Turning raw data into meaningful insights, business decisions, and intelligent solutions.

I'm a Data Analyst and aspiring Data Scientist with hands-on experience working with data using Python, SQL, Excel, Power BI, Tableau, and Machine Learning.

I enjoy transforming raw and messy datasets into clean, structured, and meaningful insights through data cleaning, exploratory data analysis, visualization, statistical analysis, and predictive modeling.

🎯 Career Focus: Data Analytics → Data Science → Machine Learning

• 📊 Data Analysis & Business Intelligence
• 🐍 Python for Data Science
• 🗄️ SQL & Database Analysis
• 📈 Data Visualization & Dashboarding
• 🤖 Machine Learning & Predictive Modeling
• 🔄 ETL & Data Transformation
• 📚 Continuously learning and building real-world projects

Raw Data
    ↓
Data Cleaning & Transformation
    ↓
Exploratory Data Analysis
    ↓
Statistical Analysis
    ↓
Visualization & Dashboarding
    ↓
Machine Learning / Predictive Modeling
    ↓
Actionable Business Insights

Data Analysis: Data Cleaning • Data Transformation • Exploratory Data Analysis • Statistical Analysis • Data Validation • Pattern Identification • Outlier Analysis • Business Metrics

Analytics & Reporting: Interactive Dashboards • KPI Tracking • Business Metrics • Data Reporting • Trend Analysis • Performance Monitoring • Data Storytelling

Machine Learning: Predictive Modeling • Classification • Regression • Model Evaluation • Feature Preparation • Train/Test Splitting • Performance Comparison

Currently building stronger foundations in end-to-end Machine Learning workflows.

ETL: Data Extraction • Data Transformation • Data Cleaning • Data Loading • Data Preparation • Workflow Development

Databases:

Git • GitHub • Jupyter Notebook • Data Analysis Workflows • Version Control

Python • SQL • Power BI • Data Analysis

• Cleaned and prepared customer data by handling missing values, duplicates, and inconsistent records.
• Analyzed customer behavior to identify patterns associated with churn and retention.
• Used SQL to segment customers based on tenure, usage, and business factors.
• Created interactive Power BI dashboards to monitor churn rate, retention rate, and customer KPIs.

🔗 Repository: github.com/pabitramanda42/FUTURE_DS_02

Python • Pandas • NumPy • Power BI

• Cleaned and transformed sales datasets.
• Analyzed sales trends, product performance, revenue, and profit.
• Built an interactive Power BI dashboard for business performance monitoring.
• Identified top-performing products, regions, and key revenue drivers.

🔗 Repository: github.com/pabitramanda42/FUTURE_DS_01

July 2026 – August 2026

• Processed 200+ records using Python, Pandas, and NumPy.
• Performed data cleaning including missing values, duplicates, and inconsistent data.
• Conducted EDA across 5+ datasets.
• Identified trends, correlations, and outliers.
• Developed and evaluated 3+ Machine Learning models using Scikit-learn.

January 2026 – July 2026

• Developed Machine Learning models achieving up to 88% accuracy on structured datasets.
• Analyzed and refined 20,000+ records through EDA and preprocessing.
• Improved data quality by approximately 25% through data preparation and cleaning.
• Created dynamic Power BI dashboards for KPI tracking and performance monitoring.

I also have experience building full-stack applications using the MERN stack, Java, REST APIs, and databases.

While my current career focus is Data Analytics and Data Science, this software development background helps me understand how analytical solutions can be integrated into real-world applications.

I'm continuously developing the skills required for modern Data Science roles:

• 📊 Advanced Data Analytics
• 🐍 Advanced Python for Data Science
• 🗄️ Advanced SQL
• 🤖 Machine Learning
• 📈 Advanced Statistics
• 🔄 End-to-End ETL Workflows
• 🚀 Machine Learning Deployment
• 🧪 Model Evaluation & Optimization
• ☁️ Cloud & MLOps fundamentals

Data Analytics
      │
      ▼
Advanced Analytics
      │
      ▼
Machine Learning
      │
      ▼
Data Science
      │
      ▼
ML Deployment & MLOps

My goal is to build practical, end-to-end data projects that demonstrate not only technical skills, but also the ability to solve real business problems.

• 📊 Data Analytics
• 🤖 Machine Learning
• 📈 Business Intelligence
• 🔍 Exploratory Data Analysis
• 🧠 Predictive Analytics
• 🔄 ETL & Data Pipelines
• 📉 Customer Analytics
• 💰 Sales & Business Analytics
• 📊 KPI & Performance Analytics
• 🚀 Machine Learning Deployment

I'm interested in collaborating on:

• Data Analytics projects
• Machine Learning projects
• Python projects
• SQL analytics projects
• Power BI / Tableau dashboards
• Open-source data projects
• Real-world business analytics problems

I enjoy taking messy datasets, finding the story hidden inside them, and turning that story into actionable insights. 📊🐍

“Data is only valuable when it helps us make better decisions.”

⭐ If you find my projects useful, feel free to explore my repositories!