Deepa Palariya

Detail-oriented Business Analytics graduate student seeking opportunities to leverage strong analytical, critical thinking, and problem-solving skills for driving business growth and efficiency. Proficient in data analysis, reporting, and management, with a solid understanding of database systems.

Strategic Safety Solutions: A Data-Driven Approach to Vehicle Design (RDBMS): 

• Developed an RDBMS using Microsoft SQL Server for vehicle safety analysis.
• Utilized SSIS for efficient data loading and transformation.
• Conducted OLAP analysis with KPIs to extract safety insights.
• Created comprehensive reports with SSRS and interactive dashboards with Power BI.
• Leveraged MSSQL, MS Access, ETL (SSIS), and reporting tools (SSRS, Power BI).

Energy Consumption/Production: Time Series Forecasting (Python/R/ML/SAS):

• Conducted predictive analysis to forecast energy consumption and production trends in the United States, spanning 1973 to 2017.
• Utilized Python and R for data cleaning and preprocessing, identifying monthly seasonality.
• Employed machine learning models including SARIMA, Exponential Smoothing, RNN, LSTM, GRU, and XGBoost, exhibiting higher accuracy.
• Evaluated model performance using MAE and MSE metrics, showcasing ability to handle complex patterns.
  Incorporated economic variables using SAS, enhancing forecast precision and accuracy.
• Incorporated economic variables using SAS, enhancing forecast precision and accuracy.

Gemstone Price Prediction (SAS):

• Utilized SAS software for predictive analysis, employing Multiple Linear Regression, CART, and Neural Network techniques.
• Predicted prices for 27,000 cubic zirconia gemstones.
• Successfully identified profitable stones and key price- influencing factors.

• Power BI: Certification issued by PwC and Forage
• Crash Course on Python: Certification authorized by Google (Coursera)
• SAS (Programming & Visual Analytics): Issued by SAS