For the First Time in Brazil, Lawrence Corr October 22 - 24, 2018, Brasília-DF, Brazil Um curso de 3 dias ministrado internacionalmente pelo autor e especialista em Data Warehouse Lawrence Corr, abrangendo técnicas ágeis para coleta de requisitos de Business Intelligence (BI) e projeto eficiente de sistemas DW/BI. A 3-day course presented 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. Inscreva-se! 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. Information Workshop ministrado em inglês* Workshop ministered in english* 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. What you will learn Model BI requirements with BI stakeholders using inclusive tools and visual thinking techniques Rapidly translate BI requirements into efficient, flexible data warehouse designs dentify and solve common BI problems – before they occur – using dimensional design patterns Plan, design and incrementally develop BI solutions with agility Lawrence Corr Lawrence Corr is a DW/BI designer and modelstormer who has worked in management information / decision support / business intelligence for more than 25 years and has specialised in data warehouse design since 1996. He has developed, reviewed and enhanced BI solutions within aerospace, insurance, healthcare, pharmaceuticals, telecommunications, engineering, manufacturing, television, financial services, e-commerce and retail, for client in Europe, USA, the Middle East and Africa. Lawrence held the position of data warehouse practice leader at Linc Systems Corporation, CT, USA and vice-president of data warehousing products at Teleran Technologies, NJ, USA. In 2000, he was invited by Ralph Kimball to become an associate and teach data warehousing classes for Kimball University in Europe and South Africa during 2000 and 2001. Nowadays he works completely independently through DecisionOne Consulting, based in the UK, providing agile data consultancy and training worldwide. He is the author of 'Agile Data Warehouse Design: Collaborative Dimensional Modeling, from Whiteboard to Star Schema’. Redes sociais: LinkedIn e Twitter Workshop Outline Day 1: Modelstorming – Agile BI Requirements Gathering Agile Dimensional Modeling Fundamentals I/DW design requirements, challenges and opportunities: the need for agility Modeling with BI stakeholders: the case for collaborative data modeling odeling for measurement: the case for dimensional modeling, star schemas, facts & dimensions hinking dimensional using the 7Ws (who, what, when, where, how many, why & how) usiness 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.