Analyticaldepends
Analyticaldepends is a conceptual framework and set of practices for representing and managing dependencies among data sources, analytical procedures, and results within analytical pipelines. It aims to make the flow of data, decisions, and outcomes explicit so that analyses are more reproducible, auditable, and governable.
- Dependency graph: a formal model where nodes represent data sources, datasets, analyses, and results, with edges
- Provenance and versioning: metadata about origin, authorship, and historical changes to inputs and analyses, enabling traceability
- Impact analysis: mechanisms to determine how changes to inputs or methods affect downstream results and decisions.
- Reproducibility and governance: built-in audit trails, access controls, and documented assumptions to support verifiability and compliance.
Applications of analyticaldepends span data science, business intelligence, and regulatory reporting. It supports scenario planning, risk
Architecture and implementation typically include a dependency graph database, a metadata and lineage store, registries for
Limitations and challenges involve managing scale, resolving ambiguities in complex pipelines, ensuring privacy and security, and