I'm a Behavioral Scientist and Data Analyst passionate about
transforming data into actionable insights. I bridge the gap
between human behavior and data science, combining psychological
expertise with technical skills to solve real-world problems.
🎯 What I Do
I specialize in:
📊 Data Analysis & Visualization: SQL, Power BI, Tableau
🧠 Behavioral Research: Psychometrics, Statistical Modeling,
Experimental Design
🏗️ Data Engineering: Building data warehouses, ETL pipelines,
dimensional modeling
📈 Business Intelligence: Creating dashboards and analytical
solutions
📘 View my full project planning in Notion
💻 View my GitHub Repository
Comprehensive sales dashboard analysis showcasing advanced data
analytics capabilities across product performance, temporal
trends, and strategic business recommendations. This analysis
provides actionable insights for optimizing sales strategy and
revenue generation through descriptive analytics, time series
analysis, and customer segmentation.
End-to-end warehouse project integrating CRM and ERP CSV files
into Bronze, Silver, and Gold layers. I designed a star-schema
sales data mart, created a customer analytics view, and built
Tableau dashboards to surface customer value, segments, and
long-term sales trends.
SQL × Exploratory Data Analysis
In this project I use pure SQL to explore a sales data warehouse
built from CRM and ERP sources. I profile tables and columns,
validate date and customer coverage, compute core business KPIs,
and analyze how revenue is distributed across customers. The EDA
sets the analytical foundation for the star‑schema data mart and
Tableau dashboards developed in the full data warehouse project.
In this project I extend a star‑schema sales data warehouse to perform
advanced analytics directly in SQL. I use window functions, CTEs, and
segmentation logic to analyze time‑series trends, compare products to their
historical baselines, quantify category contribution to total revenue, and
segment customers into VIP, Regular, and New groups. The project shows how
well‑structured SQL alone can answer complex business questions that are
usually handled in BI tools or notebooks.
This project demonstrates robust SQL querying techniques to derive
meaningful insights from the Car Dekho automotive database. The
findings provide a clear picture of car inventory trends, fuel
preferences over the years, and potential growth or decline in car
availability.
This project analyzes COVID-19 data to understand the distribution
and impact of the pandemic across different countries. It focuses
on total cases and deaths and visualizes the data to highlight
which countries have been most affected.
Python × Jupyter Notebook
This project analyzes historical CO2 emissions alongside GDP and
population data to understand the impact of economic development
on environmental health. It also explores the effectiveness of
global efforts to manage carbon footprints.
This project conducts a comprehensive psychometric evaluation using
the Item Response Theory framework. The 3-parameter logistic model
is applied to estimate and analyze participants' abilities on a
learning test dataset.
This project analyzes the nutritional content of various cereal
products to identify patterns in healthiness and compare
nutritional value. By examining relationships between nutritional
factors and health standards, it highlights healthier choices for
consumers.
This project involves a longitudinal analysis of the development
of cognitive and socio-emotional skills in adolescents aged 11 to
15. The findings inform educators and policymakers about which
areas may require additional support during these crucial years of
development.