In this project, where I had worked on with a dataset from a Finance based company which provides financial supports to the customers by lending them money on some interests. Company wants to visualize this data to understand or predict about customer who may turn their financial health worse and the ones that won't based on different factors in dataset. This will result in reducing risk of high number of defaulters and bankruptcy.

In this Project the 100 top-rated movies from the past decade along with various pieces of information about the movie, its actors, and the voters who have rated these movies online,to find some interesting insights into these movies and their voters, using Python.

In this project , I was required to model the demand for shared bikes with the available independent variables. It will be used by the management to understand how exactly the demands vary with different features. They can accordingly manipulate the business strategy to meet the demand levels and meet the customer's expectations. Further, the model to be used in a good way for management to understand the demand dynamics of a new market.

My job was to categorise the countries using some socio-economic and health factors that determine the overall development of the country and need to suggest the countries which the CEO needs to focus on the most. The datasets containing those socio-economic factors and the corresponding data dictionary was provided to Us , This Project was Focused on Clustering and Kmeans and hierarchial clustering Method.

A online education institute wants to convert the customers visiting their website to enroll for the Course they are searching which currently is around . Using Data Processing steps like data understanding, cleaning, analyzing with the help of different python libraries, graphs and charts I had decided to use Logistic Regression to answer factors that could help them to focus on those factors that could help them in converting those leads.

In this Project, I used SQL to analyse the given data and give recommendations to RSVP Movies based on the insights. For convenience, the entire analytics process has been divided into four segments, where each segment leads to significant insights from different combinations of tables.

Here, we have a dataset from an unknown online cosmetic selling company. It is 'Click Stream Data' which is collected by tracking visitor's clicks on the website and searching for patterns within them. The data is of October and November month of 2019 where we are trying to execute 8 questions using HQL (Hive Query Language) and generating some useful insights and patterns for the company to improve their sales. Also, we are trying to understand the profit and loss for both months.

To understand the behavior and correlation of all the variables against Target varibale Survived. Note: EDA (Exploratory Data Analysis) steps will be performed to attempt a solution for given problem statement.

Here, I have used IPL(Indian Premier League) dataset of year 2008 to 2017 and using this I have answered few questions asked in University assignment like Orange and Purple Cap Holder for each year, Highest number of 4s and 6s hit by player each year, Highest batting average, highest bowling average, Toss outcome Vs Match outcome, Team performance (Away Vs Home), etc.