Tanisha Das

<p>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.<br>
Created charts.<br>
Prepared dashboards.<br>
Derived insights.</p>

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

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

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

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

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

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