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Capstone Project: Enterprise Data Warehouse Analysis to Video Generation System

Capstone Project: Enterprise Data Warehouse Analysis to Video Generation System

fundae Software Inc., positioning itself as "The Revenue Intelligence Company," specializes in developing AI-powered business solutions for pharmaceutical and healthcare enterprises. The company's flagship offering is an AI Agentic Framework that leverages digital twins to automate complex revenue operations, gross-to-net calculations, and data strategy workflows. As an official ISV partner on Azure, AWS, and Salesforce platforms, fundae delivers enterprise-grade solutions within each client's VPC, ensuring data security while enabling teams to extract actionable insights from disparate systems including transaction data, regulatory documents, and market feeds. Their domain-focused approach allows pharmaceutical companies to unify investments across specialized systems, freeing human teams from repetitive data gathering tasks to focus on critical reasoning and strategic decision-making.

Project Overview

Transform complex enterprise data warehouse analytics into accessible, AI-generated video content that automatically explains metrics, trends, and business insights to stakeholders at all levels.

Business Context

Modern enterprises struggle to communicate data insights effectively across diverse stakeholder groups. While data warehouses contain valuable information, translating technical metrics into understandable narratives remains a significant challenge. This project addresses that gap by creating an automated system that converts structured data and documentation into professional video presentations.

Technical Scope

Core Deliverables

  1. Data Ingestion Pipeline: Extract and process structured tables from enterprise data warehouses
  2. AI Analysis Engine: Generate intelligent questions and answers from data patterns
  3. Visualization Generator: Create appropriate charts and graphs automatically
  4. Narrative AI System: Write clear, context-aware explanations of metrics and trends
  5. Video Assembly Platform: Combine visuals, narration, and captions into polished videos

Azure Services Architecture

  • Azure Synapse Analytics: Data warehouse integration and query processing
  • Azure Cognitive Services: Natural language generation and text-to-speech
  • Azure Machine Learning: Pattern recognition and trend analysis
  • Azure Media Services: Video encoding and streaming
  • Azure Storage: Blob storage for videos and intermediate assets
  • Azure Functions: Serverless orchestration of the pipeline

Implementation Phases

Phase 1: Foundation and Data Integration

Objectives:

  • Establish secure connections to enterprise data warehouses
  • Design metadata catalog for metric definitions
  • Implement data quality validation framework
  • Create standardized data transformation pipelines

Key Activities:

  • Configure Azure Synapse workspace and linked services
  • Build data profiling tools to understand table structures
  • Develop metric definition repository with business context
  • Create data governance and security protocols

Deliverables:

  • Functional data ingestion pipeline
  • Metric definition catalog with versioning
  • Data quality dashboard
  • Security and compliance documentation

Phase 2: AI-Powered Analysis Development

Objectives:

  • Build intelligent question generation system
  • Develop automated insight discovery engine
  • Create context-aware explanation generator
  • Implement trend and anomaly detection

Key Activities:

  • Train language models on enterprise terminology
  • Develop question templates based on metric types
  • Build statistical analysis modules for trend detection
  • Create business rule engine for contextual insights

Deliverables:

  • Question-answer generation API
  • Insight ranking algorithm
  • Trend analysis reports
  • Anomaly detection alerts

Phase 3: Visualization and Narrative Creation

Objectives:

  • Design automatic chart selection logic
  • Build narrative structure templates
  • Develop script writing AI system
  • Create visual design consistency framework

Key Activities:

  • Implement chart type selection based on data characteristics
  • Build narrative templates for different audience types
  • Train text generation models on business communication styles
  • Design visual branding and styling system

Deliverables:

  • Chart generation service
  • Narrative script templates
  • AI script writing engine
  • Visual style guide implementation

Phase 4: Video Production Pipeline

Objectives:

  • Integrate text-to-speech with appropriate voices
  • Synchronize visuals with narration timing
  • Add captions and annotations automatically
  • Implement quality assurance processes

Key Activities:

  • Configure Azure Cognitive Services Speech SDK
  • Develop timing synchronization algorithms
  • Build automated captioning system
  • Create video quality validation framework

Deliverables:

  • Automated video generation pipeline
  • Multi-language support system
  • Caption generation service
  • Video quality metrics dashboard

Phase 5: Enterprise Integration and Scaling

Objectives:

  • Deploy production-ready system
  • Implement monitoring and alerting
  • Create user feedback loops
  • Establish performance optimization

Key Activities:

  • Set up CI/CD pipelines in Azure DevOps
  • Implement Application Insights monitoring
  • Build feedback collection mechanisms
  • Optimize for cost and performance

Deliverables:

  • Production deployment
  • Monitoring dashboards
  • User feedback portal
  • Performance optimization report

Success Metrics

Technical Metrics

  • Video generation time: < 5 minutes per standard report
  • Data processing accuracy: > 99%
  • System uptime: > 99.5%
  • Cost per video: < $2

Business Metrics

  • Stakeholder comprehension scores: > 85%
  • Time to insight: 75% reduction
  • Report consumption rate: 3x increase
  • Cross-functional data literacy improvement: 40%

Expected Outcomes

Immediate Benefits

  • Democratized access to data insights
  • Reduced time for report creation
  • Improved stakeholder engagement
  • Standardized metric communication

Long-term Value

  • Enhanced data-driven culture
  • Reduced dependency on technical teams
  • Scalable insight distribution
  • Improved decision-making speed

Innovation Opportunities

Advanced Features

  • Interactive video elements
  • Real-time data updates
  • Personalized content generation
  • Multi-modal output formats

Future Expansions

  • Predictive analytics integration
  • Automated recommendation systems
  • Cross-platform distribution
  • AI-powered Q&A capabilities

This capstone project represents a significant opportunity to revolutionize how enterprises communicate data insights, making complex analytics accessible to all stakeholders through the power of generative AI and modern cloud infrastructure.