I'm skilled in Tableau, Power BI, Excel, SQL, and Python. Currently, I'm training as a Data science at AlmaBetter, specializing in Python, SQL, & machine learning. I've worked on projects like banking data analysis, adverse event reporting, and Supply chain. Previously, I work as conferences coordinator at OMICS International and also interned as a Data Analyst at Psyliq. I hold a Master's in ECE and a Bachelor's in Instrumentation and Control. In my spare time, I enjoy writeing blog, making posters.
0 + Projects completed
AlmaBetter offers data science and web development courses with "pay after you land your dream job" model.
OMICS International is an Open Access publisher that publishes over 700 peer-reviewed journals across various fields like clinical, medical, and life sciences. They also host scholarly conferences.
Grade: 8.83 CGPA
Grade: 7.94 CGPA
Below are the sample Data Analytics projects on SQL, Python, Power BI & ML.
Analysis enhances banking decisions by leveraging transaction data for insights and predictive modeling.
Crafted dynamic HR Analytics Dashboard in Power BI, empowering informed decision-making and optimizing workforce strategies.
Developed dynamic Online Sales Dashboard in Power BI for General Store, enabling real-time insights nationwide.
Analysis of 64,500 food safety records revealed trends, risks, and demographic insights for public health.
Tableau visualizations analyze hotel bookings: hotel-wise, distribution channels, cancellations, time trends, guests, and revenue.
Explore IPL data match insights, player analysis, team performance through engaging Tableau visualizations revealing trends and stories.
Transformed supply chain insights with Excel, correlating consumer behavior and operations for strategic decision-making.
Interactive tool tracks India's online sales with diverse visualizations, user-driven parameters, and drill-down functionality.
Analyzed hotel bookings with Excel, created pivot tables, and developed a data dashboard.
Enhanced bike-sharing program efficiency in Seoul by predicting rental demand through machine learning analysis.
SVM outperformed other models, achieving 96% accuracy, aiding mobile companies in competitive pricing decisions.
Predict Yes Bank's monthly closing prices using Ridge Regression, Random Forest, and XGBoost models.
Explore hotel booking trends, preferences, and factors influencing bookings through thorough EDA and visualizations.
The system integrates Python, MySQL, and Power BI for data generation, storage, visualization, and informed decision-making.
Below are the details to reach out to me!
Bihar, India