Explain MD-DDL architecture concepts and compare with Data Mesh and Data Fabric.
npx skills add https://github.com/Semprini/md-ddl --skill architecture-semprini
Please help me install this Agent Skill. Skill: architecture Source: https://github.com/Semprini/md-ddl/tree/main/agents/agent-architect/skills/architecture Command: npx skills add https://github.com/Semprini/md-ddl --skill architecture-semprini
This Skill helps users understand and articulate the core architectural philosophy behind MD-DDL, enabling them to position it effectively within their organizations and compare it against alternative approaches.
Use the architecture skill to explain the concept of Data Products as architecture quantum.
High-intent search queries and answers about installing and using this skill.
The MD-DDL architectural philosophy centers on Data Autonomy and model-driven generation to create self-sufficient data products. Data Autonomy works by empowering data assets to operate independently within the architecture, reducing centralized bottlenecks.
Comparing MD-DDL architecture to Data Mesh and Data Fabric frameworks highlights distinct approaches to decentralized data management. MD-DDL emphasizes model-driven generation and data products as architecture quanta, contrasting with the federated governance of Data Mesh and the integrated layering of Data Fabric.
To prepare an executive summary on data product architecture for a CIO, use the Skill's Teach mode to generate tailored talking points. It translates the MD-DDL architectural philosophy into business value propositions, trade-offs, and next steps for non-technical stakeholders.
You can use MD-DDL architecture to position data products against an Enterprise Data Warehouse (EDW) by contrasting decentralized data autonomy with centralized EDW repositories. The Skill facilitates structural comparisons to highlight specific architectural trade-offs and business advantages.
A model-driven generation approach for data architecture may not suit contexts requiring highly bespoke, non-standard data pipelines outside the data products paradigm. If an organization relies heavily on unstructured data without clear architectural models, alternative frameworks may be more appropriate.
SempriniCompare generated MD-DDL artifacts against baseline documentation or deployed schemas.
nathanielcrowell12-specImplement Stripe Connect destination charges with 50/50 commission splits for marketplace payments.
nanorepublicaValidate code against centralized global tech stack standards.
wardawgmalviciousImplement T-SQL commands for schema, data, and performance in Fabric Data Warehouse.
