Data Foundation

Enterprise data infrastructure from source to consumption

Executive Summary

Build a robust, scalable data foundation that enables seamless data flow from source systems through centralized storage to consumption layers, supporting enterprise analytics and decision-making.

Source Systems

27

Integrated data sources

Data Lake Coverage

85%

Enterprise data coverage

Data Marts

12

Business domain marts

Daily Data Volume

2.5TB

Average daily ingestion

Strategic Priorities

Source Integration
In Progress

Expand source system coverage and implement real-time data capture capabilities

65%
Data Lake Optimization
In Progress

Implement medallion architecture and optimize storage costs

78%
Self-Service Analytics
Planned

Enable business users with governed self-service data access

40%

Data Governance Zachman

Enterprise data governance framework mapping business objectives to implementation

Why (Business Driven)What (Business Capabilities)How (Key Project)Where (Location)Who (People)When (Timeline)
Contextual
Motivation
Why do we need a data foundation?
No data yet
Conceptual
Business Enablement
What data do we need?
No data yet
Logical
Data Architecture
How should data flow?
No data yet
Physical
Technology Stack
Which platforms do we use?
No data yet
Assembly
Integration & Standards
How to integrate?
No data yet
Operation
Operations & KPIs
How to measure success?
No data yet

Foundation Layers

Source Layer

Core banking, CRM, and operational systems integration

27

Total Sources

18

Implemented

67%

Coverage

Data Lake

Centralized data repository with medallion architecture

450TB

Total Size

2,500+

Tables

1,200

Daily Jobs

Consuming Layer

Data marts, APIs, and analytics interfaces

12

Data Marts

85

API Endpoints

500+

Active Users

Explore

Source Coverage

Source system integration and data ingestion status

Data Lake

Central data repository and medallion architecture

Consuming Layer

Data marts, APIs, and analytics interfaces