GANDHI SIRIVESHI

Logical Data Analyst is skilled in requirement analysis, and database management. Self-directed and proactive professional with 2 years of vast experience collecting, cleaning, and interpreting data sets. Natural problem-solver possessing a strong cross-functional understanding of information technology and business processes. Skills in SQL, Python, Excel, Power BI, Azure Data Factory, Azure SQL Server.

• EDA on e-com Myntra Fashion Clothing: Performed data cleansing and manipulation on Myntra e-com dataset to perform Exploratory Data Analysis, to understand the customer buying behavior, Performed univariate and bivariate analysis on variables to bring out the correlation between different parameters, Top 3 factors affecting the purchasing behavior are Colour, Price and total number of product images, Used visualization to observe the effect of parameters such as number of images, price, primary color on overall data
• Exploratory Data Analysis on Crop Production: The data is an open source dataset on State-wise Crop Production in India at kaggle for 1997 to 2015 having 246091 records and 7 variables, Evaluated and performed Exploratory Data Analysis to bring insights into Indian agriculture status: state-wise, district-wise, crop-wise, area-wise and levels of productions, Data Preparation and Data Cleaning using pandas and numpy library and Visualization using matplotlib and seaborn, Analyzed each variable, the trend and relationship among them, thus creating a number of problem statements to discover patterns and to spot anomalies
• HR Business Intelligence Project (Power BI): Used Python to understand business parameters and factors affecting the attrition, identified ways to improve the business, Exploratory Data Analysis, in order to get the insights about the dataset having 1470 records., Extensive use of Python libraries such as pandas, and NumPy to perform univariate and bivariate analysis, to find out the correlation between different factors affecting the business, Top 3 factors affecting the attrition behaviors for the company - Life Sciences, age of 25-34, Count of Males, Analyzed each variable and explored the identified KBR's to get KPI's responsible to achieve the desired goal, Performed correlation analysis in Python on quantitative variables to understand the effect of one on the other

• Learning Path in Data Science | Board Infinity | 2021-22
• Learning Path in Data Science | Almabetter | 2022-23
• Participated in the Python Hackathon Organized By Board Infinity.
• National Cadet Corps Army wing 2 (T)

• The Star Employee in Kfintech Private Limited in 2022.