Feb

Agile Data Warehouse Design with Lawrence Corr - Bern, Switzerland 7-9 Febr...

by DecisionOne Consulting

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Date and time

Wed, 7 Feb 2018, 09:00 –

Fri, 9 Feb 2018, 16:30 CET

Location

IT-Logix AG

Schwarzenburgstrasse 11

3007 Bern

Switzerland

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Refund policy

Refunds up to 30 days before event

Description

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.

Lunch, teas and coffees will be provided each day