DATA FOUNDATION

ERP & AI READINESS

We create a consistent data foundation: KPI definitions, governance as well as reporting and semantic layers – so that decisions can be prepared on a reliable basis and data requirements can be operationalized cleanly. We focus on a consistent data foundation and KPI governance.

OUTCOME

Unified KPIs instead of contradictory figures

Data quality as a process, not manual work

Single Source of Truth for BI & Analytics

TYPICAL DELIVERABLES

Data Assessment + Target State (Architecture, Priorities)

KPI/Metric Catalog incl. responsibilities and calculation logic

Canonical Model + DQ Rules + Governance Package

When clients come to us

KPIs vary by department

Numbers do not match

Master data quality slows down processes

Duplicates, missing fields, corrections

Forecast and margin pressure

Lack of transparency over costs and working capital

Growth/M&A

Multiple systems, inconsistent KPI logic

Self-Service BI

Fails due to standards and governance

Starting AI initiatives

Data is not accessible/reliable

Audit/Compliance pressure

Traceability, Data Lineage, Permissions

Typically included

Consistent

KPI definitions as well as data model and data flow design

Single Source of Truth

Development of a consistent reporting/semantic layer

Data quality rules, responsibilities (RACI) and governance setup

Integration and transformation logic

In the client tenant / client systems

Documentation and enablement

For operation and further development

Prioritization

Via roadmap/backlog (use cases & sources)

Explicitly not included*

*(unless ordered separately)

Data Science / Model Building as the main service

Hosting/operation of own data platforms outside of the client tenant

Full volume data cleansing "by hand" without DQ process

Unlimited source system connections without prioritized backlog

TYPICAL TIMEBOXES

ASSESSMENT

1-2 weeks

IMPLEMENTATION SPRINT

4-6 weeks

HYPERCARE

2 weeks

TYPICAL DELIVERABLES

Data Assessment + Target Illustration

Architecture, data flows, priorities

Power BI Semantic Model

Single-Source-of-Truth layer (stack-dependent)

KPI/Metric Catalog

Incl. definitions, owners and calculation logic

Governance Package

Roles, processes, standards + technical documentation including KPI governance.

Canonical Data Model / Domain Model + Data Quality Rules

Incl. definitions, owners and calculation logic

Roadmap/Backlog for Expansion

Use case and source prioritization