Sneethika B

Results-driven professional with a proven track record in utilizing advanced tools such as Excel, Access, and various database query tools to streamline processes, analyze complex data sets, and drive strategic business decisions. Proficient in designing and implementing robust data warehouse architectures, optimizing SQL queries, and utilizing data visualization tools including Power BI, Tableau, and Smartsheet. Experienced with Snowflake and possesses strong data analyst skills with a foundational understanding of VBA. Successful in implementing automated reporting systems, leading data warehouse initiatives, and optimizing SQL queries for enhanced business performance. Consistently transforms raw data into actionable insights, contributing to improved operational efficiency and strategic decision-making.

• Python programming for everybody, 10/2023
• Data Warehousing, 10/2023
• Python Programming, 09/2023
• PySpark Project- End to End Real Time Project Implementation, 09/2023
• Data Engineering on Microsoft Azure, 09/2021
• Data Application Builders Workshop(DABW), 09/2020
• Azure Fundamentals, 09/2020

Improving Restaurant Establishments Using Data Mining and Outlier Detection

• The application is designed to predict the profitability and feasibility of an establishment located in a particular area.

• Gathered and analyzed data on various aspects of the restaurant industry, such as customer reviews, food quality, service, ambiance, location, and pricing, using Python and SQL.

• Applied data mining techniques such as Map Reduce, clustering, outlier detection, and linear regression analysis to identify data patterns and insights and predict the restaurant's profitability and feasibility.

• Created a complete system to examine and understand data to recognize trends and patterns in restaurant establishments.

Pharmacy Analytics Dashboard

• Conducted exploratory data analysis on a large pharmacy dataset to gain insights into medication usage and prescribing patterns.

• Cleaned and preprocessed the dataset, addressing missing values, outliers, and inconsistencies. Created interactive visualizations, such as bar charts, line graphs, heat maps, and scatter plots to showcase the pharmacy company's sales performance and prescription trends.

• Developed a geographic map visualization to identify areas of high demand for the pharmacy company's products and services.

• Identified the top-selling products and categories, providing insights for inventory management and marketing strategies.

• Visualized the sales performance of different regions and stores, highlighting areas of improvement for sales teams and store managers.

• Analyzed the impact of discounts and promotions on sales revenue, providing insights for future pricing and promotional strategies.

• Compared the sales performance of different brands and manufacturers, providing insights for partnership and collaboration opportunities.

• Discovered a correlation between certain medical conditions and product categories, providing insights for targeted advertising and cross-selling opportunities.