Data Analyst primarily skilled in Everything Excel–Formulas, Power Query, VBAs/MACROs.
With strong hands-on experience on SQL, Power BI, Tableau, & Python.
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Collaborative capabilities were implemented in Excel, allowing team members to input data directly via web or apps, with real-time updates reflected
in the workbook. Highlights include Interactivity, VBAs, Scalability, and more.
Click to Watch YouTube video for more details.
In this project, we wrote code in Python to collect data from PakWheels. The data was stored in a CSV file, cleaned for EDA, and visualized in Excel. Click to Watch YouTube video for a detailed description — (0:00 - 2:50) for overview.
This dashboard in Tableau shows AirBnB trends in Seattle. It helps in taking initial steps as an investment project in AirBnB apartments within the city of Seattle. The trends show the 6-bedroom apartments are very rare and yet they have the highest potential for charging higher average prices.
Bigquery, utilizing SQL, is incredible in handling massive datasets and offers cost effective scalability options. Looker Studio allows creating interactive dashboards using Google's Cloud services straight from BigQuery.
This code monitors the price of a product listed on Amazon. When price drops below a threshold an automatic email notification is generated.
Identifying KPIs using Power Bi & SQL, creating a dashboard that matches companies theme & colors, determining trends, and making recommendations to increase profit via a 10-15% hike in prices . Click to view project on Github.
This Deep Learning (DL) model predicts risk for developing diabetes from patient's health data with a precision score of 95.78%. The code also includes automatic hyperparamter optimization using Keras library. Click this link to watch a quick 3-min video in which I explain the model to a friend.
A very simple code in Python that takes user input to calculate their BMI. The user can input their weight in pounds and height in feet inches to calculate their BMI.
From a sample dataset of a pizza store, we’ll be using MySQL to query through data and find important business factors such as those as listed in the highlights. Click to view project on Github.
As part of semester project, this photo gallery app was developed and hosted on the cloud. It uses netlify.com to host frontend; render.com for backend; and MongoDB for database. It also uses GitHub to store the code and allow interaction between frontend, backend, database, and cloud.
A file processing script in Python that organizes incoming client files into correct folders and then outputs data profile of each file.
