
Retail Sales Root Cause Dashboard
Integrated revenue, profit, discount and delivery data to isolate root causes of declining profitability.
2.8 years of experience turning operational and business data into dashboards, analysis, KPI reporting and actionable insights across Automotive, Smart City and QSR domains. Currently working as an MIS Executive while pursuing an MBA in Business Analytics.

Clean, validate and explore business and operational datasets to identify trends, exceptions and patterns.
Build Power BI dashboards, DAX measures and KPI reporting systems for recurring business decisions.
Identify root causes, performance gaps and operational opportunities from structured analysis.
Reduce repetitive reporting work with Excel, Power Query and Python-based workflows.
Pull orders, registrations, enquiries, logs and other operational sources.
Deduplicate, reconcile, structure and validate the source data.
Use SQL and Python to identify patterns, trends and root causes.
Build Power BI dashboards and KPI reporting around the findings.
Turn the output into a clear business action or decision.

I turn operational and business data into insights that support better decisions.
Across Automotive dealership analytics, Smart City / AI data operations, and QSR customer journey analysis, my work has centered on finding signal in scattered data, structuring it and reporting it clearly enough for someone to act on.
My day-to-day toolkit includes Power BI, SQL, Python, DAX and Excel, with a focus on dashboards, KPI reporting, data validation, business analysis and automation.
I am currently completing an MBA in Business Analytics at Amrita Vishwa Vidyapeetham alongside my professional work.
Each project demonstrates a combination of analysis, visualization, business reasoning and technical execution.

Integrated revenue, profit, discount and delivery data to isolate root causes of declining profitability.

Analyzed ROI, conversion rate, cost per conversion and revenue per customer at campaign level.

Analyzed customer wait times, peak-hour demand and service throughput to identify operational efficiency opportunities.
View on GitHub →
Used RFM analysis and K-Means clustering to identify high-value customer segments and behavioral patterns.
View on GitHub →
Exploratory analysis and dashboard covering the Indian bike resale market, regional performance, inventory patterns and customer demographics.
View on GitHub →
Built an end-to-end classification workflow with XGBoost, SMOTE for class imbalance and SHAP-based explainability.
View on GitHub →Customer analytics, uplift testing and strategic reporting on transaction data.
EDA and predictive framework work for delinquency risk using GenAI tools.
Forensic data analysis and classification in Excel, presented via Tableau.
Executive data visuals and strategic questions for leadership decisions.
Cleaned and analyzed seven datasets for a social media client and presented findings.








For Data Analyst, BI Analyst and Business Analyst opportunities, reach out directly.