ShaDey Inc. Data Platform
Enterprise data platform for retail and consumer goods. Product lifecycle management, physical data modeling, SAP source intelligence, and data governance frameworks.
Interactive tools and reference architectures for product lifecycle management, data modeling, and enterprise governance. Each module is purpose-built for architects, engineers, and data teams.
End-to-end product lifecycle from market need through continuous improvement. 16 stages with SAP ECC/S4HANA table mappings, data types, and system integration points at each phase.
Conceptual, Logical, and Physical data modeling with interactive examples. Covers star schema design, SCD Type 2 patterns, and surrogate key strategies for retail/CPG domains.
Visual entity-relationship diagramming tool. Explore all 24 PDM entities with their attributes, source systems, data types, and FK relationships. Toggle between CDM, LDM, and PDM views.
Three governance scenarios demonstrating impact on data quality, metadata alignment, and downstream analytics. Includes RACI matrices, DQ scorecards, and organizational models.
Reference implementation of a centralized business glossary with consistent term definitions, ownership, and cross-system alignment. The target state for enterprise metadata.
Anti-pattern reference showing what happens when glossary alignment degrades. Conflicting definitions, ownership gaps, and downstream metric divergence across business units.
Comprehensive SAP source table catalogues and source-to-target mappings for both ECC 6.0 and S/4HANA environments. Covers field definitions, data types, business explanations, FK relationships, and transformation logic.
Star schema data model with dimensions, facts, data products, and ML/AI products. All entities include source system traceability, SCD patterns, and surrogate key strategies.
| Layer | Entity | Grain | Primary SAP Source | Pattern |
|---|---|---|---|---|
| Reference | dim_date | One row per calendar date | Generated (date spine) | Calendar script |
| Dimension | dim_customer | Customer x SCD version | KNA1 / BUT000 | SCD Type 2 |
| Dimension | dim_product | Product x SCD version | MARA / MAKT / MBEW | SCD Type 2 |
| Dimension | dim_supplier | Supplier x SCD version | LFA1 / BUT000 | SCD Type 2 |
| Dimension | dim_store | Store x SCD version | T001W | SCD Type 2 |
| Dimension | dim_promotion | Promotion x SCD version | KONH / KONP | SCD Type 2 |
| Fact | fact_order | One row per order | VBAK / VBUK | Transaction |
| Fact | fact_inventory_snapshot | Product x store x date | MARD / MATDOC | Periodic snapshot |
| Fact | fact_sales | Billing doc item | VBRK / VBRP | Transaction |
| Fact | fact_shipment | One row per delivery | LIKP | Transaction |
| Fact | fact_return | One row per return | VBAK (RE) / VBRK (G2) | Transaction |
| Data Product | dp_customer_360 | One row per customer | DWH derived | Aggregation |
| Data Product | dp_demand_forecast | Product x store x date | ML pipeline | Prophet + LightGBM |
| ML/AI | ml_feature_store | Entity x feature x time | ML pipeline | Key-value store |
Three governance models demonstrating the impact of metadata alignment on data quality, analytical consistency, and organizational trust. Side-by-side comparison of aligned vs. degraded vs. absent governance.
Three scenarios with RACI matrices, DQ scorecards, and organizational impact analysis. Demonstrates how governance maturity affects every downstream system and business decision.
View scenarios →Reference implementation: centralized term ownership, consistent definitions across systems, and full semantic traceability from source to reporting layer.
View glossary →Demonstrates metric divergence, conflicting ownership, and downstream trust erosion when glossary definitions drift between business units.
View anti-pattern →Full field-level lineage from SAP source tables through transformation logic to PDM target attributes. Explicit vs. inferred mapping confidence for all 24 entities.
View mappings →Deep-dive training modules covering CRM identity resolution, Data Vault 2.0, domain-driven design, advanced dimensional modeling, semantic layers, medallion architecture, and enterprise model governance.
Cross-system identity resolution across SAP, Salesforce, and Shopify. Survivorship logic, timing conflicts, and golden record assembly for ShaDey Inc.'s omni-channel customer data.
View module →Hub/Satellite/Link patterns, Raw vs Business Vault, hashdiff computation, and a comprehensive model validation framework with anti-pattern detection.
View module →Bounded contexts for retail domains, anti-corruption layers, MDM golden records, and multi-region modeling with global core entities and regional extensions.
View module →Grain discipline, three fact table types, additivity traps, multi-calendar dimensions, SCD trade-offs, and BI consumption safety patterns for enterprise warehouses.
View module →KPI dependency DAGs, metric contracts, AI feature stores, feature leakage prevention, training/inference parity, and hot/cold data tiering strategies.
View module →Bronze/Silver/Gold lakehouse layers, relational-to-graph conversion patterns, temporal edge modeling, and Neo4j Cypher queries for graph-based analytics.
View module →Forward/reverse engineering workflows, naming enforcement, semantic drift detection, version reconciliation, conflict resolution, and UDP strategy for enterprise models.
View module →Seven Neo4j use cases for retail: supply chain risk analysis, customer network discovery, product recommendations, data lineage, fraud detection, and more.
View module →Recommended workflow for architects, engineers, and data teams navigating the platform.
Start with the Product Lifecycle Journey to understand the 16 stages, SAP system touchpoints, and data flows across the retail/CPG value chain.
Use the interactive ER Modeler to examine all 24 PDM entities, their attributes, source system mappings, and relationships at CDM, LDM, and PDM levels.
Reference the SAP source table catalogues and source-to-target mappings to understand field-level lineage, transformation logic, and join conditions.
Review governance scenarios and business glossary references to ensure metadata alignment, term consistency, and data quality standards across the platform.
Static site. No build tools or runtime dependencies. HTML + CSS + JS. Works from file:// protocol.