• Mehr als ein Papiertiger

    Wie BI-Ziele im Detail erreicht werden und nachhaltigen Mehrwert erzielen.

    Mehr erfahren

  • Fit für dynamische und stürmische Zeiten

    Ein umfassendes Datawarehouse - basierend auf Microsoft SQL Server - versorgt das Management regelmässig mit den aktuellsten und handlungsrelevanten Informationen. 

    Mehr erfahren

  • Strukturiertes Assessment für ein kundenorientiertes SLA-Reporting

    Basierend auf dem IT-Logix BI-AuditTM hat die Swisscom konkrete Handlungsempfehlungen für eine effiziente und kundenorientierte Reporting-Umgebung erhalten.

    Mehr erfahren

  • Balanced Scorecard mit KPI

    Im Rahmen eines KPI-Projekts hat PWC die wichtigsten Kennzahlen in einer firmenweit gültigen Balanced Scorecard zusammengefasst. IT-Logix AG unterstützte PWC, diese Balanced Scorecard zu definieren, aufzubereiten und zu verteilen.

    Mehr erfahren

  • DWH-Lösung

    Damit aus der wachsenden Datenmenge in kurzer Zeit korrekte und relevante Informationen gezogen werden können, hat IT-Logix AG für die Universität Bern eine Data-Warehouse-Lösung entwickelt, die eine signifikante Verbesserung der Auswertungsmöglichkeiten erlaubt. Analysen werden nicht nur in kürzerer Zeit realisiert, sondern auch visuell ansprechender aufbereitet und einfacher zum Informationskonsumenten gebracht.

    Mehr erfahren

Agile DWH Design

Collaborative BI Requirements Analysis & Dimensional Modeling Training

Join Lawrence Corr, author of the DW/BI 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

Material

Attendees receive a course workbook, BEAM* agile dimensional modeling reference card, downloadable modelstorming templates plus paperback and ebook copies of Agile Data Warehouse Design (DecisionOne Press, 2011) by Lawrence Corr and Jim Stagnitto.

Ort: IT-Logix AG, Bern Zeit: 09.00 - 16.30

Datum:   07.-09.02.2018


Lunch, teas and coffees will be provided each day

Ort: IT-Logix AG, Bern Zeit: 09.00 - 16.30

Datum:   07.-09.02.2018


Lunch, teas and coffees will be provided each day