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Full Stack Data Science in Python
Home of the Open Data Product Standard (ODPS).
The Data Product Descriptor Specification (DPDS) Repository
Template to deploy a Data Product for analytics and data science use-cases into a Data Landing Zone of the Data Management & Analytics Scenario (former Enterprise-Scale Analytics). The Data Product template can be used by cross-functional teams to create insights and products for external users.
Template to deploy a Data Product for Batch data processing into a Data Landing Zone of the Data Management & Analytics Scenario (former Enterprise-Scale Analytics). The Data Product template can be used by cross-functional teams to ingest, provide and create new data assets within the platform.
Template to deploy a Data Product for data stream processing into a Data Landing Zone of the Data Management & Analytics Scenario (former Enterprise-Scale Analytics). The Data Product template can be used by cross-functional teams to ingest, provide and create new data assets within the platform.
A platform to manage the data product life cycle
The Data Store API Specification Repository
Playground site for creating/validating data contracts
Teaching materials for Building data-driven products
Gather Information Product requirements with the Information Product Canvas, an AgileDataGuides Pattern Template app
The Schema Annotations Specification (SAS) Repository
A Machine Learning Product for Business Planning Involving Predicting Inflation, Recession and Business Cycles
Data Catalog documentation, from terms and explanation to strategic roadmap for implementation. Published to Github pages from my Obsidian via Quartz plugin.
Local-first spreadsheet operations workbench with configurable source mapping, metrics, dashboards, and reporting-ready handoff.
A repo for the MOOC of the same name.
Legal AI product-boundary evaluation and data governance system for model routing, RAG reliability, human review, release gates, and data asset routing.
MCP agent that transforms high-level business intents into structured Data Product Requirement Prompts through AI-powered conversational refinement
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