Data Warehousing & BI Summit - Barry Devlin - Rick van der Lans - Mike Ferguson Data Warehousing & Business Intelligence Summit

Agile Datawarehouse Design

Agile Data Warehouse Design covers step-by-step techniques for capturing data warehousing/business intelligence (DW/BI) requirements and turning them into high performance dimensional models in the most direct way: by modelstorming (data modeling + brainstorming) with BI stakeholders.

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 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.

The course teaches BEAM (Business Event Analysis & Modeling), an agile approach to dimensional modeling, for improving communication between data designers, BI stakeholders and the whole DW/BI development team. BEAM provides tools and techniques that will encourage designers and developers to set aside their keyboards and entity relationship based tools and model interactively with their business stakeholders and colleagues. The result is everyone thinks dimensionally from the initial high level data requirements right down to detailed datasets. Developers understand how to efficiently implement dimensional modeling solutions. Business stakeholders feel ownership of the models they co-create and can already imagine how they will use them to answer their business questions.

BEAM helps close the gap between the business users’ data requirements and database design. It allows groups of business and IT professionals to model data collaboratively to not only gather and prioritize data requirements but create a shared understanding of data analytics opportunities and design more flexible BI solutions.

Join Lawrence Corr, author of the DW/BI bestseller Agile Data Warehouse Design for a lively three-day collaborative dimensional modeling course covering the latest agile techniques for systematically gathering Business Intelligence (BI) requirements and designing effective DW/BI systems.

Learning objectives

You will learn how to:

Understand the requirements and challenges of DW/BI design in a “Big Data” world
Explain the impact of agile practices on DW/BI design
Agile dimensional modeling using Business Event Analysis & Modeling (BEAM)
Run modelstorming sessions: do data modeling that is quicker, more inclusive, more productive, and quite frankly more fun!
Model BI requirements with stakeholders using business-friendly tools and techniques
Model data requirements collaboratively using visual thinking and storytelling
Tell dimensional data stories using the 7Ws (who, what, when, where, how many, why and how)
Use narrative, visual thinking, 7Ws and lots of Post-it ™ notes to get everyone thinking more clearly about data requirements and creating better data models
Help business stakeholders develop powerful mental maps for exploring their data with modern BI tools
Model by example not abstraction; using data story themes, not crow’s feet, to describe detail
Storyboard the data warehouse to discover conformed dimensions and plan iterative development
Rapidly translate BI data requirements into efficient, flexible data warehouse and data mart designs
Plan, design and develop BI solutions incrementally
Solve common BI performance and usability problems with proven dimensional design patterns.

Who Should Attend

Business and IT professionals who want to jointly develop better analytical data solutions sooner
Business analysts, scrum masters, data modelers/architects, DBAs and application developers new to DW/BI, will benefit from the solid grounding in dimensional modeling.
Data scientists and engineers will learn valuable techniques for designing feature rich datasets.
Experienced DW/BI professionals will find the course updates their hard-earned industry knowledge with fresh ideas on agile modeling, dimensional design patterns and business model alignment.
Data Vault practitioners will appreciate BEAM’s systematic approach for designing query-friendly dimensional data marts and unlocking business value.

You receive a free copy of the book Agile Data Warehouse Design by Lawrence Corr.

Lawrence Corr

Chief Data Modelstormer
DecisionOne Consulting

Lawrence Corr is a leading international BI consultant and former Ralph Kimball Associate. He has worked on data warehousing projects in the US, Europe, the Middle East and Africa within healthcare, telecoms, broadcasting, higher education, financial services and retail, helping organizations benefit from simpler, more inclusive requirements modeling techniques.

Van der Valk Hotel Utrecht
Winthontlaan 4-6
3526 KV Utrecht
Telefoon 030 8000 800

The hotel is very well accessible by public transport. From busstop ‘Kanaleneiland Zuid’ it is only a three-minute walk. You can take buses 63, 65, 66, 74 and 77 from Utrecht Central Station and you also take the tram line 20 or 21 from the train station and get off at stop ‘Kanaleneiland’. Please consult www.9292.nl (door-to-door journey planner, also available in English) or call 0900-9292 (travel advice by phone, € 0.70 p/m).

Van der Valk Hotel Utrecht is also located next to the highway A12, exit 17 (Utrecht / Jaarbeurs / Kanaleneiland).

Although the hotel has a large parking garage, we cannot guarantee parking spots. We therefore advise you to go by public transport.

For those who would like to arrive the day before, there is the possibility of staying at the Van der Valk Hotel Utrecht. However, the hotel does not provide special discounts for attendees of events. Therefore, when interested in an overnight stay, please consult Van der Valk directly to make a reservation.

More information about the hotel and the location can be found on their website www.vandervalkhotelutrecht.nl.

Taking part in this three-day workshop will only cost 1791 Euro per person when registering 30 days beforehand and 1990 Euro afterwards (excl. 21% Dutch VAT). This also covers documentation, lunch, coffee and the book Agile Data Warehouse Design by Lawrence Corr. If you also register for our Datawarehousing & BI Summit, you will get extra discount and pay 1890.50 Euros for this workshop and 1701.45 Euros when registering early.

For Credit Card payment please contact our office using our contact form or by e-mail mentioning your phone number to obtain your credit card information.
In completing your registration form you declare that you agree with our Terms and Conditions.

Extra discounts
Discounts are available for group bookings of two or more delegates representing the same organization made at the same time. Ten percent off for the second and third delegate and fifteen percent off for all delegates when registering four or more delegates (all delegates must be listed on the same invoice).
This cannot be used in conjunction with other discounts.

Payment
Full payment is due prior to the event. An invoice will be sent to you containing our full bank details including BIC and IBAN. Your payment should always include the invoice number as well as the name of your company and the delegate name.

Payment by credit card is available for attendees from countries outside the IBAN region. This is not an automated process via our website but requires a manual transaction by phone or Skype. For Credit Card payment please contact our office by e-mail or through our contact form mentioning your phone number to obtain your credit card information. Never mention your credit card details in our registration form, contact form or in e-mail messages.

The course starts at 09.30 am and ends at 5 pm. Registration commences at 08.30 am.

Modelstorming – Agile BI Analysis and Design

BI/DW design requirements, challenges and opportunities: the need for agility and collaboration
The 7 Vs of Data. The 3 Vs of Big Data + 4 more that technology alone cannot solve. Facts and opinions. Configuration, calibration and collaboration. The need for collaborative data design
Reactive data warehouse design vs. proactive design
The 6Ws Game – Breaking the ice, introducing the Ws and basic visual collaboration techniques. Adding a 7th W for analytical data modeling
Waterfall BI vs. Agile BI: balancing ‘just enough design up front’ (JEDUF) and ‘just in time’ (JIT) data modeling
Traditional BI requirements gathering limitations: data-driven vs. report-driven. Supply vs. demand. Avoiding the ‘field of dreams’ build-it-and-they-will-come approach. Becoming value-driven
Modelstorming with BI stakeholders: the case for collaborative data modeling

Agile Dimensional Modeling Fundamentals

Modeling for measurement: the case for dimensional modeling, star schemas, facts & dimensions
Business Event Analysis and Modeling (BEAM): an agile approach to dimensional modeling
Thinking dimensionally with 7Ws (who, what, when, where, how many, why & how). Supporting a measurement mindset

Collaborative Data Requirements Gathering

Introduction to BEAM: “Who does what?” a simple question for discovering business events
Describing business event details using the 7Ws. Modeling a single business event in 7 simple questions: using the BEAM script
Documenting business events with the BEAM Canvas (and lots of Post-it notes)
Modeling multiple business events in just enough detail. Avoiding technical data modeling jargon. Modelstorming data as verbs, nouns and adjectives
Modeling related business processes (multiple business events) using the BEAM Storyboard

Visual Dimensional Modelstorming Tools

NoERD: Not only Entity Relationship Diagrams – using more appropriate diagrams for collaborative modeling with subject matter experts
Business Model Canvas: aligning business intelligence and data analytics with business model definition and innovation. Value-driven BI job one: measuring the business model
BEAM Canvas: a detailed BI model canvas for systematic data set & database schema design
Data Stories: Using narrative to engage stakeholders and help them describe data-rich business events
Data Story Types: Discrete, Evolving and Recurring business events
BEAM Tables and Data Story Themes: modeling data requirements by (structured) example
Data Timelines: Sorting multiple business events chronologically. Modeling time and process measurement
BEAM Storyboard: modeling processes, shared data definitions and development priorities using a collaboration-friendly, non-technical version of the dimensional matrix
Recording priorities and estimates for agile BI data development within the design
Hierarchy Charts: modeling BI drill-downs, rollups and critical measurement levels for cross process comparison. Using the Ws to identify ‘hot’ levels
Change Stories: capturing historical data requirements and reporting defaults (slowly changing data rules)

Agile Star Schema Design

Converting analytical data requirements into logical data models. Turning data story nouns, verbs, and adjectives into entities, relations, attributes.
Converting a BEAM canvas into star schemas and other ER diagrams/models. Turning business events into facts and dimensions or hubs, links and satellites
Test-driven design: agile/lean data profiling for validating and improving requirements models
Data warehouse reuse: identifying, defining and developing conformed dimensions and facts. Developing an agile data warehouse bus architecture. Coping with conformance failure
Designing flexible, high performance star schemas: maximising the benefits of surrogate keys
How Much/How Many: Designing facts, measures and KPIs (Key Performance Indicators)
Fact types: transactions, periodic snapshots, accumulating snapshots
Fact additivity: fully additive, semi-additive and non-additive data. Full documenting and correctly aggregating semi-additive measures
Fact performance and usability: indexing, partitioning, aggregating and consolidating facts
Capturing complex slowly changing data rules: mixing type 1 and 2 attributes. Differentiating between minor and major changes and corrections via multi-column dependencies
Designing facts, measures and KPIs (Key Performance Indicators)
Fact table types: transactions, periodic snapshots, accumulating snapshots. Choosing the appropriate types
Refactoring star schemas: responding to change, dealing with data debt
Agile process measurement: designing and developing derived fact tables for multi-verb/event analysis
Recording a BEAM Storyboard as a Dimensional Matrix – bus architecture.
Enhance Star Schema: drawing better database diagrams. Taking advance of position and visually consistent layouts to encourage reuse and encode common data model patterns. Using BEAM short codes to fully document dimensional design decisions
Developing Data Warehouse Matrix dashboards. Documenting the design without complex global schemas

Dimensional Design Patterns

Using the 7W data types to identify common analytical data challenges ant the dimensional design patterns that address them.
Adapting design pattern and understanding their limitations – when to uses them, when not to.

Who & What dimension patterns: customers, employees, products and services

Modeling large volatile populations with rapidly changing attributes: mini-dimensions & customer facts
Customer segmentation: business to business (B2B), business to consumer (B2C) dimensions: Swappable population subsets for performance, usability and compliance
Multi-level dimensions: supporting business events with varying levels of descriptive information and variable granularity measurements
Recursive customer relationships and organisation structures: variable-depth hierarchy maps for analysing 1:M and M:M recursive relationships
Current and historical reporting perspectives: hybrid slowly changing dimensions. Using highly efficient swappable views to support multiple historic perspectives with agility. Avoiding unnecessary type 6 and 7 slowly changing dimensions
Mixed business models: heterogeneous products/services, diverse attribution, ragged hierarchies: swappable attribute subset dimensions
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
Describing and measuring time: modeling when details as dimensions and facts. Coping with specialist clocks and varying schedules
Multinational BI: national languages reporting, multiple currencies, time zones & national calendars
Understanding journeys and trajectories: modeling events with multiple geographies – the importance of first and last locations

Why & How dimension patterns: cause and effect

Causal factors: trigger 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. Avoiding unnecessary model complexity – efficiently handling exceptional data which is only ‘slightly’ multi-valued
Behaviour Tagging: modeling causation and outcome with dimensional overloading. Using step dimensions to understand sequential behaviour

Review

Further reading/viewing for encouraging and supporting modelstorming within your organisation
Downloadable BEAM templates and other online modelstorming resources
Documented and Distributed Modelstorming: photography, visual collaboration tools and platforms
The immutable laws of data warehousing – anticipating agile BI.

testimonials

Bram Nijenhuis BI-specialist, VisionBI B.V.

“Relevant for anyone interested in gathering BI-requirements, with a lot of practical models.”

Petter Derhaag BI Developer, PGGM

“Great course for people in BI who are looking for a quality set of basic knowledge in DWH design. Combine this with excellent methods to do this with non-technical colleagues.”

Paul Gale Data Architect, Paga BV

“Great course from the business perspective, will make me change my approach to modeling with the business.”

Erik van Dongen Data Engineer, Gemeente Oosterhout

“Very refreshing approach to Data Warehouse Modelling. Speaking the stakeholder language is a big plus.”

Francoise Grandjean BI Expert, Keyrus nv

“Very complete DWH and DTM training, including Agile Business Communication tips.”

Norbert Lourijsen BI Consultant, Rabobank

“Great workshop, very inspiring.”

Peter Hamersma Data analist, Agentschap Telecom/EZK

“Lawrence is an excellent trainer and has a lot of experience he shares with us.”

Simona Klebonaite , INFOTRUST

“Lawrence Corr demonstrates exceptional professionalism in his ability to present complex subjects in clear and understandable language. His engaging and enjoyable teaching style makes learning both fun and effective. The three-day course is rich with practical exercises, use cases, analyses and inspiring, thought-provoking ideas.”

Rutger Meijer BI-specialist, RDW

“Great course, good speaker! Recommend it to all.”

Rowan Dunne Data Governance Analyst, PVM

“I found this a nice review of Star schema's, and loved the process to conduct Business Event Analysis & Modeling.”

Maarten Sitvast BI Team-lead, Ymere

“Lawrence is a fantastic, enthusiastic speaker. Definitely an 'icon' in the world of BI. I enjoyed following his workshop BEAM Agile Data Warehouse Design.”

Erwin de Vries Data Engineer, Devhouse Spindle

“Lawrence Corr is a really enjoyable and knowledgeable lecturer. The workshop has a nice variety of team exercises and theory.”

Sanne van der Veer BI analist, Ymere

“Very intersting, fun, broad. Covers a lot and manages to keep it simple. Inspiring days, lots of new ideas!”

Najma Mustafa Product Owner, NEOM

“I can see why Lawrence is an expert in the Agile DW & Dimensional Modelling field. His teaching & knowledge is thorough, engaging and thoughtful.”