Sai Alekhya Chandramouli

Hardworking, highly motivated professional eager to lend combined knowledge and skills to enhance business performance. Operates well in both individual and team capacities, leveraging seasoned work ethic to quickly adapt to different processes and drive company objectives. Resourceful and results-driven with a passion for growth and efficiency to meet company needs and increase service value.

Project title: 

Business Analytics Models for Automobile Customer Segmentation

Applied a variety of quantitative approaches to examine a dataset of car customers.
Applied data visualization strategies to gain deeper understanding of consumer behavior.
Employed business forecasting methods to anticipate patterns and trends.
Utilized data mining techniques to obtain important information for making decisions.
Created and put into place a business intelligence system for thorough examination.
Oversaw database management systems and planned commercial data warehousing.
Developed a strong model that enables companies to make well-informed decisions in order to maximize profitability, increase car sales, and improve customer satisfaction.

• Database management: By creating a structured database with SQL Server, effective data storage and manipulation via SQL queries were made possible.
• Data Warehousing: Using Visual Studio, a thorough data warehouse was built, and dataset data was transformed and loaded for more efficient business intelligence processes.
• Visual Information Interpretation: Made use of Tableau's data visualization capabilities to create dynamic graphs and charts that help understand complex data linkages.
• Business Intelligence: Made use of Tableau to produce perceptive visuals that made trend and pattern analysis easier.
• Data mining techniques: Regression, naive Bayes classification, decision trees, and WEKA were used for thorough data mining in order to find hidden relationships and predicted insights.
• Business Forecasting: ARIMA and exponential smoothing were used to predict future trends, while Excel and WEKA were used as tools for this process.
• Quantitative Business Methods: Utilizing statistical methods such as correlation analysis and hypothesis testing

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