Agile Data Warehouse Design Workshop

Visual BI Requirements Gathering and Collaborative Dimensional Modeling Training

A 3-day course presented live online and in person internationally by leading data warehousing expert and author Lawrence Corr, covering the latest agile techniques for systematically gathering Business Intelligence (BI) requirements and designing effective DW/BI systems.

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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.

The course contrasts agile and non-agile DW/BI development and highlights the inherent failings of traditional BI requirements analysis and data modeling. Via class room sessions and team exercises attendees will discover how
modelstorming (modeling + brainstorming) data requirements directly with BI stakeholders overcomes these limitations.
 

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.
 
You will learn how to:
 ✲  Model BI requirements with BI stakeholders using inclusive tools and visual thinking techniques
   Rapidly translate BI requirements into efficient, flexible data warehouse designs
 ✲  Identify and solve common BI problems – before they occur – using dimensional design patterns
   Plan, design and incrementally develop BI solutions with agility
 
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 & dimensions
   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 BI data requirements by example
   Timelines: modeling time and process measurement
   Hierarchy charts: modeling dimensional drill-downs and rollups
 ✲  Change stories: capturing historical reporting requirements (slowly changing dimension 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 BI & 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, DW matrix
 
 How Much/How Many: Designing facts, measures and KPIs (Key Performance Indicators)
   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 & 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 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 & 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

 
Material
Attendees receive a course workbook, BEAM agile dimensional modeling reference card and a copy of Agile Data Warehouse Design by Lawrence Corr and Jim Stagnitto.

Where and When Next
Our next public course will be in Utrecht, 7-9 November 2022

What Next

View our full public training schedule for 2022/23 or contact us via the email link below to private team training and workshops.