VENKAT SAI CHARAN KOVI

Results-driven Data Engineer with expertise in big data processing, ETL development, and cloud technologies (AWS, Azure, GCP). Skilled in designing scalable data pipelines, optimizing SQL performance, and implementing data governance strategies. Strong background in data warehousing, BI visualization (Tableau, Power BI), and machine learning applications. Experienced in networking, IT support, Active Directory management, and cloud security, ensuring smooth infrastructure operations. Adept at troubleshooting network issues, managing IT ticketing systems (ServiceNow), and supporting enterprise hardware deployments. Passionate about leveraging data engineering best practices and analytical solutions to enhance enterprise decision-making and healthcare analytics. Holds a Master’s in Business Analytics (Healthcare Analytics) from Lewis University and a Bachelor’s in Computer Science Engineering.

• Google IT Support – Google & Coursera
• Spark and Python for Big Data with PySpark – Udemy
• SQL for Data Analytics and Business Intelligence – Udemy
• Web Application Development - Certified by Chennai IT Training Solutions
• Programming with Python in 100 Steps - Udemy Certified
• Introduction to Algorithms and Data Structures in C++ - Udemy Certified
• Android Development for Newbies - Udemy Certified
• Fundamentals of Digital Marketing - Google Certified
• English Writing Proficiency - Certified by Aspiring Minds

• Healthcare Data Breach Analysis Using Business Intelligence Models, Led a team in developing a business intelligence and decision-making model using the Major US Health Data Breaches dataset from Kaggle to analyze breach patterns and risk factors. Directed project planning, execution, and monitoring while overseeing data collection, preprocessing, and integration using Excel and WEKA. Managed data analysis and visualization efforts using Tableau, applying quantitative business methods to derive actionable insights. Developed and implemented a database solution utilizing SQL Server and Visual Studio for efficient data storage and retrieval. Applied association rule mining and clustering techniques in WEKA to identify breach patterns and correlations. Conducted performance evaluation and validation to ensure model accuracy and reliability. Designed a data warehouse model to streamline breach data storage and analysis. Presented project findings at departmental meetings, receiving positive recognition for innovative approaches to breach prevention. Received accolades for leadership and project management, enhancing the project's impact within the academic community.
• Spam Mail Detection and Prevention at Server Side, Developed an innovative spam filtering approach integrating collaborative filtering with semantics-based text classification to enhance detection accuracy and efficiency. Implemented machine learning algorithms such as Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM) for spam classification. Designed and developed a web application prototype resembling Gmail to demonstrate the effectiveness of the proposed method. Conducted feature selection by extracting semantic meanings from text content to improve classification accuracy. Evaluated the accuracy and performance of the implemented algorithms, ensuring superior results compared to traditional spam filters. Collaborated with team members to analyze results, optimize the approach, and propose further enhancements. Applied natural language processing (NLP) techniques to improve text classification and filtering capabilities. Gained expertise in collaborative filtering methodologies and their application in spam detection. Developed proficiency in web application technologies, including HTML, CSS, and JavaScript, for building the prototype. Achieved notable results in spam detection, demonstrating improved efficiency and accuracy through the innovative approach.

Venkat Sai Charan K. Spam Mail Detection and Prevention at Server Side. Innovations in Power and Advanced Computing Technologies (i-PACT) 2019, IEEE, Vellore, India, March 22–23, 2019. DOI: 10.1109/i-PACT44901.2019.8959960. ISBN: 978-1-5386-8190-9.