Passionate professional and love to deep dive in data.

👋 Hi there! I'm Pratik Barjatya, a passionate data engineer and machine learning enthusiast. I enjoy working with big data technologies and building scalable data pipelines to extract insights from massive datasets.

🚀 As a tech enthusiast, I love exploring emerging technologies and leveraging them to solve real-world challenges. From data ingestion and processing to designing efficient data architectures, I thrive on turning complex data problems into actionable solutions.

💻 My GitHub repositories showcase my work in data engineering, where I share projects, code snippets, and best practices related to data processing, ETL, and data integration. Feel free to explore and collaborate on these projects—I'm always open to new ideas and collaborations!

📚 When I'm not coding or tinkering with data, you'll find me diving into books and articles on the latest trends in data engineering and machine learning. I believe in the power of continuous learning and enjoy staying up-to-date with the ever-evolving tech landscape.

By Nature, I am keen to explore untapped areas, research and build applications. Willing to learn and being available as a mentor for the one who wants to explore this field.

Strong believer in giving back to community and running Learn-On-Go

Knowledge sharing space Data Engineering

My portfolio is a representation of all that I have learned and accomplished as a Techie student. The articles and projects you will see in this portfolio show how my knowledge and experience have evolved over time.

Checkout my blog - https://pratikbarjatya.medium.com Visit my website - https://pratikbarjatya.github.io

• Data Engineering - Python | PySpark | NiFi | Airflow
• Machine Learning
• ELK Stack
• NLP Deep Learning
• Statistics
• AWS EMR, EC2, S3, RedShift, Athena, Glue, Sagemaker
• Data Visualisation
• SQL, NoSQL, MySQL
• Tableau

Data Engineering

• Why Digital Businesses Need to Be Data-Driven

• Key Trends and Challenges in Data Engineering in 2023

• Top Courses to Become a Data Engineer in 2023

• Introduction to Data Warehousing in 2023

• Top 10 Must-Know Data Engineering Tools for 2023

• 10 Fantastic Books for Data Engineering: A Must-Read List

• Interview Preparation: Top SQL Queries and Solutions for Data Engineers and Data Analyst

• Using NoSQL Databases for Big Data Storage and Retrieval

• Top 5 Open Source Data Catalogs for Effective Data Management

• Unlock the Power of Your Data Pipeline with Streaming Data Ingestion, Data Warehousing and Feature Extraction!

• Building a Data Ingestion System Using Apache NiFi

• Implementing a Data Lake and Data Ingestion System with CDC Pipeline Using Kafka and Spark

• Overview of Parquet and Why It Gels with PySpark

• Exploring the Apache ORC File Format: Advantages, Use Cases, and Best Practices for Data Storage and Processing

• Data Pipelines: The Backbone of Modern Data Architecture

• Mastering Data Processing with Apache Spark’s Catalyst Optimization

• Maximizing Big Data Potential: Batch and Stream Processing, Data Pipelines, and Distributed Cloud Computing

• Kappa Architecture: Stream Processing in Big Data Analytics

• 10 Best Practices for Building Scalable Data Pipelines

• Unveiling the Mysteries of Apache Hadoop and Its Thriving Ecosystem

• How to Visualize and Explore Big Data Using Python

• The Ethics of Big Data and AI: Navigating the Age of Information

• The Impact of COVID-19 on the Surge in Online Shopping Across the Globe

• How Indian Railways Leveraged Big Data Analytics to Boost Profitability

• What’s Next for Data Engineering in 2023? 7 Predictions

• Predictive Analytics: Forecasting Future Trends with Big Data

• Customer Segmentation: Unlocking Insights from Big Data

• Mastering Data-driven Decision Making: A Guide to Leveraging Predictive Analytics

• Unleashing the Power of Data: How Big Data and Data Science are Revolutionizing Decision Making in Business

• Unraveling the Power of ELK Search Engines: Real-Time Analytics and Beyond

• Key Algorithms for ELK-Based Search Engines for Digital E-Commerce Platforms

• Optimizing Spark Performance with AQE: A Deep Dive into Apache Spark’s Adaptive Query Execution

• How to Optimize E-commerce using Data-Driven Segmentation and Personalized Recommendations

• The power of dataframe in Pandas

Personal Finance & Heatlh

• Improve Your Posture and Reduce Back Pain: Tips and Exercises for Better Spine Health

• The Psychology of Money: How to Master Your Finances and Achieve Financial Success

• Millennial Habits for 2023: The Roadmap to Success and Happiness

• How I transformed from Software Quality Engineering to Data Science World

Software Testing and Quality Engineering

• Mobile App Testing Essentials: A Guide for Developers and QA Professionals
• Importance of XPath in Web Automation

I am currently looking for new opportunities. My inbox is always open, whether you have a question or just want to say hi, you can always connect with me.

Python

Spark

Jupyter

TensorFlow

Pytorch

Scikit Learn

FastAPI

Docker