Data Analysis with Multidimensional Modelling

Course Description

This SkillDynamo course develops practical, role-relevant capability in designing multidimensional analytical models with dimensions, cubes, measures, hierarchies, calculations, processing, security, performance, and business reporting. The learning path progresses from essential concepts and planning to implementation, validation, troubleshooting, and operational use.

Learners work through realistic scenarios, guided demonstrations, applied exercises, and evidence-based reviews. Every topic is connected to workplace responsibilities, common risks, quality controls, and measurable outcomes.

The course helps professionals make informed decisions, identify failure points, communicate results, and create an actionable improvement plan for future projects.

What You Will Learn

• Explain multidimensional architecture, source systems, data-source views, cubes, dimensions, measures, processing, and client tools
• Translate business questions into grain, facts, dimensions, attributes, relationships, hierarchies, and aggregation requirements
• Create cube structures, measure groups, dimensions, keys, attribute relationships, hierarchies, partitions, and perspectives
• Configure aggregation behavior, calculations, time dimensions, currency, many-to-many relationships, and business semantics
• Build calculated members, named sets, KPIs, actions, translations, and MDX queries for analytical use cases
• Apply roles, dimension security, cell security, permissions, sensitive-data controls, and user testing
• Process models, manage partitions, deploy changes, validate totals, monitor failures, and troubleshoot data issues
• Tune aggregations, storage modes, queries, caches, processing windows, capacity, documentation, and support

SkillDynamo Training Approach

SkillDynamo delivers this course through demonstrations, hands-on exercises, scenario analysis, validation checklists, structured troubleshooting, solution reviews, and a final improvement plan. Learners repeatedly practice planning, implementation, evidence collection, testing, correction, and communication so the skills transfer confidently into real workplace situations.