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Agile Data Warehouse Design Masterclass with Lawrence Corr

4-6 March 2019

Join Lawrence Corr, author of the bestseller “Agile Data Warehouse Design” for a three-day BEAM✲ training workshop and data modelstorming masterclass covering the latest agile techniques for systematically gathering Business Intelligence (BI) requirements and designing effective DW/BI systems.

Read our blogs about what is BEAM*, and how it can help you.

Visual BI Requirements Gathering & Collaborative Dimensional Modeling

Discover how modelstorming (modeling + brainstorming) directly with business stakeholders overcomes the limitations of traditional BI requirements analysis and data modeling to create a shared data language across business and IT.

Over three days of engaging class room sessions, quizzes, games and team exercises, Lawrence will build on Kimball method, industry-standard dimensional modeling and go beyond the books to provide you with practical tools and techniques for BI data design.



  • Understand BI vs. APP requirements
  • Know the BI lifecycle
  • Learn a common BI-specific language
  • Handover without re-translation
  • Repeatable framework
  • Document the right level of detail


  • Requirements that look dimensional
  • Framework to ask clarification questions
  • Cumulative build (less rework)
  • Know the context of data requirements
  • Framework for prioritising needs
  • Better estimates of effort to deliver


  • Upfront input into the data model
  • Enable self-service BI
  • Build on others reports
  • Faster reporting based on dimensions
  • Learn how to gather BI requirements
  • Enable better communication with users

Course Overview

You will learn how to:

  • Model BI requirements with stakeholders using business-friendly tools and techniques
  • Rapidly translate BI data requirements into efficient, flexible data warehouse designs
  • Identify and solve common BI problems using dimensional design patterns
  • Plan, design and develop BI solutions incrementally with agility

Agile Dimensional Modeling Fundamentals

  • BI/DW design requirements, challenges and opportunities: the need for agility
  • Modeling for measurement: the case for dimensional modeling, star schemas, facts & dimensions
  • Modelstorming with BI stakeholders: the case for collaborative data modeling
  • Thinking dimensional using the 7Ws (who, what, when, where, how many, why & how)
  • Business Event Analysis and Modeling (BEAM✲): an agile approach to dimensional modeling

Dimensional Modelstorming Tools

  • Data Stories, Themes and BEAM✲ Tables: modeling detailed BI data requirements by example
  • Timelines: modeling process sequence measurement
  • Hierarchy Charts: modeling dimensional drill-downs and rollups
  • Change Stories: capturing historical data requirements (slowly changing dimension rules)
  • BEAM✲ Matrix: Storyboarding multiple business events planning and estimating for agile BI development
  • Business Model Canvas: aligning DW/BI design with business model definition, measurement and innovation
  • BEAM✲ (BI Model) Canvas: a systematic approach to BI & star schema design
  • Test-driven design: agile data profiling for validating and improving requirements models
  • Data warehouse reuse: identifying, defining and developing conformed dimensions and facts
  • Balancing ‘just enough design up front’ (JEDUF) and ‘just in time’ (JIT) data modeling
  • Designing flexible, high performance star schemas: maximising the benefits of surrogate keys
  • Refactoring star schemas: responding to change, dealing with data debt
  • Lean DW documentation: enhanced star schemas, Data Warehouse matrix
  • How Many: Designing facts, measures and KPIs
  • Fact table types: transactions, periodic snapshots, accumulating snapshots
  • Fact additivity: additive, semi-additive and non-additive measures

Who & What patterns for modeling customers, employees, products and services

  • Large populations with rapidly changing dimensional attributes: mini-dimensions & customer facts
  • Customer segmentation: business to business (B2B), business to consumer (B2C) dimensions
  • Recursive customer relationships and organisation structures: variable-depth hierarchy maps
  • Current and historical reporting perspectives: hybrid slowly changing dimensions
  • Mixed business models: heterogeneous products/services, diverse attribution, ragged hierarchies
  • Product and service decomposition: component (bill of materials) and product unbundling analysis

When & Where patterns for modeling dates, times and locations

  • Flexible date handling, ad-hoc date ranges and year-to-date analysis
  • Modeling time quantitatively and qualitively as dimensions and facts
  • Multinational BI: national languages reporting, multiple currencies, time zones & national calendars
  • Understanding journeys and trajectories: modeling event sequences with multiple geographies

Why & How patterns for modeling cause and effect

  • Causal factors: trigging events, referrals, promotions, weather and exception reason dimensions
  • Fact specific dimensions: transaction and event status descriptions
  • Multi-valued dimensions: bridge tables, weighting factors, impact and ‘correctly weighted’ analysis
  • Behaviour Tagging: modeling causation and outcome, dimensional overloading, step dimensions


NZD $4,200(+gst)

Early Bird Discount NZD $3,600 (+gst)


OptimalHQ, Level 4

139 The Terrace Wellington