Designing Business Intelligence Solutions with Microsoft SQL Server

Course Category : Data Management

A specialised programme on designing business intelligence solutions with Microsoft SQL Server to support enterprise reporting, analytics, and decision-making.
Duration: 5 Days | Level: Intermediate to Advanced.

Starts On

28 - September - 2026

Ends On

2 - October - 2026

Location

Spain - Madrid

Language

English

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Targeted Audience

  • Data and Business Intelligence Analysts
  • Database Developers
  • Data Warehousing and Data Engineering Professionals
  • SQL Server Administrators
  • IT and Information Systems Managers
  • Business Analysts and Technical Decision-Makers
  • Enterprise Reporting and Analytics Teams

Targeted Skills

  • Understanding BI solution architecture
  • Designing data warehouses and dimensional models
  • Analysing ETL processes using SSIS
  • Understanding analytical modelling with SSAS
  • Designing reports with SSRS and Power BI
  • Applying data quality and governance principles

Expected Outcomes

  • Understand the architecture of Microsoft SQL Server-based BI solutions.
  • Translate business requirements into analytical data models.
  • Design data warehouses based on dimensions and fact tables.
  • Understand the role of SSIS in data integration and ETL processes.
  • Evaluate the use of SSAS, SSRS, and Power BI in analytics and reporting.
  • Apply governance, quality, and security concepts within BI solutions.

Training Topics Index

  • Business intelligence concepts and decision-support role
  • Components of the Microsoft SQL Server BI environment
  • BI solution lifecycle
  • Operational versus analytical databases
  • Scalability and reliability principles

  • Data warehouse and data mart concepts
  • Fact and dimension table design
  • Star Schema and Snowflake Schema models
  • Keys and analytical relationships
  • Performance and data quality considerations

  • Extraction, transformation, and loading stages
  • Data flows and control flows
  • Error handling and data validation
  • Scheduling and monitoring integration packages
  • Documentation of data integration processes

  • Multidimensional and tabular model concepts
  • Measures and analytical indicators
  • Relationships and hierarchies
  • Performance considerations in analytical models
  • Analytical data access security

  • Enterprise reporting design with SSRS
  • Dashboard principles using Power BI
  • KPIs and analytical navigation
  • Report security and permission management
  • BI governance and solution sustainability