Microsoft SQL Server Practice Exam

Microsoft SQL Server Practice Exam

Microsoft SQL Server is a RDBMS (relational database management) software from Microsoft. It is used to store, retrieve, and manage data as well as provide high-performance solutions with analytics, in-memory capabilities, and integration services, as needed by enterprise applications.

Certification in Microsoft SQL Server attests to your skills and knowledge in using SQL Server databases. This certification assess you in SQL Server database administration, development, and analytics.
Why is Microsoft SQL Server certification important?

• Demonstrates proficiency in SQL Server features and tools.
• Enhances credibility and professional recognition.
• Opens doors to advanced career opportunities in database management and analytics.
• Keeps professionals updated on the latest SQL Server advancements.
• Increases employability in competitive job markets.
• Provides a structured learning path to mastering SQL Server.

Who should take the Microsoft SQL Server Exam?

• Database Administrators
• Database Developers
• Data Analysts
• Business Intelligence Developers
• System Engineers
• Data Architects

Skills Evaluated

Candidates taking the certification exam on the Microsoft SQL Server is evaluated for the following skills:

• Database installation, configuration, and management
• SQL queries
• Security
• Permissions
• Backup and recovery
  
• Monitoring and tuning performance
• Business intelligence
• Reports
• Data warehouses
  
• Big data analytics

Microsoft SQL Server Certification Course Outline
The course outline for Microsoft SQL Server certification is as below -

• Database concepts and design principles
• Data types and normalization

• SELECT, INSERT, UPDATE, DELETE operations
• Joins, subqueries, and window functions

• Installation and configuration
• Backup and recovery strategies
• Security management

• Query performance tuning
• Index management
• Resource monitoring

• Data transformation using SSIS
• Report generation using SSRS
• Data modeling for BI

• Managing data warehouses
• Using PolyBase for data integration

• Machine learning integration
• Predictive analytics with SQL

• SQL Server on Azure
• Hybrid database solutions