Tanisha Das

Did customer analysis on Bangalore Zomato dataset from the view point of a customer who shifted to Bangalore and wants to know about their food and restaurant culture.
Created charts.
Prepared dashboards.
Derived insights.

Successfully prepared an interactive dashboard using Tableau.
Implemented filter actions to enable dynamic region-wise profit analysis, enhancing user experience.
Employed parameter actions for icons to provide interactive sales analysis, allowing users to explore data intuitively.
Utilized data visualization techniques to present insights effectively and engage stakeholders.

Designed and developed an interactive Customer Churn Dashboard using Power BI, providing critical insights on customer retention.
Analyzed customer data to identify churn patterns and factors influencing customer attrition.
Incorporated key performance indicators (KPIs) relevant to customer retention in the dashboard.

Undertook a profound analysis of "Crimes Against Women in India (2001-2014)" to shed light on the situation of women in our society.
Leveraged MySQL queries to extract and analyze relevant data related to crimes against women.
Utilized Microsoft Excel for advanced data manipulation and insightful visualizations to present the findings effectively.
Addressed the pressing issue of women's safety in India, aiming to create awareness and promote positive change through data insights.

Conducted an in-depth analysis of the Weather dataset to explore factors impacting the Temperature of Szeged, Hungary.
Utilized Linear Regression in Python to derive valuable insights and correlations.
Employed data visualization techniques to present findings in a clear and concise manner.
Demonstrated proficiency in Python programming, statistical analysis, and data modelling.

Utilized Logistic Regression in Python to analyze the Social Network Ad dataset and predict customer behaviour.
Successfully identified customers more likely to purchase Ads based on the analysis.
Conducted data pre-processing and feature engineering to optimize the dataset for modelling.
Developed and implemented the Logistic Regression model to achieve accurate predictions.
Communicated the findings and predictions effectively to stakeholders.

Leveraged data analysis and visualization skills to prepare informative dashboards.
Conducted trend analysis on call center data, resulting in actionable insights to enhance operations and customer satisfaction.
Explored customer retention metrics, identifying opportunities to improve retention rates and enhance customer loyalty.
Examined diversity and inclusion data, providing valuable insights to promote a more inclusive work environment.
Utilized data visualization tools to present findings effectively and engage stakeholders.
Gained hands-on experience in data interpretation and dashboard creation.