dynamic data-masking policy in T-SQL over sensitive data in employee table 2 ) App user selects from employee table 3 ) Dynamic data-masking policy obfuscates sensitive data in query results BUSINESS APP BUSINESS APP ALTER TABLE [Employee] ALTER COLUMN [SocialSecurityNumber] ADD MASKED WITH (FUNCTION = SSN() ) ALTER TABLE [Employee] ALTER COLUMN [ ] ADD MASKED WITH (FUNCTION = () ) ALTER TABLE [Employee] ALTER COLUMN [Salary] ADD MASKED WITH (FUNCTION = RANDOM(1,20000) ) GRANT UNMASK to admin1 Security Officer SELECT [Name], [SocialSecurityNumber], [ ], [Salary] FROM [Employee] other login admin1 login

9 Dynamic Data Masking Limitations and restrictions A masking rule cannot be defined for the following column types: Encrypted columns (Always Encrypted) FILESTREAM COLUMN_SET For users without UNMASK permission, deprecated READTEXT, UPDATETEXT, and WRITETEXT statements do not function properly on a column configured for Dynamic Data Masking Source: Eladio Rincón presentation

10 SQL-Server 2016 Reporting Services