I'm a business-driven Data Analyst specializing in Star/Snowflake dimensional modeling, DAX time-intelligence frameworks, advanced relational SQL, and AI-augmented analytics workflows (FastMCP + Claude). Focused on solving revenue leakage, credit risk, operational transit bottlenecks, and retention dynamics.
Power BI Desktop, DAX Studio, Tabular Modeling, Power Query (M), Advanced Excel Power Pivot (xVelocity Engine), Executive UI Layouts.
PostgreSQL, MySQL, Complex Joins, CTEs, Window Functions (DENSE_RANK, LAG/LEAD), Star & Snowflake Schema Architecture.
Pandas, NumPy, Seaborn, Matplotlib, Exploratory Data Analysis (EDA), Cohort Analysis, Correlation Matrices, Jupyter Notebook.
FastMCP Claude Analytics Servers, Automated Forensic Analysis, LLM Prompt Engineering, Git Version Control, GitHub Open-Source.
Each project features full data pipelines, clean dimensional schemas, live dashboards, and verifiable commercial impact.
Cleaned raw loan data via Python, engineered 37 validated SQL queries for DTI & default ratios, and built a 3-page Power BI dashboard isolating capital adequacy.
Modeled 37.9K transactional logs into an enterprise forensic model with a custom FastMCP server generating real-time AI anomaly narratives.
Engineered an interactive household cash-flow suite with dynamic SVG linear gauge indicators and automated 30% savings threshold tracking.
Modeled 60,400 orders in-memory inside Excel with zero external BI dependencies, designing 25+ DAX calculated measures and territory drilldowns.
Orchestrated a relational transit model tracking 6,585 passenger trips with AI-assisted capacity diagnostic analysis for peak congestion corridors.
Synthesized 149K POS transactions and benchmarked 14 Indian metro markets using a 10-query SQL framework (DENSE_RANK, LAG) to rank expansion targets.
Evaluated 10,000 subscribers and modeled tenure cohorts, uncovering months 1-12 as the vulnerability window with 48%+ contract churn.
Modeled 400K ad logs across Facebook & Instagram for a $2.54M spend, proving Stories format outperforms Feed placements with a 5.69% CVR.
24-page analytical BI platform supported by 11 dimensions and 12 fact tables, formulating an actionable RM799K management value pipeline.
Diagnosed attrition patterns across 2,925 employee records, utilizing automated DAX rule engines to isolate 144 promotion-ready and 234 retrenchment-review staff.