Venkat Sai Charan Kovi

Results-driven Data Engineer with a strong track record in delivering high-quality data solutions. Expertise in big data processing frameworks like Hadoop and Apache Spark, complemented by advanced SQL management and data visualization skills using Tableau. Known for outstanding problem-solving capabilities and effective collaboration in fast-paced environments, leading innovative initiatives that enhance operational efficiency. Dedicated to utilizing technical proficiency to support organizational objectives and improve decision-making processes.

• Google IT Support by Google on Coursera
• Udemy Spark and Python for Big Data with PySpark
• Udemy SQL-MySQL for data Analytics and Business Intelligence
• 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

English, Full Professional

Healthcare data breach analysis using business intelligence models, Led a team in developing a comprehensive business intelligence and decision-making model utilizing the Major US Health Data Breaches dataset from Kaggle. The project aimed to address the increasing threat of data breaches in the healthcare industry through the application of various business intelligence techniques and tools., Leading the team in project planning, execution, and monitoring., Conducting data collection and exploration, as well as preprocessing and integration using Excel and WEKA., Overseeing data analysis and visualization efforts, utilizing quantitative business methods and tools like Tableau., Managing database development and implementation using SQL Server and Visual Studio., Applying association rule mining and clustering techniques using WEKA for pattern identification., Conducting performance evaluation and validation to ensure model accuracy and reliability., Proficiency in data analysis and visualization tools such as Excel, Tableau, and WEKA., Strong command of database management systems, particularly SQL Server., Experience in business intelligence methodologies and techniques., Familiarity with data preprocessing and integration techniques., Knowledge of statistical analysis and predictive modeling., Excellent leadership, communication, and project management skills., Development of a robust business intelligence model providing invaluable insights into breach patterns and risk factors within the healthcare industry., Successful identification of trends and correlations in breach data, empowering proactive measures for breach prevention., Implementation of an efficient data warehouse model, streamlining the storage and analysis of breach data., Presentation of project findings at departmental meetings, receiving positive feedback and recognition for innovative approaches to breach prevention., Receipt of accolades for leadership and project management skills, further enhancing the project's success and recognition within the academic community. Spam Mail Detection and Prevention at Server Side, Developed an innovative approach to combat spam emails by proposing a collaborative filtering strategy combined with semantics-based text classification technology. The project aimed to address the inefficiencies in current spam filtering methods caused by the vast size of vector space and the need for extensive computation., Contributing to the conceptualization and development of the collaborative filtering approach with semantics-based text classification., Participating in the selection of feature terms derived from semantic meanings of text content., Implementing machine learning algorithms such as Latent Dirichlet Allocation (LDA) and Support Vector Machine (SVM) for spam classification., Designing and developing a web application prototype resembling Gmail to demonstrate the effectiveness of the proposed approach., Evaluating the accuracy and performance of the implemented algorithms and collaborative filtering strategy., Collaborating with team members to analyze results, draw conclusions, and propose further enhancements to the approach., Proficiency in machine learning algorithms, particularly LDA and SVM., Experience in natural language processing and text classification techniques., Knowledge of web application development using relevant technologies (e.g., HTML, CSS, JavaScript)., Familiarity with collaborative filtering principles and methodologies., Strong analytical and problem-solving skills., Excellent communication and teamwork abilities., Notable results and achievements in spam email detection through innovative integration of semantics-based text classification and collaborative filtering., Development and successful implementation of a more efficient detection method., Careful selection and utilization of semantic feature terms to streamline the classification process, leading to improved accuracy., Creation of a functional web application prototype resembling Gmail, demonstrating the practicality of the approach., Rigorous evaluation confirming superior performance compared to traditional methods.

Spam Mail Detection and Prevention at Server Side, Innovations in Power and Advanced Computing Technologies (i-PACT) 2019, 03/22/19, Vellore, India, IEEE (Institute of Electrical and Electronics Engineers)

• Worked as a member of Community Development Club, 02/2016 - 11/2017
• Attended a 2-day workshop on Android Development at Sathyabama Institute of Science & Technology, 08/2015
• Visit to a Government school for the purpose of community service, 02/2017
• Participated in blood donation camp - Gleneagles global health city, 05/2018

Venkat Sai Charan K. Spam Mail Detection and Prevention at Server Side. In Proceedings of the Innovations in Power and Advanced Computing Technologies (i-PACT) 2019, sponsored by IEEE(Institute of Electrical and Electronics Engineers). Vellore, India. 22-23 March 2019, IEEE Xplore, [DOI: 10.1109/i-PACT44901.2019.8959960],[ISBN: 978-1-5386-8190-9].

https://ieeexplore.ieee.org/document/8959960