Enterprise BI Migration & Analytics Optimization
Industry - Real Estate Technology | Duration - 6 mo. | Investment: Full-stack AI solution
Challenge
A leading real estate technology company faced significant challenges with their business intelligence infrastructure:
Manual Excel-based reporting system requiring daily maintenance
Complex goal-tracking across multiple product lines
Limited visibility into real-time performance metrics
Legacy Tableau Server installation with scaling issues
Inconsistent data quality across departments
High manual effort in report generation (4-6 hours daily)
Technical Challenges
Multiple disparate data sources
Complex SQL stored procedures requiring optimization
Legacy system dependencies
Data quality inconsistencies
Need for minimal disruption during migration
Security and compliance requirements
Solution Architecture
Implemented a comprehensive BI modernization program:
Data Layer:
Optimized SQL stored procedures
Implemented automated data quality checks
Created centralized data warehouse structure
Established automated ETL pipelines
Analytics Layer:
Migrated from Tableau Server to Tableau Cloud
Designed scalable dashboard framework
Implemented row-level security
Created automated refresh schedules
Process Optimization:
Automated daily goal calculations
Built cross-product performance tracking
Implemented version control for all processes
Created automated testing framework
Implementation Phases
Discovery Phase (2 months):
Comprehensive system audit
Stakeholder interviews
Requirements gathering
Technical architecture planning
Development Phase (12 months):
Iterative dashboard development
ETL pipeline creation
Automated testing implementation
User acceptance testing
Migration Phase (4 months):
Parallel running of systems
User training
Performance optimization
Full cutover to new system
Measurable Results
Reduced report generation time from 4-6 hours to 15 minutes
Achieved 99.9% data accuracy
Eliminated 40+ hours of manual work weekly
Improved dashboard load times by 300%
Reduced system maintenance overhead by 70%
Increased user adoption by 150%
Business Impact
Enabled data-driven decision making across organization
Improved product performance visibility
Enhanced ability to identify market opportunities
Streamlined goal tracking and performance management
Reduced operational costs
Improved scalability for future growth