Tech Portfolio Projects includes:

SETUP GUIDES

A comprehensive collection of step-by-step instructions to help you establish the technical foundation for your analytics portfolio projects. These guides walk you through environment setup, tool installation, and basic configurations needed to successfully complete the projects in both Essentials and Advanced categories.


ESSENTIALS LEVEL

1. Pizza Sales Analytics
An entry-level data analysis project focusing on a pizza delivery business. Learn to analyze sales patterns, popular toppings, peak ordering times, and delivery performance metrics. Perfect for beginners looking to demonstrate fundamental data visualization and basic SQL query skills.

2. Bike Shop Performance Dashboard
A visualization-focused project that transforms bike shop sales and inventory data into an interactive dashboard. Track key performance indicators like sales by model, seasonal trends, inventory turnover, and customer demographics to help a fictional bike shop make data-driven decisions.

3. Essential Sales Analytics
A foundational project covering core sales analytics concepts applicable to various industries. Practice cleaning messy sales data, creating standardized reports, identifying sales trends, and presenting actionable insights for business stakeholders.

ADVANCED LEVEL

1. Coffee Shop Sales Analytics
A more complex analytics project centered on a specialty coffee business with multiple locations. Analyze product mix, pricing effectiveness, customer loyalty patterns, and operational efficiency across different store locations.

2. Customer Churn Analysis
A predictive analytics project focused on identifying customers at risk of cancellation or non-renewal. Learn to build churn prediction models, identify key factors contributing to customer attrition, and recommend retention strategies based on data insights.

3. Price Prediction Model
An advanced machine learning project where you'll develop models to predict optimal pricing for products or services. Explore factors like competition, demand elasticity, and market conditions to build price optimization algorithms.

4. Fraud Detection Analytics
A security-focused data science project that uses anomaly detection techniques to identify potentially fraudulent transactions. Implement algorithms to flag suspicious patterns while minimizing false positives in a financial transaction dataset.

5. Car Industry Analytics
A comprehensive industry analysis project examining automotive market trends, consumer preferences, sales forecasting, and competitive positioning. Practice working with diverse data sources to create a holistic market analysis.

6. Advanced Sales Analytics
A sophisticated sales performance project incorporating multiple data sources, advanced statistical methods, and predictive modeling. Perfect for showcasing skills in sales forecasting, territory optimization, and sales funnel analysis.

7. Bank Card Analysis
A financial data project focused on credit and debit card transaction patterns, spending behavior segmentation, and product recommendation algorithms for a banking institution.