KoutroubisLLC.com - Oracle OAC AI Assistant

Oracle Analytics Cloud AI Assistant

Unlock the transformative power of Oracle AI Assistant with our comprehensive, full-cycle implementation and optimization services. Our proven project plan guides your organization from initial environment assessment through to advanced automation—ensuring every phase is tailored to your unique data landscape and business goals. With expertise in Oracle Analytics Cloud and Fusion Data Intelligence, we evaluate your readiness, configure robust AI solutions, create rich data dictionaries, and fine-tune for peak performance. From defining business-centric analytics to enabling seamless natural-language insights and advanced optimization, our team delivers measurable value, step-by-step, across every phase. Discover a smarter, more agile organization with Oracle AI Assistant powering your data-driven future.

Phase 1: Assessment and Readiness Review

Estimated Duration: 1.5 to 2 weeks

Objectives:
Evaluate current Oracle Analytics Cloud and Fusion Data Intelligence environments to establish prerequisites for AIA setup.

Key Activities:

Review data architecture, integrations, and user permissions.
Identify use cases and role‑based analytics needs.
Assess metadata readiness and data quality.
Prepare the readiness and gap assessment report.

Deliverables:

Readiness Assessment Report
Implementation Roadmap and Timeline
Gap and Risk Analysis

Phase 2: System Setup and Configuration

Estimated Duration: 1 to 1.5 weeks

Objectives:
Deploy AIA within OAC and integrate it with Oracle Fusion Data Intelligence and related data sources.

Key Activities:

Enable AIA services in the OAC environment.
Configure connections to Fusion Data Intelligence datasets.
Set up user access, roles, and security policies.
Validate technical connectivity and single sign‑on setup.

Deliverables:

Configured AIA instance integrated with Fusion Data Intelligence.
Technical and Access Configuration Documentation.

Phase 3: Data Dictionary Creation

Estimated Duration: 2 to 3 weeks

Objectives:
Establish a comprehensive data dictionary to define the core business entities, attributes, and relationships for AIA processing.

Key Activities:

Catalog Fusion ERP, HCM, SCM, and CX subject areas.
Define naming conventions and standardized metrics.
Align with Oracle Data Catalog standards.
Publish dictionary within the OAC semantic model.

Deliverables:

Complete Data Dictionary.
Metadata Model Published to AIA.

Phase 4: Custom Data Descriptions Development

Estimated Duration: 1 to 1.5 weeks

Objectives:
Enhance AI comprehension and business context using natural‑language data descriptions.

Key Activities:

Create narrative descriptions for datasets, measures, and dimensions.
Align language with business terminology and user phrasing.
Validate via prompt testing and user review sessions.

Deliverables:

Data Description Catalog.

Updated Business Glossary for AIA.

Phase 5: Synonym Definitions and Data Set Indexing

Estimated Duration: 1 week

Objectives:
Expand AIA’s natural‑language vocabulary through synonyms and optimize dataset indexing for better query accuracy.

Key Activities:

Map synonyms for KPIs and business terms.
Configure AIA indexing and categorization rules.
Test semantic search and context recognition.

Deliverables:

Synonym Dictionary.
Indexed and Validated Data Sets.

Phase 6: Advanced Data Preparation and Fine‑Tuning

Estimated Duration: 2 to 3 weeks

Objectives:
Refine AIA’s performance through advanced data handling, model calibration, and query optimization.

Key Activities:

Build calculated fields and transformations.
Integrate machine learning or predictive models if applicable.
Calibrate query handling, caching, and result generation.
Conduct UAT and performance benchmarking.

Deliverables:

Fine‑Tuned AIA Environment.
Performance Optimization Report.
Final User Training and Adoption Plan.

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