Hi! My name is Palak
About Me...
My background was originally in the field of Microbiology, having obtained a Bachelor of Science from Gujarat University and over 10 years of experience in laboratory analysis. This cultivated my curiosity for patterns and problem-solving, leading to a transition into the world of Data Science and Quality Assurance. As a Data Analyst, I’m passionate about leveraging data visualization, reporting, and business intelligence tools to improve operational efficiency and support strategic decision-making. I bring a scientific mindset and analytical rigor to every project, and am eager to contribute to organizations making smarter, data-driven decisions.
Skills...
Python
SQL
Tableau
Microsoft Excel
Microsoft PowerBI
Snowflake AI
Projects...
Predicting Instacart Purchases
Using open-source data from Kaggle and the Jupyter notebook, created a model a model that predicts which previously purchased products will be in a user’s next order.
Customer Churn-rate Analysis
Using data from a csv file representative of a telecom company, utilized Microsoft PowerBI to create a dashboard that analyzes customer churn rate based on variables such as Gender, age group, contract type, Tenure, etc.
SQL Customer Sales Exploratory Data Analysis
Used SQL in order to explore sales data and performed RFM analyses. The final segmentation dashboard as well as the SQL file are available on the GitHub repository.
Python Customer Lifetime Value (CLV) Analysis
Used the Pandas, Matplotlib and Seaborn Python libraries in order to perform CLV analysis on a Kaggle dataset.
kNN Iris Data Set Classification
Exploring the iris dataset and learned about kNN using Python.
Predicting Instacart Purchases
Using open-source data from Kaggle and the Jupyter notebook, created a model a model that predicts which previously purchased products will be in a user’s next order.
Customer Churn-rate Analysis
Using data from a csv file representative of a telecom company, utilized Microsoft PowerBI to create a dashboard that analyzes customer churn rate based on variables such as Gender, age group, contract type, Tenure, etc.
SQL Customer Sales Exploratory Data Analysis
Used SQL in order to explore sales data and performed RFM analyses. The final segmentation dashboard as well as the SQL file are available on the GitHub repository.
Python Customer Lifetime Value (CLV) Analysis
Used the Pandas, Matplotlib and Seaborn Python libraries in order to perform CLV analysis on a Kaggle dataset.
kNN Iris Data Set Classification
Exploring the iris dataset and learned about kNN using Python.
