🔎 Insights & Findings

Notes from our reverse-engineering of the DAS system and our warehouse design decisions.

7 OLTP Anti-Patterns in das-db

#	Finding	Example	ETL Impact
1	1NF violation (list-in-column)	accounts.branches = comma IDs	Explode to junction tables
2	Missing explicit FKs	account_transactions	Orphan-risk validation
3	Type anomaly	customer_credit_invoices.business_id = longtext	Cast in ETL; indexes die
4	Redundant indexes	sales_invoices 7+ trees	Extract carefully
5	No partitioning	stock_histories, account_transactions	Chunked/date-bounded extracts
6	CDC as BLOB	pub_sub_message_records.old_obj/new_obj	Parse JSON in Python
7	Missing audit columns	opening_stocks	Full-refresh, not delta

Full detail: Epic 1 · Source Analysis.

The Purpose of an ERP

Single Source of Truth

An ERP unifies finance, inventory, delivery and HR into one cohesive database. For a multi-BU organization it ensures data flows seamlessly between departments, leadership sees real-time performance, and processes stay standardized, scalable and compliant. Our warehouse extends the ERP — it does not replace it.

Pipeline Architecture

graph BT
    subgraph SOURCE
        D1[Mtech] & D2[MKitchen] & D3[Marathon Exp.] & D4[MTrading] & D5[ShweZay]
    end
    subgraph ETL
        C5[Daily Sync] --> C4[Cleansing] --> C3[UOM Conv.] --> C2[SKU Mapping] --> C1[Python/SQL ETL]
    end
    subgraph ANALYTICS
        B1[dim_product] & B6[fact_sales] & B7[fact_inventory] & B8[fact_finance]
    end
    subgraph PRESENTATION
        A1[Looker Studio] & A3[Excel]
    end
    SOURCE --> ETL --> ANALYTICS --> PRESENTATION