Lightness Cartier
I turn slow, complex data into fast, decision-ready systems.
I'm a Power BI Developer and BI Solutions Architect with 6+ years of experience building dashboards, optimizing data models, and delivering reporting systems used by business teams and leadership.
$50M+
Analytics Supported
40%+
Efficiency Improved
1000+
Dashboard Users
Data & Modeling
SQL • DAX • Data Modeling
Automation & ETL
ETL • Data Pipelines • Azure Data Factory
Reporting & Insights
Power BI • Executive Dashboards • Reporting Automation
Results
Business Impact
Key achievements and measurable results
Reduced Reporting Time by 60%
Automated manual workflows and eliminated redundant processes across enterprise reporting systems
Automated Reporting Workflows
Eliminated manual data entry with Power Query and SSIS automation, saving 15+ hours weekly
Improved Data Accuracy
Implemented governance frameworks and data quality standards ensuring 99.9% data integrity
Executive Decision Support
Built dashboards enabling real-time business decision-making for C-suite stakeholders
Portfolio
Featured Work
Selected Power BI projects built for performance, automation, and business impact
Healthcare Claims Analytics & KPI Optimization
Eliminated manual claims reporting by building an automated Power BI system with real-time KPI tracking and drill-through analysis.
Patient Trends
Real-time
Claim Processing
-60%
Denial Rate
12% to 4%
Cost/Patient
-$45
Business Problem
Manual claims reporting caused significant delays and limited visibility into patient outcomes, denial patterns, and operational bottlenecks.
Solution
Built an automated Power BI dashboard integrating SQL Server data with real-time refresh, advanced KPI tracking, and drill-through capabilities.
Fact Table
FactClaims
100M+ rows
DimPatient
Demographics
DimProvider
Facilities
DimProcedure
CPT Codes
DimDate
Time Intel
Technical Implementation
Executive Financial Performance & KPI Analytics System
Automated executive financial reporting with real-time visibility into revenue, margins, and cross-unit performance.
Revenue Visibility
Live
Margin Improvement
+15%
Business Units
12+
Reporting Time
↓80%
Business Problem
Financial reporting relied on manual processes, limiting real-time visibility into revenue, margins, and performance across business units.
Solution
Designed and implemented a Power BI executive dashboard with real-time data refresh, drill-through analytics, and mobile-optimized reporting.
Simulated enterprise-scale financial dataset for performance optimization and reporting accuracy.
Fact Table
FactFinancials
50M+ rows
DimDate
Time Intel
DimBusinessUnit
BU Hierarchy
DimRegion
Geography
DimAccount
GL Accounts
Technical Implementation
Retail Sales Forecasting & Demand Optimization System
Built a predictive analytics solution to forecast demand, optimize inventory, and uncover revenue opportunities across multiple regions.
Forecast Accuracy
94%
Revenue Impact
$2M+
Inventory Turnover
+22%
Regions
8
Business Problem
Lack of predictive analytics limited inventory planning and caused missed revenue opportunities across multiple regions.
Solution
Designed and implemented a forecasting solution using Azure ML and Power BI to predict demand, optimize inventory, and support data-driven decision-making.
Integrated forecasting outputs with structured sales and inventory data models for scalable reporting and regional analysis.
Fact Table
FactSales
25M+ rows
DimProduct
SKU Data
DimRegion
Geography
DimDate
Time Intel
DimInventory
Stock Levels
Technical Implementation
Automated ETL Pipeline & Data Processing System
Automated end-to-end data pipelines to eliminate manual reporting, improve data quality, and enable reliable, scalable analytics.
Processing Time
↓90%
Data Accuracy
99.5%
Data Sources
15+
Error Rate
<0.1%
Business Problem
Manual data preparation consumed 20+ hours weekly and introduced frequent errors, limiting reporting reliability and efficiency.
Solution
Designed and implemented an end-to-end ETL pipeline using SSIS and Power Query to automate data transformation, validation, and reporting workflows.
Centralized data pipeline integrating multiple source systems into a structured model optimized for Power BI reporting. Integrated 15+ data sources into a unified reporting pipeline for consistent and reliable analytics.
Fact Table
Centralized Data Pipeline
15+ sources rows
Data Validation
Error Logging
Transformation
Power Query M
Orchestration
SSIS Packages
Automation
Scheduled Refresh
Technical Implementation
Code
Technical Highlights
VAR CurrentSales = [Total Sales]
VAR PriorSales =
CALCULATE([Total Sales], SAMEPERIODLASTYEAR('DimDate'[Date]))
RETURN
DIVIDE(CurrentSales - PriorSales, PriorSales, 0)Used for executive dashboards to track year-over-year performance.
SELECT
provider_id,
claim_status,
COUNT(*) AS total_claims,
SUM(claim_amount) AS total_claim_amount
FROM claims
WHERE claim_date >= '2025-01-01'
GROUP BY provider_id, claim_status;Prepared aggregated data before Power BI, improving performance and reducing load time.
Capabilities
What I Build
Enterprise Power BI dashboards for Healthcare and Finance
Automated reporting pipelines that replace manual Excel workflows
Star schema data models optimized for DAX performance at scale
Self-service BI environments with row-level security and governance
Technical Expertise
Power BI
- DAX
- Data Modeling
- Dashboard Design
SQL & Data
- SQL Server
- Query Optimization
- Data Warehousing
ETL & Processing
- Power Query
- SSIS
- Data Transformation
Cloud & Tools
- Azure Data Factory
- Excel
- Python
Other SkillsMicrosoft Copilot • AI-assisted data analysis • Agile / Scrum • Jira
My Process
How I Build BI Systems
Data Ingestion
Connect SQL, APIs & cloud sources
Transformation
Cleanse & normalize with Power Query
Data Modeling
Star schema, relationships & hierarchies
KPI Development
DAX measures & time intelligence
Dashboard Design
Interactive, intuitive visuals
Deployment
Publish with RLS & auto-refresh
Performance
Power BI Performance Optimization
Diagnosed and resolved a slow Power BI report to improve scalability and user experience.
Load Time Reduction
12s → 3s
Rows Supported
Enterprise scale
Memory Reduction
Via query folding
What I Changed
- +Reduced dataset size using query folding and column filtering
- +Rewrote DAX measures to eliminate expensive context transitions
- +Added aggregation tables for high-frequency reporting views
- +Fixed relationship cardinality and removed bi-directional filters
- +Enabled incremental refresh to reduce full-reload overhead