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Data Assessment · Master Data · DMOne™ Cleansing · Semantic Foundation™ · Data Quality · AI Enablement

AI-Ready Data &
Semantic Foundation™

Clean, governed Oracle data that AI can act on

Most AI initiatives on Oracle stall for the same reason: nobody can vouch for the data underneath them. eAppSys cleanses and reconciles the data with DMOne™, then applies Semantic Foundation™ so that finance, HR and operational terms are defined once and used consistently across reporting, analytics and AI agents.

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Home › Data & AI › AI-Ready Data & Semantic Foundation™

Data Foundation

AI-Ready Data & Semantic Foundation™ — Service Areas

eAppSys delivers AI-ready data across six service areas. Engagements usually start with an assessment and progress through cleansing to a semantic layer that AI and reporting share.

AI-ready data infrastructure and semantic foundation framework

AI-Readiness Data Assessment

A fixed-scope review of whether your Oracle data is fit to drive AI, with a prioritised remediation plan.

  • Profiling of master and transactional data across Fusion and EBS
  • Duplicate, completeness and consistency scoring by domain
  • Ownership, stewardship and lineage gaps identified
  • Remediation backlog ranked by AI use-case dependency
  • Fixed-price proposal for the cleansing and semantic work that follows

Master Data Management

Suppliers, customers, employees, items and chart of accounts governed as single, owned records.

  • Golden-record design for supplier, customer, worker and item domains
  • Survivorship rules and match thresholds agreed with data owners
  • Fusion as the master, with controlled synchronisation to satellite systems
  • Chart of accounts and enterprise structure rationalisation
  • Ongoing stewardship model and data-owner RACI

Data Cleansing & Reconciliation

DMOne™ cleanses, validates and reconciles data with a full audit trail from source to target.

  • Rule-based cleansing with exception queues for data owners
  • Deduplication and matching across legacy sources
  • Validation against Fusion configuration before load
  • Reconciliation of record counts and balances to source
  • Audit evidence retained for internal and external audit

Data Cleansing & Reconciliation

Semantic Foundation™

Business definitions — revenue, headcount, cost centre, supplier spend — defined once and applied consistently to OTBI, BI Publisher, Fusion Data Intelligence and AI agents.

  • Business glossary agreed with finance and HR owners
  • Metric and dimension definitions mapped to Fusion subject areas
  • One semantic model consumed by reporting and by AI agents
  • Conflicting definitions across legacy reports resolved and retired
  • Change control so a definition changes in one place only

Data Quality & Governance

Controls that keep the data clean after go-live rather than a one-off clean-up.

  • Data quality rules monitored continuously against Fusion
  • Steward dashboards with exceptions routed to owners
  • Data ownership, policies and standards documented
  • UK GDPR retention and minimisation applied to HCM data
  • Quarterly quality reporting to the data governance board

Data Quality & Governance

AI Enablement on Oracle Fusion

Switching on embedded Fusion AI and building agents only once the data they read is trusted.

  • Embedded AI features activated by process area
  • Fusion AI Agent Studio agents grounded in the semantic model
  • Fusion Data Intelligence as the analytics and AI data layer
  • Use-case sequencing based on data readiness, not enthusiasm
  • Handover to managed data and AI operations

AI Enablement on Oracle Fusion

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Delivery Approach

Delivery Approach

eAppSys delivers data foundation engagements in a structured phased approach — clear outputs and decision gates at every stage.

 
 
01

Assess

Data profiling, ownership review, AI use-case dependency map, fixed-price remediation proposal

02

Cleanse

DMOne™ cleansing, deduplication and reconciliation with data-owner sign-off by domain

03

Define

Semantic Foundation™ glossary, metric definitions and semantic model agreed and built

04

Sustain

Quality monitoring, stewardship and governance in place; transition to managed service

Why eAppSys

Your Data Foundation Partner

Data First, AI Second

eAppSys will not build an agent on data it cannot reconcile. The sequence is assessment, cleansing, semantic definition, then AI — because that is the order in which the results hold up.

Built on DMOne™

The same platform used for Oracle Fusion migrations handles cleansing and reconciliation, so the rules, audit trail and exception handling are proven rather than assembled for the engagement.

One Definition, Every Consumer

Semantic Foundation™ means a report, a dashboard and an AI agent give the same answer to the same question, and a definition changes in one place.

Fixed Price and Scope

Assessment, cleansing and semantic work are each scoped and priced at signature. Ongoing governance moves to a managed service with agreed SLAs.
Common Questions

Frequently Asked Questions

What is Semantic Foundation™?
Semantic Foundation™ is the eAppSys approach and toolset for defining business terms once — what counts as revenue, headcount, active supplier — and applying those definitions consistently across Oracle Fusion reporting, analytics and AI agents. It removes the situation where three reports give three different numbers for the same measure.
No. The assessment and cleansing work applies to Oracle E-Business Suite and to Fusion. Where a Fusion migration is planned, cleansing the data beforehand reduces migration risk and the semantic model carries across.
Typically four to six weeks for a single pillar such as HCM or Financials, depending on the number of source systems. It produces a scored data profile, a ranked remediation backlog and a fixed-price proposal for the next phase.
Fusion Data Intelligence provides the data pipeline and analytics platform. Semantic Foundation™ provides the agreed business definitions that sit on top of it, so the FDI subject areas, custom reports and AI agents share one meaning.
Data quality does not stay fixed on its own. eAppSys offers managed data and AI services with quality monitoring, stewardship support and semantic model maintenance under SLAs.
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