Program · Foundation

Enterprise Data Warehouse

Answers: what happened? EDW establishes Saba IP's trusted data foundation — integration, canonical models, semantic consistency, governance, and historical storage.

Purpose

Decision-ready information, not just stored data.

EDW transforms operational data into trusted, curated analytical information that serves as the single analytical foundation for enterprise reporting, performance management, and decision intelligence.

Operational SystemsWhere data originates
EDWCurates the foundation
EPMReports on performance
EDIPredicts and recommends

Pipeline

How data becomes decision-ready.

Five phases, each producing something the next phase depends on:

1. Extract Data

Retrieve operational data from source systems. Manual today — extraction criteria per source system are being documented.

2. Prepare Data

Clean, standardize, validate and transform in KNIME — data quality checks, standardization, incremental logic, staging.

3. Curate Enterprise Data

Update master and reference dimension tables, business mappings, and lookup tables — where data becomes enterprise-ready.

4. Publish Analytical Data

Produce parquet files and analytical snapshots; publish to the serving layer consumed by EPM and EDI. Implemented today via Supabase.

5. Validate & Monitor

Row counts, QA, refresh validation, pipeline health, completeness, and release confirmation.

Engagements

Specific deliverables built on this pipeline.

Artifacts

Published outputs.

Standards

The rules EDW work is built against.