Lego Market Research Framework:
- Developed an effective framework to conduct market research in order to meet the targets set by the management to deal with the effects of the COVID-19 Pandemic.
- Developed a strategy to boost awareness about their initiative of using recycled plastic in order to produce their bricks as opposed to chemicals that harm the environment.
- Produced framework to perform multiple multivariate statistical analysis techniques to obtain insights about LEGO and implement the strategy as efficiently and effectively as possible.
World Bank default predictions:
- Applied various Data Classification techniques to predict whether a given banker would default or not.
- Generated a model, using R programming language, such that it was able to predict the correct outcome with an accuracy of 90.3%.
Student Performance Analysis:
- Applied several multivariate statistical techniques such as multiple linear regression to produce a model that can help predict how a student is likely to perform in a given exam.
- Generated a model that was able to predict the performance with an RMSE OF 3.521 and a normalized RMSE of 0.176.
British Airways Predictive and Sentiment Analysis:
- Conducted web scraping to obtain data, namely British Airways customer reviews from AirlineQuality.
- Generated a model that was able to predict if a given customer was going to book a ticket with an accuracy of 84.37%.
- Conducted Sentiment Analysis to determine what consumers associated the most with both positive and negative experiences in their travel.
Tata Group Financial Analysis:
- Performed data analysis and cleaning using Power-BI.
- Acquired key insights to develop an effective strategy to improve the financial performance of the organization.
- Determined the best and worst performing products & regions to better inform strategic decision making.
- Communicated findings to relevant stakeholders so that strategies can be implemented to boost ROI and improve performance.