Designing Enterprise Data Products in SAP BDC

What is an Enterprise Data Product?

In SAP BDC context:

An enterprise data product is a domain-owned, semantically harmonized, governed, reusable dataset with certified KPIs that can be consumed across analytics, AI, and APIs.

It is not just a data model — it includes:

Business semantics
Ownership
SLA
Governance
Security
Reusability

Scenario

A global enterprise wants a “Global Financial Performance” data product that:

Combines S/4 + ECC finance data
Standardizes Revenue & Margin definitions
Applies global currency conversion
Supports SAC dashboards and AI forecasting

Step-by-Step Design Framework

🔹 Step 1: Define Domain & Ownership

Identify:

Domain (Finance / Sales / HR)
Business Owner
Data Product Owner
Technical Steward

👉 Data products without ownership fail governance.

🔹 Step 2: Identify Source Systems

Example:

SAP S/4HANA
SAP ECC
External flat files or APIs

Ingest data into BDC managed data foundation.

🔹 Step 3: Build Canonical Business Entities

Instead of exposing raw tables:

Create standardized entities:

Company
Cost Center
Product
Customer
Fiscal Period

Align:

Master data
Currency
Units
Hierarchies

👉 This becomes the semantic backbone.

🔹 Step 4: Define Harmonized KPIs

Example:

Net Revenue
Gross Margin
EBITDA
Revenue Growth %

Ensure:

Single definition across regions
Centralized calculation logic
Reusable KPI framework

This avoids duplication.

🔹 Step 5: Create Analytical Models

Design:

Measures
Dimensions
Time hierarchies
Aggregation logic
Security filters

This makes the product consumption-ready.

🔹 Step 6: Apply Governance & Controls

Define:

Data quality checks
Refresh frequency (SLA)
Versioning
Role-based access control
Certification status

Enterprise trust depends on this layer.

🔹 Step 7: Enable Multi-Channel Consumption

Expose via:

SAP Analytics Cloud
APIs
AI/ML models
External BI tools

A data product should not be tied to one dashboard.

🏗️ Reference Architecture

Source Systems ↓ Data Ingestion Layer ↓ Managed Data Foundation ↓ Harmonized Business Entities ↓ KPI & Semantic Layer ↓ Certified Data Product ↓ Analytics / AI / APIs

📌 Design Principles for Interviews

✔ Domain-driven
✔ Business semantics first
✔ Reusable across use cases
✔ Governed & certified
✔ Scalable & cloud-native
✔ API-first mindset

⚠️ Common Mistakes (Good to Mention in Interview)

❌ Exposing raw tables as data products
❌ Duplicating KPI logic across domains
❌ No SLA or quality validation
❌ No ownership
❌ Tight coupling with a single report

🎯 Interview-Ready Summary

Designing enterprise data products in SAP Business Data Cloud involves creating domain-owned, semantically harmonized, governed, and reusable business entities with standardized KPIs that serve as certified, analytics-ready assets across the enterprise.

You can also checkout ebooks for SAP BDC – Quick Revision – using the link :
Part 1 : https://topmate.io/vartika_gupta11/1954785

Part 2 : https://topmate.io/vartika_gupta11/1956232

Also can schedule a mock interview either by me or my team at topmate for SAP BDC – 35+ Minutes : https://topmate.io/vartika_gupta11/1962923

You can reach out to me or follow my profile for more such helpful content : Vartika Gupta | LinkedIn