- Retail Domain: - Utilized Power BI for Overview report on store performance - Covered revenue, units sold, average basket size, GMROI, etc. - Provided insights into store performance - Developed Inventory Management model using SQL and Excel - Implemented EOQ method, reducing expiry loss by 10%- Social Media: - Created Power BI dashboards with Facebook API - Developed Python scripts for social media and ad data - Analyzed post data for optimal posting times- AWS Domain: - Worked with AWS Lambda and S3 buckets - Wrote Python scripts, saving 3+ hours per week- Web Development: - Developed Flask Apps in Python for internal use - Integrated OpenAI API for ChatGPT prompts - Used Selenium Webdriver for basic automation testing - Built Internal Apps using Django- Current Project: - Integrating WhatsApp Business API into Flask apps - Sending messages based on triggers and actions

- Hospitality Domain: - Extracted, transformed, and loaded (ETL) hospitality data using Excel - Imported data into Power BI to create an overview report - Report covered Average Room Rate, Check-ins, and Revenue trends - Forecasted Average Daily Rate (ADR) for the next calendar year, considering seasonality- Retail Domain: - Imported Retail Store Data into Microsoft SQL Management Studio (SSMS) - Conducted thorough analysis of the data - Created new tables, views, and stored procedures - Ensured proper nomenclature for data elements