Agile BI: Just Enough Design, Data Modeling with Agility Training

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Agilists criticize the “big design up front” (BDUF) nature of plan-driven development. Uncertainty early in a project makes BDUF costly and risky. However, the avoidance of BDUF is sometimes misconstrued to mean “no design up front,” which leads to poor quality and high technical debt. Experienced agilists know that what is truly needed is sufficient design up front (SDUF)—enough to galvanize developers around a shared understanding of the problem domain, architecture, and data models. This course introduces an agile modeling approach that strikes the sufficient-up-front and just-in-time balance.

There are no prerequisites for this course.

Data warehouse architects, designers, developers, and administrators
Business intelligence practitioners
Business analysts and product owners

Agile modeling values and principles
Techniques for determining the right level of up-front design
How to avoid overbuilding solutions by designing for what is needed
Domain modeling
Data model patterns
Data smells and the impact of technical debt
Continuous integration
Safe refactoring techniques for making incremental design changes
How to determine the right level of design documentation that is needed
Effective collaborative modeling practices for cross-functional teams
How to minimize the amount of unnecessary rework through reference and conceptual designs
How to establish iteration zero as an agile practice that gives teams the runway to start delivering

1. Introduction

Agile Overview
Benefits of Evolutionary Design

2. Agile Modeling Mindset

The Challenge
Purpose of Modeling
Agile Modeling Goals
Modeling in the Agile Project Management Lifecycle
Agile Modeling Guiding Principles

3. Agile Documentation

Why, When and What to Document
Creating Self-Evident Implementations
Documenting with a clear purpose for the right audience
Minimally sufficient documentation
Negative Value Documentation and Document End of Life

4. Domain Modeling

Why, When and Who
Story-Gathering Process
Defining and Refining user roles
User Personas
Domain Modeling Exercise

5. Use Cases and User Stories

Why, When and Who
Use Cases
User Stories
Use Case Exercise

6. Sufficient Design Up Front

How Buildings Learn
Iteration Zero
Conceptual Data Modeling
Establishing Test Automation
Continuous Integration Infrastructure
Sufficient Design Guiding Principles

7. Data Model Patterns

What is a Pattern?
Pattern References
Why Use Patterns?
Drawbacks of Patterns
Patterns, Seed Models, and Archetypes

8. Technical Debt

Overview
Design and Technical Debt
Indicators of Technical Debt
Prioritizing Debt
Technical Debt exercise

9. Database Refactoring

What is Refactoring?
Refactoring Categories
How Refactoring Works
Preparing to Refactor
How to Refactor

10. Agile Modeling with Data Vault

Complexity of Changeb
Introduction to Data Vault
Hubs, Satellites and Links
Data Vault example
Data Vault Strength: Adapting to Change
Data Vault Principles
Why is Data Vault agile?
Data Vault Exercise

Agile BI: Just Enough Design, Data Modeling with Agility Training

Prerequisites

Who Should Attend

What You Will Learn

Outline

6 IMPORTANT TIPS FOR AGILE COACHES IN 2021

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