Tanuja Santosh Bora

Created robust ETL framework enhancing data integration and accessibility. Accounts Receivable and Payable Prediction Pipeline (MVue Project)

• Designed and implemented an ETL pipeline using DBT and Fivetran to automate data transformation and ingestion.
• Integrated Git with Fivetran, ensuring version-controlled data pipeline updates.
• Built a scalable data pipeline to move data from Data Lake to Data Warehouse to Data Mart, ensuring efficient and incremental data updates.
• Developed SQL-based transformations in DBT for structured reporting and analysis.
• Processed combined transaction data and product data to generate insights.
• Enabled dashboard creation using Data Mart, facilitating real-time business reporting.
• Developed an end-to-end ML pipeline to predict payment dates for Accounts Receivable (AR) and Accounts Payable (AP) at the invoice level.
• Extracted and processed data using Python, performing extensive data cleaning, and feature engineering.
• Designed and implemented SQL queries to retrieve, validate, and transform data from the database.
• Built and trained an XGBoost model to forecast payment dates for invoices with missing receipt data, helping clients anticipate future cash flow scenarios.
• Automated the pipeline for data ingestion, transformation, model training, and prediction, ensuring continuous updates.
• Provided financial clients with actionable insights to optimize cash flow and decision-making.

• Managed customer interactions, ensuring high satisfaction, and repeat business.
• Analyzed sales trends to predict stock demand and optimize inventory management.
• Handled financial planning, budgeting, and cost optimization to drive business growth.
• Gained hands-on experience in business operations, supply chain management, and decision-making.

• Created ML content using R and SAS, covering real-world case studies like Boston Housing Data and Customer Churn Analysis.
• Conducted SAS training sessions, teaching students data analysis, predictive modeling, and statistical techniques.
• Earned Base SAS Certification, demonstrating proficiency in data manipulation, reporting, and analytics.
• Developed structured learning materials to help students understand ML concepts, data preprocessing, and modeling techniques.