Keyah Taneja

Data analyst with expertise in R, Tableau, and SQL, specializing in advanced data analysis, predictive modeling, and data visualization. Adept at optimizing processes, uncovering insights, and driving data-driven decision-making. Experienced in transforming complex datasets into actionable insights for diverse stakeholders and improving operational efficiency. Proven track record of automating workflows and enhancing reporting accuracy.

Bellabeat Fitness Device (Code)

Packages: R Studio, dplyr, plotly, lubridate, UpSetR

• Conducted exploratory data analysis on Fitbit datasets using R, cleaning and merging multi-source data to identify user activity trends, segment engagement levels, and provide actionable insights for Bellabeat's marketing strategy, leveraging advanced visualization and statistical correlation techniques

Heart Disease (Code)

Packages: R Studio, ggplot2, Hmisc, tidyverse, car

• Conducted comprehensive exploratory data analysis to build a logistic regression model using Python and R to predict heart disease outcomes, achieving 91.7% AUC and 85.7% accuracy; applied feature engineering, statistical evaluation, and visualization techniques to refine predictors and provide actionable insights for cardiovascular risk stratification.

Amazon Sales Dashboard (Link)

• Utilized Tableau to analyze 116,649 shipment records, identifying key trends in sales channels, shipping statuses, and regional performance; translated data insights into actionable strategies that enhanced decision-making and operational efficiency.

Covid-19 Dashboard (Link)

• Designed an interactive Tableau dashboard analyzing COVID-19 data across states, highlighting vaccination progress, case trends, and demographic insights to support informed decision-making.