Purpose of This Repository
This repository documents Phase 4 of my role at ECO3, where my responsibilities expanded beyond reporting into:
- Data engineering
- Automation
- Platform architecture
- Long-term data strategy
The core focus of this phase is BDM 2.0 the future-state data environment designed to replace a fragile legacy ecosystem with a scalable, secure, and AI-ready platform.
This repository captures how hands-on operational experience directly shaped architectural decisions.
All examples are conceptual and use dummy representations to respect confidentiality.
While owning and stabilizing reports (Repo ECO3-operational-BI-ownership ), clear systemic problems emerged:
- Reporting logic duplicated across tools
- Transformations scattered across Excel, Access, and Power BI
- High dependency on individual files and people
- Extremely high break risk
- No clear separation between data, logic, and consumption
Fixing reports alone was not sustainable.
A platform-level redesign was required.
Data Engineering & Automation Work
Python for Data Cleaning & Reliability
To reduce fragility, I introduced Python into the ecosystem:
- Data cleaning and transformation
- Reconciliation logic
- Automation of repetitive tasks
- Replacement of complex Excel macros
- Replacement of fragile Access query logic
This allowed:
- Clear, versionable logic
- Improved transparency
- Reduced manual intervention
- Easier troubleshooting
Reverse-Engineering Legacy Logic
A major part of the work involved reverse-engineering:
- Complex Access databases
- Nested Excel formulas
- Legacy macros
- SAP BW Analyzer–based SQL extractions
I translated undocumented logic into:
- Clear transformation steps
- Business-readable rules
- Maintainable data flows
This knowledge directly fed into future-state architecture design.
BDM 2.0 – Future-State Architecture
Together with the BI Head, I contributed to designing BDM 2.0, based on:
- Real operational pain points
- Business feedback gathered via surveys
- Long-term scalability and governance needs
Architectural Shift
Current (Legacy):
SAP → SAP BW → Excel → Access → Excel / Power BI
Future (BDM 2.0):
SAP → Microsoft Fabric → Centralized Databases → Power BI / Excel
Centralized Database Strategy
BDM 2.0 will consist of XX centralized databases, designed to be:
- Easy to maintain
- Easy to understand
- Secure by design
- Scalable
- Resilient
- Hard to break
These databases will serve:
- Executives (CEO-level)
- Management
- Operational teams
- Analysts
- Future AI and automation use cases
Design Principles Applied
Key principles guiding BDM 2.0:
- Separation of data, logic, and consumption
- Single source of truth
- Clear ownership
- Minimal duplication
- Controlled complexity
- Business-readable structures
Every design decision is traceable back to real operational issues observed in production.
Microsoft Fabric Involvement
I actively work with Microsoft Fabric while still supporting legacy systems.
My contributions include:
- Evaluating Fabric capabilities
- Designing data flows into Fabric
- Defining how master data should connect
- Aligning Fabric usage with Power BI and Excel consumption
- Ensuring future extensibility
Managing Major Business Changes
Product mapping Changes
Recent Product mapping changes impacted many critical reports.
- Reconciled data across SAP BW, Excel, Access, and Power BI
- Identified high-risk dependencies
- Implemented controlled changes
- Ensured continuity for business users
Data Carve-Out Impact
An upcoming carve-out impacts:
- Data sources
- Folder structures
- SAP BW environments
- Excel reports
- Power BI semantic models
I am currently:
- Assessing end-to-end impact
- Designing safe transition paths
- Preventing reporting disruption
- Protecting business-critical outputs
Preparing for AI & Long-Term Readiness
Looking ahead 5+ years, BDM 2.0 is being designed to support:
- AI model training
- Intelligent agents
- Advanced analytics
- Automation and orchestration
This requires:
- Clean, structured data
- Stable schemas
- Clear lineage
- Trusted datasets
BDM 2.0 is built with these requirements in mind.
Strategic Role & Positioning
In this phase, my role functions as a bridge between:
- Business users
- BI developers
- Data engineers
- Architecture and platform teams
I translate:
- Business needs → technical requirements
- Technical constraints → business realities
Sometimes this means:
- Challenging unrealistic expectations
- Saying no - politely and with justification
- Protecting platform integrity
How This Repository Fits in the Bigger Journey
This repository represents the strategic backbone of the ECO3 analytics journey:
Each phase is documented separately to keep clarity and focus.
Suggested Diagrams to Add (Optional – Later)
- Legacy vs BDM 2.0 Architecture
- Centralized Database Layer Model
- Data Flow: SAP → Fabric → Consumption
- AI-Ready Data Platform Concept
- Ownership & Governance Model
Confidentiality Notice
All descriptions use abstracted logic and dummy representations.
No proprietary ECO3 data, architecture diagrams, or business rules are disclosed.
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