Around the world, there’s a surge of interest in data modelling as a powerful tool for improving communication among technical and non-technical groups. Why? – because it allows all stakeholders to develop a common understanding of the things - the entities - that are at the core of the business’s applications, processes, and information assets. It uncovers and resolves inconsistency in business terminology, policy, and rules that otherwise plague application development and other initiatives.

This workshop introduces Concept Modelling and then Logical Modelling from a non-technical perspective, thoroughly covering the components of any data model - entities, relationships, attributes, and rules. It includes clear, practical guidelines, as well as many tips, quality checklists, and warnings of common pitfalls. Just as important, it contains far more advice on the process of developing a data model than other courses, including specific methods for getting subject matter experts involved and maintaining their commitment.

Business Analysts and Agile/DevOps teams find that a small, up-front investment in business-oriented data modelling saves much time and refactoring in later sprints. Data professionals, including business intelligence (BI) specialists, data scientists, big data professionals, and data lake implementors see the communication and integration benefits of the technique. It’s even used in support of business transformation initiatives, and software selection and configuration. The key in all cases is to recognise that a data model (especially a concept model) is a description of a business, not of a database – the philosophy on which this unique workshop is based.

• Understand the essential components of an entity-relationship model - entities, relationships, attributes, and assertions/rules
• Use entity-relationship modelling to depict facts and rules about business entities at different levels of detail and perspectives, specifically Concept (overview) and Logical (detailed) Models
• Apply techniques that support active participation and engagement by business professionals
• Develop conceptual and logical models quickly using repeatable methods for Agile modelling
• Apply the most common patterns in data modelling to rapidly develop and extend useful models
• Use a Concept Model as the starting point for discovering Use Cases/User Stories and Services
• Draw an Entity-Relationship Diagram (ERD) for maximum readability
• Read a data model, and communicate with specialists using the appropriate terminology.

Core audience - business analysts, solution architects, application developers (especially on Agile teams) responsible for the analysis, design, and development, or selection and configuration, of an application.
Business intelligence (BI) professionals, big data specialists, data scientists, data lake implementers and business professionals are all currently benefitting from this workshop.