Data Engine Thinking

Designing and implementing data solutions that are truly designed for change.

    

Data Engine Thinking is a structured, software- and methodology-independent approach to designing and managing data solutions. Rather than hand-building a data solution once, you build the engine that delivers it — reference architectures defined in layers and areas, reusable design and solution patterns, and metadata-driven automation — so the solution can evolve as requirements, teams, and technology change.

This organisation is the home of the open-source frameworks, schemas, and examples that support the approach, as described in the book Data Engine Thinking.

Repositories

Repository	What it is
samples	A curated, living library of sample code, design patterns, and solution patterns supporting the approach. Browse it at docs.dataenginethinking.com.
data-solution-automation-metadata-schema	A generic interface exchange format for data solution automation and code generation: the JSON Schema definition, a class library, and worked examples. See the schema documentation.
DIRECT	The Data Integration Run-time Execution Control Tool — a data logistics control framework to monitor, log, audit, and control data integration processes.
testing-framework	An open-source testing framework that automates the validation of a data solution with reusable data quality tests.
book-notes	The central hub for reporting, tracking, and resolving typos and content issues for the book.

Tip

The Data Engine Thinking book is out! Get it now at the Data Engine Thinking website.

Note

Several repositories moved here from the data-solution-automation-engine organisation. All existing links, clones, and Git remotes redirect automatically to their new home.

Contributing

These repositories are intentionally living: improved, expanded, and refined as new lessons and practices emerge. If you spot a gap, find an issue, or want to add a pattern — small edits are just as valuable as new contributions — pull requests are very welcome.