Visual BI Requirements Gathering & Collaborative Dimensional Modeling Training
Join Lawrence Corr, author of the bestseller “Agile Data Warehouse Design” for a three-day BEAM✲ workshop and data modelstorming masterclass covering the latest agile techniques for systematically gathering Business Intelligence (BI) requirements and designing effective DW/BI systems.
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.
Who Should Attend
Business and IT professionals who want to jointly develop better BI solutions faster.
Business analysts, scrum masters, data modelers/architects, DBAs and application developers, new to DW/BI, will benefit from the solid grounding in dimensional modeling.
Experienced DW/BI practitioners will find the course updates their hard-earned industry knowledge with fresh ideas on agile modeling, data warehouse design patterns and business model alignment.
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
Day 1: Modelstorming – Agile BI Requirements Gathering
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
Day 2: Agile 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
Day 3: Dimensional Design Patterns
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
Lawrence Corr is a leading data warehouse designer, speaker, modelstormer and former Kimball University instructor with over 20 years’ experience in business intelligence. Lawrence has worked on DW/BI projects in Europe, USA, Middle East and Africa developing and reviewing data warehouses within healthcare, telecoms, broadcasting, higher education, financial services and retail. He is the co-author of Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema, an Amazon #1 bestseller in data warehousing and database design. His techniques are used by thousands of BI professionals worldwide.
What (will you get)
Attendees receive a course workbook, BEAM✲ agile dimensional modeling reference card, downloadable templates and a copy of Agile Data Warehouse Design (DecisionOne Press, 2011) by Lawrence Corr and Jim Stagnitto.
Lunch, teas and coffees will be provided each day