Modeling a Business Intelligence System

Reference : BI-MOD-05

Price : Contact us

Level & Prerequisites :

Duration : 2 days

  • Basic understanding of databases and data concepts

  • Familiarity with Business Intelligence principles is recommended

Description

This course provides a practical and structured approach to modeling Business Intelligence (BI) systems. Participants will learn how to design robust data models that support analytics, reporting, and decision‑making across the organization. The training covers conceptual, logical, and physical modeling, with a strong focus on dimensional modeling techniques widely used in modern BI environments. Through hands‑on exercises and real‑world examples, learners will gain the skills needed to build efficient, scalable, and business‑oriented BI models.

Public

  • BI developers and data modelers

  • Data analysts and business analysts

  • Data engineers and ETL developers

  • IT architects and technical project managers

  • Anyone involved in designing or maintaining BI systems

Course objectives

  • Understand the principles and purpose of BI system modeling.

  • Distinguish between conceptual, logical, and physical data models.

  • Apply dimensional modeling techniques (star schema, snowflake schema).

  • Identify and design fact tables, dimension tables, and hierarchies.

  • Model data to support KPIs, dashboards, and analytical queries.

  • Understand normalization vs. denormalization in BI contexts.

  • Evaluate modeling choices based on performance, scalability, and business needs.

  • Implement best practices for building maintainable BI models.

Content

  • Module 1 — Introduction to BI Modeling

  • Module 2 — Dimensional Modeling Fundamentals

  • Module 3 — Designing Fact Tables

  • Module 4 — Designing Dimension Tables

  • Module 5 — Advanced Modeling Techniques

  • Module 6 — Performance & Optimization

  • Module 7 — Modeling for Modern BI Architectures

  • Module 8 — Practical Workshops

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Concept and Architecture of Business Intelligence Systems