1. Predictive Analysis of Bank Subscription Behavior:

Tools used : Jupiter Notebook

In this project I analyzed a marketing data set of a bank with 45,212 records and 17 variables to predict the customer subscription to term using logistic regression. I identified the key factors that affect the customer decisions and call quality. I implemented various methods to find the accurate one. This project highlights my skills in data analysis, statistical modelling, predictive analysis and strategic decision making.

•  Objective: Analyze a Portuguese bank's marketing campaign to predict and improve term deposit subscriptions through cold calling.

•  Data: Utilized a dataset of 45,212 cases with 17 variables covering client profile, account details, and call quality, targeting deposit completion.

•  Methodology: Preprocessed data by cleaning, normalizing, encoding, and oversampling; built models including Decision Tree, Logistic Regression, KNN, Random Forest, and XGBoost.

•  Key Findings: Identified significant variables impacting deposit probability and highlighted the imbalanced nature of the dataset with 11.7% successful deposits.

• Conclusion: The "Bank Marketing Case" project developed predictive models to enhance cold calling strategies for term deposits, identifying key influencing variables despite data imbalance. The findings provide actionable insights for optimizing campaigns, with future improvements involving advanced techniques and updated data to boost accuracy and conversion rates.

Gitthub Link : https://github.com/Prakashtamminedi/Data-Mining-Project

Employee Dashboard creation:

Tools Used: Excel, Tableau

In this project, I developed automated Tableau dashboards to Visualize employee performance metrics. I created real time dashboards for tracking employee performance, NPS data and customer escalations. These dashboards can be used to monitor productivity and efficiency. This project demonstrates my skills in data visualization, automation and real time data management.

• Automated Tableau Dashboards: Developed automated Tableau dashboards to visualize employee performance metrics, NPS data, and customer escalations in real-time.

• Real-time Monitoring: Created real-time dashboards enabling continuous tracking of employee performance metrics, NPS scores, and customer escalations.

• Enhanced Productivity: These dashboards serve as tools to monitor and enhance productivity and efficiency within the organization.

• Skills Demonstrated: Demonstrated proficiency in data visualization using Tableau, automation of reporting processes, and real-time data management.

• Integration with Google Sheets: Leveraged Google Sheets for dashboard creation by extracting and integrating data from Tableau, demonstrating adaptability and proficiency in utilizing different data management tools.

Github Link : https://github.com/Prakashtamminedi/Dashboard-Project

MariaDB Database Product Development:

Tools used : MariaDB

We implemented the CRUD operations on various data types and developed a transactional databased management system using MariaDB. Through this project I waws able to demonstrate the practical knowledge in using the MariaDB in real world applications. It highlights my skills in database management and administration.

•  Objective: Analyze Walmart sales data to support data-driven decision-making using MariaDB.

• Database Setup: Created a database with `store_data` and `walmart_data` tables, performing CRUD operations for data integrity.

• Technology: Utilized MariaDB for its open-source nature, MySQL compatibility, and superior performance.

• Key Analyses: Conducted markdown analysis, examined sales trends, and assessed the impact of holidays on sales.

• Data Management: Illustrated data management through entity-relationship diagrams and detailed SQL operations.

• Outcome: MariaDB facilitated insights to aid Walmart in making informed business decisions.

Github Link : https://github.com/Prakashtamminedi/ADBMS-Project