This repository complements Data Engine Thinking by providing practical examples for implementing a flexible data solution. In the book, we often refer to our website -including this repository- to dive deeper into the technical aspects. This way, we aim to keep the book readable while still providing the level of technical detail we feel is necessary to developer data solutions the way we feel these should be implemented.
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Data is evidence of past activity — frozen moments in time, waiting to be uncovered and analyzed. But without understanding the context in which data is created, it remains just ‘stuff.’ Building this understanding takes time. To turn raw data into meaningful information, we must continuously refine our interpretations — and adapt our data solutions accordingly. Flexibility is key.
A truly effective data solution must evolve alongside our understanding, supported by a structured approach, automation, and code generation.
Data Engine Thinking presents an end-to-end methodology for designing and delivering data solutions that can evolve. This book guides you on a journey with FastChangeCo, a fictitious company struggling to keep up with today’s business demands. Faced with an increasingly complex and fast-changing system landscape, they embark on a mission to develop a future-proof data solution — one that accelerates the implementation of new requirements and overcomes integration challenges. Supported by detailed conceptual and practical explanations, we follow FastChangeCo as they transform their fragmented, inflexible data platforms into a solution that fully meets the business’ needs.
Along the way, you’ll learn how to:
- Define a clear vision and strategy for data
- Select the right frameworks for a scalable architecture
- Overcome integration challenges
- Tackle the complexities of ‘time’ in data
- Deliver an architecture that is designed for change
- Implement code generation and automation
- Solve real-world problems when working with data
Whether you're a data architect or modeler, engineer, or business leader, Data Engine Thinking will provide the principles, patterns, and practical techniques to create a data solution that adapts — just like your organization does.
Roelant is a globally recognized data expert, speaker, and writer with over 25 years of experience in data management. As a consultant, trainer, developer, software vendor, and corporate decision-maker, he has experienced data management from many angles. His passion for automation and model-driven engineering has been a constant throughout his career.
After beginning his career developing BI solutions, he quickly became fascinated by pushing the boundaries of automation, especially in the data integration space. Having led large-scale data projects worldwide, he remains a firm believer that harnessing patterns, automation, and code generation is the key to making data solutions more efficient, manageable, and, most importantly, adaptable.
Dirk is an experienced independent consultant and managing director of TEDAMOH — the Data Modeling Hub. He is considered a global expert on BI & data architectures, modeling, and is highly regarded for his work on temporal data — including groundbreaking examples on his blog and in his trainings that highlight the many aspects of managing time in data, and how to solve them.
With a 25-year career centered on data modeling, temporal data, and automation, Dirk has consistently applied these disciplines to create flexible, lean, and extendable architectures. As a pioneer for Data Vault and FCO-IM in Germany Dirk has written various publications, and is a highly acclaimed international speaker at conferences.