Agile Data Warehouse Design

Visual BI Requirements Gathering and Collaborative Dimensional Modeling Workshop

A 3-day workshop presented by international data warehousing (DW) expert and author Lawrence Corr, covering the latest agile techniques for systematically gathering Business Intelligence (BI) requirements and designing effective DW/BI systems.


Agile techniques emphasise the early and frequent delivery of working software, stakeholder collaboration, responsiveness to change and waste elimination. They have revolutionised application development and are increasingly being adopted by DW/BI teams. This course provides practical tools and techniques for applying agility to the design of DW/BI database schemas – the earliest needed and most important working software for BI.

Who should attend?

  • Business and IT professionals who want to develop better BI solutions faster.
  • Business analysts, scrum masters, data modelers/architects, DBA’s and application developers, new to DW/BI, will benefit from the solid grounding in dimensional modeling provided.
  • Experienced DW/BI practitioners will find the course updates their hard-earned industry knowledge with the latest ideas on agile modeling, data warehouse design patterns and business model innovation.

Workshop Outline

Day 1: Modelstorming – Agile BI Requirements Gathering

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

    Dimensional Modelstorming Tools
  • Data stories, themes and BEAM tables: modeling BI data requirements by example
  • Timelines: modeling time and process measurement
  • Change stories: capturing historical reporting requirements (slowly changing dimension business rules)
  • Storyboarding the data warehouse design: matrix planning and estimating for agile BI development
  • The Business Model Canvas: aligning DW/BI design with business model definition and innovation
  • The BI Model Canvas: a systematic approach to star schema design

Day 2: Agile Star Schema Design

    Star Schema Design
  • Test-driven design: agile/lean 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 (minimum viable) DW documentation: enhanced star schemas, BEAM short codes, DW matrix

    How Many: Designing facts, measures and KPIs
  • Fact types: transactions, periodic snapshots, accumulating snapshots
  • Fact additivity: additive, semi-additive and non-additive measures
  • Fact performance and usability: indexing, partitioning, aggregating and consolidating facts

Day 3: Dimensional Design Patterns

    Who & What dimension patterns: customers, employees, products and services
  • Large populations with rapidly changing dimensional attributes: mini-dimensions and 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 and services, diverse attribution, ragged hierarchies
  • Product and service decomposition: component (bill of materials) and product unbundling analysis

    When & Where dimension patterns: dates, times and locations
  • Flexible date handling, ad-hoc date ranges and year-to-date analysis
  • Modeling time as dimensions and facts
  • Multinational BI: national languages reporting, multiple currencies, time zones and national calendars
  • Understanding journeys and trajectories: modeling events with multiple geographies

    Why & How dimension patterns: 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

Dates: May 27th, 28th & 29th

Venue: Microsoft Envisioning Centre, Microsoft Building 3

Cost: €1,799 (Early Bird until February 28th 2013 €1,500)

For further information contact: or call 01 2933883

Register Now


  • Lawrence Corr

    Lawrence Corr

    Lawrence Corr is a leading data warehouse designer, author and highly experienced educator who has worked in Europe, North America, the Middle East and South Africa developing and reviewing BI solutions for healthcare, telecoms, engineering, broadcasting, financial services and retail sectors. He specialises in helping organisations benefit from simpler, more inclusive DW/BI design techniques.

    He is the author of the bestselling Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema (an #1 bestseller in data warehousing) and a past contributor to Ralph Kimball articles and design tips.

  • Lawrence Corr

    Attendees receive a course workbook, BEAM agile dimensional modeling reference card and a copy of ‘Agile Data Warehouse Design’ (DecisionOne Press, 2011) by Lawrence Corr and Jim Stagnitto.


  • Prodata SQL Centre of Excellence
  • Microsoft

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